Composite Renewable Energy Index for MENA Region

By Ahmed Abdel Raouf Mohamed Salama

A Thesis submitted to Faculty of Engineering at

Cairo University and Kassel University in Partial Fulfillment of the

Requirements for the Degree of Master of Science

In RENEWABLE ENERGY AND ENERGY EFFICIENCY

Kassel University, Kassel, Germany

Faculty of Engineering, Cairo University, Giza, Egypt

2013

Composite Renewable Energy Index for

MENA Region

By Ahmed Abdel Raouf Mohamed Salama

A Thesis submitted to Faculty of Engineering at

Cairo University and Kassel University in Partial Fulfillment of the

Requirements for the Degree of Master of Science

In

RENEWABLE ENERGY AND ENERGY EFFICIENCY

Under supervision of

Prof. Dr. Mohamed Elsobki Prof. Dr Dirk Dahlhaus Cairo University Kassel University

Prof. Dr. Mohab Halloudah Dr. Tareq Emtairah Cairo University Regional Center for Renewable

Energy and Energy Efficiency

Kassel University, Kassel, Germany

Faculty of Engineering, Cairo University, Giza, Egypt

2013

Composite Renewable Energy Index for

MENA Region

By Ahmed Abdel Raouf Mohamed Salama

A Thesis submitted to Faculty of Engineering at

Cairo University and Kassel University in Partial Fulfillment of the

Requirements for the Degree of Master of Science

In RENEWABLE ENERGY AND ENERGY EFFICIENCY

Approved by the Examining Committee

Prof. Dr. Mohamed El-Sobki Faculty of Engineering, Cairo University

Thesis Advisor and Member

Prof. Dr. Dirk Dahlhaus Chair of communication laboratory, Kassel University

Member

Prof. Dr.AmrAdly Faculty of Engineering, Cairo University

Member

Dr.-Ing. Hani Nokraschy Nokraschy Engineering GmbH, Germany

Member

Declaration

To the best of my knowledge I do hereby declare that this thesis is my own work. It has not been submitted in any form of another degree or diploma to any other university or other institution of education. Information derived from the published or unpublished work of others has been acknowledged in the text and a list of references is given. Place: Kassel, Germany Date: 28/2/2012 Name: Ahmed Salama Signature:

i

Acknowledgments

In the name of Allah,

I would like to thank my supervisors Prof. Dr. Mohamed Elsobki, and Prof Dr. Mohab Halloudah for their continuous support and encouragement.

My sincere thanks also go to my reviewer Prof. Dr. Dirk Dahlhaus.

Special thanks to Prof. Adel Khalil, Dr. Sayed Kaseb and Ms. Anke Aref for their support and guidance during all REMENA period.

Special thanks for Prof. Galal Osman and Dr. Mohamed Ali from Mansoura University.

Special thanks for Dr. Tareq Emtairah, Eng Amel Bida, Eng. Maged Mahmoud, Nurzat myrsalieva, all RCREEE staff and Interns for supporting me to achieve this thesis.

In addition, I would like to express my appreciation to Dr. Hatem Elrefaie for his continuous guidance and his valuable comments.

Sincere thanks to Dr. Mohammed El-Khayat for helping me in filling the Expert Survey.

Also, I would like to thank the German Academic Exchange Service (DAAD) providing me with this great Scholarship.

Sincere thanks to my lovely parents my father, my mother, my Brother Sameh, my Sisters Hanan and Amel for their continuously encouragement throughout the years of my studies and work.

ii

Table of Contents

DECLARATION ........................................................................................................................ IV

ACKNOWLEDGMENTS ............................................................................................................. I

TABLE OF CONTENTS ............................................................................................................ II

LIST OF TABLES ....................................................................................................................... V

LIST OF FIGURES .................................................................................................................. VII

LIST OF ABBREVIATIONS .................................................................................................. VIII

ABSTRACT ................................................................................................................................ X

CHAPTER 1 : INTRODUCTION ............................................................................................ 1

1.1. INTRODUCTION ........................................................................................................... 1

1.2. RCREEE .......................................................................................................................... 1

1.3. DEFINITIONS OF RE COMPOSITE INDEX ELEMENTS .......................................... 2

CHAPTER 2 : RELATED WORK ........................................................................................... 4

2.1. INTRODUCTION ............................................................................................................ 4

2.2. CURRENT RE INDICES ................................................................................................. 4

2.2.1. ERNST & YOUNG RE INDEX .................................................................................... 4

2.2.2. RENEWABLE ENERGY MARKET COMPETENCE INDEX ................................... 4

2.2.3. BRIT SAMBORSKY PROPOSED FRAME WORK FOR RE INDEX ....................... 5

2.3. THE AIM OF THE RESEARCH ..................................................................................... 5

2.4. CONCLUSION................................................................................................................. 6

CHAPTER 3 THEORETICAL FRAMEWORK FOR PROPOSED COMPOSITE INDEX ......................................................................................................................................... 7

3.1. INTRODUCTION ........................................................................................................... 7

3.2. DATA COLLECTION AND MATHEMATICAL METHODOLOGY FOR THE COMPOSITE INDEX ............................................................................................................... 7

3.3. GENERAL INDEX .......................................................................................................... 8

3.3.1. MARKET STRUCTURE .......................................................................................... 8

3.3.1.1. PRIVATE SECTOR PENETRATION/ MARKET ACCESS ................................... 9

3.3.1.1.1. INDEPENDENT POWER PRODUCER (IPP) INDICATOR .............................. 9

3.3.1.1.2. POWER PURCHASE AGREEMENT INDICATOR ......................................... 10

3.3.1.1.3. AUTO PRODUCER INDICATOR ..................................................................... 12

iii

3.3.1.2. GRID CONNECTIVITY/ACCESS .................................................................... 13

3.3.1.2.1. INTERCONNECTION AVAILABILITY AND CAPACITY INDICATORS ... 13

3.3.1.2.2. PRIORITY ACCESS & DISPATCH INDICATOR ........................................... 16

3.3.1.2.3. GRID CONNECTION RULES (GRID CODE) .................................................. 18

3.3.2. POLICY FRAME WORK ........................................................................................... 20

3.3.2.1. STRATEGY ............................................................................................................ 20

3.3.2.1.1. ANNOUNCEMENT OF RE TARGET WITH AN ACTION PLAN ................ 20

3.3.2.1.2. PERCENTAGE OF RE SHARE IN MW .......................................................... 22

3.3.2.1.3. RESIDENTIAL PRICE INDICATOR ............................................................... 23

3.3.2.2. RE REGULATIONS ............................................................................................... 26

3.3.2.2.1. NET METERING INDICATOR ........................................................................ 26

3.3.2.2.2. COMPETITIVE BIDDING ................................................................................ 28

3.3.2.2.3. FEED IN TARIFF INDICATOR ....................................................................... 30

3.3.3. INSTITUTIONAL CAPACITY ................................................................................ 31

3.3.3.1. GOVERNANCE QUALITY .................................................................................. 32

3.3.3.1.1. EASE OF DOING BUSINESS INDEX ............................................................. 32

3.3.3.2. RE INSTITUTIONS .............................................................................................. 35

3.3.3.2.1. NO. OF POLICIES FORMULATED ................................................................. 35

3.3.3.2.2. RE AGENCIES .................................................................................................. 35

3.3.4. FINANCE & INVESTMENT .................................................................................... 37

3.3.4.1. TAX MEASURES/ FISCAL INCENTIVES ........................................................ 37

3.3.4.1.1. CUSTOMS DUTY INDICATOR: ..................................................................... 37

3.3.4.1.2. EXISTING INCENTIVES (GRANTS, SUBSIDIES, SOFT LOANS) .............. 39

3.3.4.2. RISK MITIGATION ............................................................................................. 40

3.3.4.2.1. RE FUND INDICATOR .................................................................................... 40

3.3.4.2.2. SOVEREIGN GUARANTEE ............................................................................ 41

3.3.4.3. INVESTMENT SIZE ............................................................................................ 42

3.3.4.3.1. FUTURE RE INVESTMENT ANNOUNCED INDICATOR ........................... 42

3.4. TECHNOLOGY SPECIFIC INDICES(WIND, CSP, PV)............................................... 43

3.4.1. INSTALLED BASE .................................................................................................... 43

3.4.1.1. TECHNOLOGY INSTALLED CAPACITY INDICATOR ................................... 43

3.4.2. NATIONAL TARGET ................................................................................................ 45

3.4.2.1. TECHNOLOGY YEARLY TARGET SIZE INDICATOR .................................... 45

3.4.2.2. DETAILED ACTION PLAN INDICATOR (PLANNED PROJECTS) ................. 47

iv

3.4.3. RESOURCE POTENTIAL ......................................................................................... 49

3.4.3.1. RESOURCE QUALITY ASSESSMENT INDICATOR (MAP, ATLAS) ............. 49

3.4.3.2. RESOURCE POTENTIAL INDICATOR IN TWH/YEAR .................................... 49

3.5. CONCLUSION.................................................................................................................... 51

CHAPTER 4 THE RESULTS AND ROBUSTNESS ANALYSIS ....................................... 52

4.1. INTRODUCTION ............................................................................................................... 52

4.2. COMPOSITE RE INDEX RESULTS ................................................................................. 52

4.3. ROBUSTNESS ANALYSIS FOR COMPOSITE RE INDEX .......................................... 54

4.3.1. CORRELATION ANALYSIS .................................................................................... 54

4.3.2. INDICATORS SENSITIVITY ANALYSIS ............................................................... 57

4.3.2.1. HIGH SENSITIVITY INDICATORS .................................................................... 58

4.3.2.2. LOW SENSITIVITY INDICATORS .................................................................... 58

4.3.3. EXPERTS SURVEY ANALYSIS ............................................................................ 59

4.3.4. ERNST & YOUNG COMPARISON ........................................................................ 60

4.4. HIGHLIGHTING THE WEAK AREAS FOR FUTURE IMPROVEMENT .................... 62

4.5. CONCLUSION................................................................................................................... 64

CHAPTER 5 CONCLUSIONS AND FUTURE WORK ...................................................... 66

5.1. CONCLUSION................................................................................................................... 66

5.2. FUTURE WORK................................................................................................................ 69

APPENDIX A ............................................................................................................................. 70

APPENDIX B ............................................................................................................................. 72

APPENDIX C ............................................................................................................................. 74

APPENDIX D ............................................................................................................................. 79

APPENDIX E ............................................................................................................................. 81

ANNEX ...................................................................................................................................... 83

REFERENCES ........................................................................................................................... 86

GاIJKL ............................................................................................................................................. I

v

List of Tables Table 1: IPP scoring system ......................................................................................... 9

Table 2: IPP scoring process ...................................................................................... 10

Table 3: PPA scoring system ...................................................................................... 11

Table 4: PPA Scoring process .................................................................................... 11

Table 5: Auto producer Scoring system ...................................................................... 12

Table 6: Auto producer Scoring process ..................................................................... 13

Table 7: Numbers of Interconnections scoring process ............................................... 15

Table 8: Capacity of interconnections scoring process ................................................ 16

Table 9: Priority access &Dispatch scoring system ..................................................... 17

Table 10: Priority access &dispatch scoring process ................................................... 18

Table 11: Grid code scoring system ............................................................................ 19

Table 12: Grid Code Scoring Process ......................................................................... 19

Table 13: Announcement of RE Target with an action plan scoring System ............... 21

Table 14: Announcement of RE Target with an action plan scoring Process ............... 21

Table 15: RE share % in MW Scoring Process ........................................................... 23

Table 16: Residential price scoring process ................................................................ 26

Table 17: Net Metering Scoring System ..................................................................... 27

Table 18: Net Metering Scoring Process..................................................................... 28

Table 19: Competitive Bidding Scoring System ......................................................... 29

Table 20: Competitive Bidding Scoring Process ......................................................... 29

Table 21: FIT Scoring System .................................................................................... 30

Table 22: FIT Scoring Process ................................................................................... 31

Table 23: Ease of doing business scoring process ....................................................... 33

Table 24: CPI scoring process .................................................................................... 34

Table 25: RE Agencies scoring system ....................................................................... 35

Table 26: RE Agencies Scoring Process ..................................................................... 36

Table 27: Customs duty Scoring System .................................................................... 38

Table 28: Customs Duty scoring process .................................................................... 39

Table 29: Existing Incentives Scoring System ............................................................ 39

Table 30: Existing Incentives Scoring Process............................................................ 40

Table 31: RE fund scoring system .............................................................................. 41

Table 32: RE Fund scoring process ............................................................................ 41

Table 33: Future RE investment announced scoring process ....................................... 42

Table 34: current installed capacity scoring Process for diff. Technology Indices ....... 44

Table 35: Yearly Target size scoring Process for diff. Technology Indices ................. 46

Table 36: Target announced for different technology in MW ..................................... 47

Table 37: Detailed action plan(planned Projects)scoring Process for diff. Technology 48

Table 38: Resource potential Indicator in TWh/Year scoring process ......................... 50

Table 39: Composite RE Index Ranks and Scores ...................................................... 53

Table 40: General Index Ranking Results ................................................................... 53

Table 41: Wind Index Ranking Results ...................................................................... 53

Table 42: CSP Index Ranking Results ........................................................................ 54

Table 43: PV Index Rankin Results ............................................................................ 54

Table 44: the correlation coefficient between highly correlated Indicators .................. 55

Table 45: Sensitivity Indicators which affect the Composite RE Index Ranking result 58

Table 46: Correlation between Composite RE Index and Expert survey Results ......... 59

Table 47: Correlation between the results of Technology Indices and Expert evaluation .................................................................................................................................. 60

vi

Table 48: Correlation between E&Y all renewables Index and Composite RE Index .. 61

Table 49: Correlation between E&Y renewable Indices and Composite RE Index ...... 61

Table 50: Market Structure sub general Index scores and Ranks ................................. 63

Table 51: Policy Framework sub general Index scores and Ranks .............................. 63

Table 52: Institutional Capacity sub General Index scores and Ranks ......................... 63

Table 53: Finance &Investment sub general Index scores and Ranks .......................... 63

Table 54: Weight of each technology Indices ............................................................. 85

vii

List of Figures

Figure 1: Map illustrates RCREEE M.S. ...................................................................... 2

Figure 2: the construction of Composite Index [4] ....................................................... 3

Figure 3: Total Electrical Installed Capacity and Total RE Capacity Including Hydro in RCREEE M.S. ............................................................................................................. 6

Figure 4: General Framework of constructing Composite RE Index ............................. 7

Figure 5: Sub-Indices of General Index ........................................................................ 8

Figure 6: Framework of constructing Market Structure as a sub-index for general Index .................................................................................................................................... 9

Figure 7 Policy Framework construction as a sub-index for general Index .................. 20

Figure 8 Percentage of Total RE share in current MW installed capacity for RCREEE M.S. ........................................................................................................................... 22

Figure 9: Average Price for KWh in $ cents based on 482.5 KWh consumption. ........ 25

Figure 10 Institutional Capacity construction as a sub-index for general Index ........... 32

Figure 11 Finance &Investment construction as a sub-index for general Index ........... 37

Figure 12 Technology Specific Indices Construction ................................................. 43

Figure 13 Final Composite RE Index Scores .............................................................. 52

Figure 14: Correlation between Composite RE Index and Expert survey Results ........ 60

viii

List of Abbreviations

PV Photo Voltaic

CSP Concentrated Solar Power

TPES Total primary energy supply

MENA Middle East and North Africa

RCREEE Regional Center for Renewable Energy and Energy Efficiency

M.S Member States

RE Renewable Energy

EE Energy Efficiency

E &Y Ernst &Young

NGO Non Governmental Organization

BOO Build Own Operate System

IPP Individual Power Producer

PPA Power Purchase Agreement

NUG non-utility Generator

KWh Kilo Watt hour

TPA third party access

T.L Transmission Line

MW Mega Watt

GW Giga Watt

FIT Feed In Tariff

PWMSP Paving the Way for Mediterranean Solar Plan

CPI Corruption perception index

ERA Energy Regulation Authority

MNRE Ministry of New and Renewable Energy (India)

NEAL New Energy Algeria

ix

CREG The Algerian Electricity and Gas Regulation Commission

EWA Electricity & Water Authority (Bahrain)

NREA New & Renewable Energy Authority

Egypt ERA Egyptian Regulatory Agency

MEMR Ministry of Energy and Mineral resources

NERC national Energy Research Center

ERC Electricity Regulatory Commission

JREEEF Jordanian Renewable Energy and Energy Efficiency Fund

LCEC Lebanese Center for Energy conservation

REAOL Renewable Energy Authority of Libya

ADEREE National Agency for the Development of Renewable Energies and Energy Efficiency

MASEN Moroccan Agency For Solar Energy

PEA Palestinian Energy Authority

PERC Palestinian Electricity Regulatory Council

PEC Palestinian Energy & Environmental Energy Research Center

NERC The National Energy Research Centre

MWRE Directorate of Renewable and Alternative Energy (Sudan)

ANME National Agency for Energy Saving (Tunisia)

PEC Public Electricity Corporation (Yemen)

x

Abstract

By reviewing the current two RE Indices, It was found that:

Ernst &Young RE Index which depends on Expert analysis and deep investigation for each country as a separate case study from experienced teams, in addition it includes just 3 Arabian Countries.

RE Market Competence Index measures the motivation which makes the country go forward to RE and it was so valuable for the countries to see how they should plan and give them future vision regarding to Energy.

So, it was important to construct a transparent Index which measures the actual situation of RE.

In this Thesis, a new RE index methodology is being developed to measures the real situation for RE in Thirteen Arabian Countries in MENA region based on:

1- The barriers which face RE development (Market Structure, Policy Framework, Institutional Capacity, Finance and Investment)

2- The most three promising RE technologies (Wind, Photovoltaic and Concentrated Solar Power)

Combining them together in one Composite Index express the overall RE situation for each country and to clearly display the weak areas for the future improvement.

Correlation analysis, Indicator Sensitivity analysis and Expert Survey analysis have been used to assure the robustness of the proposed composite Index.

1

Chapter 1 : Introduction

1.1. Introduction

In Mediterranean region, RE sources still account a limited fraction of total primary energy supply (TPES), which relies largely on fossil fuels.

In the whole Mediterranean region RE contributed 79 (Mtoe) or 8% to TPES in 2009 divided into 2% for transportation sector mainly in South Mediterranean countries and 6% for final energy consumption which include electricity and heating.

The outlook for renewable development is to supply (156Mtoe) which means 11% of TPES by 2030 in the conservative scenario and (about 200 Mtoe)16% in the proactive scenario). The difference between these two scenarios depends on the issued RE policies and regulations and how the scale of correct implementation.

The countries in the Mediterranean region have different legal and regulatory frameworks that affect RE development. The European Union North Mediterranean countries have announced clear policies and defined regulatory regimes. Whereas South Mediterranean countries (MENA region) have less developed institutional framework, no clear RE policies and targets. [1]

Recently, a number of initiatives have been announced in some countries in MENA region related to new RE policies, establishment of RE institutions, defined ambitious targets for different technologies by national governments with plans to achieve them through national funds and international co-operation.

Interconnection between countries and each other in MENA region and between MENA region and Europe will create a sustainable energy market and industry in the MENA region.

1.2. RCREEE

RCREEE is a regional NGO established at 2008, financed through a grant agreement from different countries and the head office settled in Cairo through a host country agreement with the government of Egypt. RCREEE works for Promotion of RE development through diffusing effective RE and EE policies and technologies in the Arab region, and increase effectiveness of the RE Institutions through the regional cooperation.

RCREEE has now Thirteen Arabian countries among its members and they are welcoming additional countries from MENA region.

2

As the author conducted this work in RCREEE, so this research will be applied for 13 countries in MENA region which are RCREEE M.S. and they are illustrated in the Figure 1 and they are:

(Algeria – Bahrain – Egypt – Iraq – Jordan – Lebanon – Libya – Morocco – Palestine – Sudan – Syria – Tunisia – Yemen) [2]

Figure 1: Map illustrates RCREEE M.S.

1.3. Definitions of RE Composite Index Elements

1- Indicator: it can be defined as something that helps us to understand a specified aspect and how far we are from the goal. There for it can be a sign, a number, a graphic and so on. Indicators normally summarize the characteristics of the system by measuring the current aspects or information and it could be done by either a statistical data or questionnaire for the Experts in this aspect. [3]

Indicators will be aggregated to form a factor and finally an Index.

2- Factor: It is a category includes some Indicators which describe specified phenomena.

3- Index: It is important to define the meaning of the Index as a core of the proposed work and the clearest definition for the Index is:

It is a normalized and dimensionless scale that gives a quantitative measure of a

defined aspect of a country

A “normalized scale” means that the “Index” will have a minimum and a maximum

values. In most indices the minimum value is “0” and the maximum value is “1”.

A “dimensionless scale” refers to its nature that the “Index” has no measuring unit.

3

A “quantitative measure” indicates that the “Index” gives a number that represents the

strength (or weakness) of the aspect under measure.

An “aspect” refers to any societal behavior or quality that exists in a country in any

domain such as in economics, politics, education, gender differences and so on.

Finally, a “country” refers to the fact that the scope of work is to, solely, compare

countries among each other. [4]

4- Composite RE Index

It is an Index which measures the variation in the value of some Indices by aggregating or merging them together in a mathematical way according to the weight of each Index and The Procedure of constructing a Composite Index is illustrating in the figure 2.

Figure 2: The construction of Composite Index

Organization of the thesis The remainder of this thesis organized as follows. Chapter 2 Provides a review

about related work from different companies and researchers plus the aim of the proposed research, Chapter 3 provides the Theoretical framework of the index including selecting indicators and the method of scoring and Chapter 4 provides a result of the proposed framework and Robustness analysis.

4

Chapter 2 : Related Work

2.1. Introduction

By reviewing the previous related work of researchers and companies about constructing indices, and it worth to mention that it will be limited for RE Indices, because there are a variety of Indices in different fields.

2.2. Current RE Indices

2.2.1. Ernst & Young RE Index

Ernst & Young is a global organization. They are releasing quarterly data that ranks RE markets and technologies since 2003 called “The Country Attractiveness Indices” these Indices include 40 countries and just three countries from RCREEE M.S among them (Morocco, Egypt and Tunisia).

E&Y All renewables index consist of:

Renewable infrastructure index: the weight of this index is 35% from whole RE Index and it include an assessment by country of the general regulatory infrastructure for renewable energy.

Technology factors: The weights of these factors are 65% (these provide resource specific assessments for each country and comprise the Wind index (55%), solar index 32% (PV index 85%, CSP index 15%), Biomass and other resources index (13%) [5] E &Y Indices are based on a template questionnaire plus additional research undertaken from Experts and further insight provided by members of E&Y team with no clear scoring process announced.[4]

2.2.2. Renewable Energy Market Competence Index

By using a new methodology for constructing an index that quantitatively, objectively, and analytically describes the competence of renewable energy Market of: 8 RCREEE countries: Algeria, Egypt, Jordan, Lebanon, Libya, Morocco, Syria, and Tunisia. 10 benchmark countries: Brazil, Turkey, Spain, Greece, South Africa, Malaysia, India, Chain, USA, and Germany.

It includes two types of Indicators: - 13 General Indicators

5

They describe the general characteristics of the country regarding to political, social, economic situation in addition to the conditions of the energy sector, fossil fuel sustainability, CO2 emission level of the country, and the available financing for RE projects.

- 5 Technology Indicators They describe the manufacturability of each technology in the country, economic potential, target, institution, and FIT. [4]

2.2.3. Brit Samborsky Proposed frame work for RE Index

He constructed a framework for RE progress Index depends on the barriers of RE development in the Arab region include:

1- 1 General Index include 18 Indicators Covering: (Market, Policy Framework, Institutional/Planning and Investment/finance) 2- Technology specific Indices including 8 Indicators. [6]

For more details and investigations with the previous 3 Frameworks see the (Appendix A, B) which illustrates the main indicators for each Proposed Index. [4], [6]

2.3. The Aim of the research

1- To benchmark and rank countries to provide a motivation for the countries to improve their condition for RE deployment through a newly developed Index by assessing:

- The existing RE situation and opportunities of the RE markets in RCREEE Member States.

- Policies that governments are adopting to promote RE market and industry for the future.

- Effectiveness of relevant Institutions. - Easiness of doing Investment for different RE technologies.

2- To make a robustness analysis for the results. 3- Able to clearly display the weak areas for the future improvements.

Note:

It is not a must that the country which has high share from RE to take the first Rank, because we merging a group of indicators together to finally reach one score for each country (composite Indicators or Index) and figure 3 is showing an idea about the Installed capacities and RE share in RCREEE Countries.

6

Figure 3: Total Electrical Installed Capacity and Total RE Capacity Including Hydro in RCREEE M.S.

2.4. Conclusion

By reviewing 3 Indices frameworks, it was found that:

E&Y Renewables Index depends more on Expert analysis and deep investigation for each country as a separate case study from experienced teams so it has no clear scoring process.

RE Market Competence Index measure the motivation which makes the country go forward to RE and it was so valuable for the countries to see how they should plan for the future regarding to Energy.

So, it was important to construct a transparent Index which measures the actual situation of RE.

Brit Samborsky Proposed Framework relies on the RE Barriers and the proposed work will be based on the main barriers mentioned in his Framework for 13 Arabian Countries.

0

5000

10000

15000

20000

25000

30000

35000

Total Installed Capacity

Total RE capacity

MW

7

Chapter 3 Theoretical Framework for proposed composite RE Index

3.1. Introduction

For the theoretical framework construction, the phenomena (Categories and Factors) have to be defined and then to choose the appropriate Indicators which will give a clear description for the Phenomena.

The following Theoretical frame work which has been developed after having a general overview with the previous Indices in addition to a lot of negotiations with RE Experts, and it worth to mention that the selecting indicators always a point of dispute from RE Experts and analysts, but at the end by making a Robustness analysis, the reality of the proposed theoretical framework will be checked.

3.2. Data Collection and mathematical methodology for the Composite Index

Collection data has been done in RCREEE based on a prepared general questionnaire shown in (Appendix C) for the Regional Center focal point in each country in addition to including some other sources for verifying the data, to fill the missing data in their answers and to get some other data which wasn’t covered in the questionnaire. [D]

The complete mathematical methodology for constructing the Composite Renewable Energy Index and the method of calculating the weight for each Indicator illustrated in the Annex.

The main framework for constructing the composite RE Index illustrated in the figure 4

Figure 4: General Framework of constructing Composite RE Index

8

3.3. General Index

By constructing the general Index depend on the barriers of RE development. General Index will consist of 4 sub-Indices as shown in figure 5.

Figure 5: Sub-Indices of General Index

3.3.1. Market structure

By selecting the Market, the situation of RE market will be measured in the selected Countries as shown in the figure 6, this could be done by measure the participation of Private investors in the current and future projects but also could be all existing projects are public and in this case it will be a benefit just for the manufacturers not for the developer who want to work and invest according to BOO system. The RE Market could be measured also by knowing the reliability of the grid, rules for connecting to the grid, priority of dispatching RE power Plants and the interconnection with neighborhood countries which will express an attractive situation of a country among the others and it will encourage to have more RE projects not just for self-consumption but to extend this stage and sell the Renewable electricity to other Countries.

9

Figure 6: Framework of constructing Market Structure as a sub-index for general Index

3.3.1.1. Private sector penetration/ Market access

3.3.1.1.1. Independent power producer (IPP) Indicator

An Independent Power Producer (IPP) or a non-utility Generator (NUG) is a private entity which owns and or operates facilities to generate electric power for sale to a utilities and end users. [7]

In almost of the countries under study, the monopoly of electricity generation has been done by governmental Power utilities which inhibit the Investors to plan their own RE power projects.

So by issuing IPP by law, it reflects the market openness to private sharing to attract Investors to come and invest in the country.

IPP scoring system illustrated in table 1 and it will be calculated in a scale from (0 to 2) and scoring process illustrated in the table 2.

Table 1: IPP scoring system

IPP scoring system Score IPP option provided by law 1

IPPs producing RE in practice under tender (+0.5), current project (+1) Otherwise 0

10

Table 2: IPP scoring process

Country IPP issued

by law IPPs producing RE

in practice Actual

IPP Score Normalized IPP

Score

Algeria yes no 1 0.5

Bahrain yes no 1 0.5

Egypt yes under tendering 1.5 0.75

Iraq yes no 1 0.5

Jordan yes under tendering 1.5 0.75

Lebanon no no 0 0

Libya no no 0 0

Morocco yes yes 2 1

Palestine yes no 1 0.5

Syria yes no 1 0.5

Sudan yes no 1 0.5

Tunisia yes no 1 0.5

Yemen yes no 1 0.5

3.3.1.1.2. Power Purchase agreement Indicator

It measures the guarantee of buying Power generated from IPP. So it is a contract between two parties (Buyer and Seller) and they are defining the commercial terms, payment procedure, and length of the contract with a predetermined rate of KWh generated.

The main advantages of PPA for renewable Energy Projects that the Investor (seller) will know how is the return on Investment before starting to putting his money on the line to be sure that he is in the safe side and guarantee his profit.

PPA scoring system illustrated in the following table 3 and the scoring Process for the countries illustrated in the table 4. It will be calculated in a scale from (0 to 2)

11

Table 3: PPA scoring system

PPA scoring system Score PPA issued by law 1

PPA are producing RE in practice under tender (+0.5), current project (+1) otherwise 0

Some countries like Lebanon don’t have this law but they are evading from the law and practice it under the power rental agreement so this country will be given the half of the score because they don’t have the law in Lebanon but it is already practiced.

Table 4: PPA Scoring process

Country PPA issued by

law PPA producing RE

in practice Actual

PPA Score Normalized PPA Score

Algeria yes yes 2 1

Bahrain no 0 0

Egypt yes (under preparation) 1.5 0.75

Iraq no no 0 0

Jordan yes no 1 0.5

Lebanon no (power rental

agreement)

Plan for power rental from wind farm (60

to 100 MW) 1 0.5

Libya no no 0 0

Morocco yes yes 2 1

Palestine yes - 1 0.5

Syria yes - 1 0.5

Sudan no no 0 0

Tunisia yes no 1 0.5

Yemen no no 0 0

12

3.3.1.1.3. Auto producer Indicator

An auto producer is a private Entity which generates electricity for their own use with the option to sell the extra generated electricity to the Electrical utility or to a third party through the national electricity grid.

It worth to mention that the difference between auto producer and Individual power producer is that the latter is generate electricity for selling to utility or End users as a primary activity, on the other hand the Auto producer primary activity is to generate electricity wholly or partially for his own use.

Auto producer of RE scoring system illustrated in the table 5 and the scoring process for the countries in the table 6., scores will be calculated in a scale from (0 to 3)

Table 5: Auto producer Scoring system

Auto producer scoring system Score Auto producer issued by law (1) , draft law (0.5)

Auto-producer with option to sell to third parties/network TPA

+1

RE Auto-producer projects in practice in preparation (+0.5), current project (+1)

Otherwise 0

13

Table 6: Auto producer Scoring process

3.3.1.2. Grid connectivity/access

3.3.1.2.1. Interconnection availability and Capacity Indicators

According to the Interconnection with neighbored countries this is reflecting how much the merit of this country site among the others and also it strengthens the regional relation and cooperation among them.

With the higher capacity of Interconnection, the more reliability and security of supply will be strengthened for interconnected systems, develops market opportunities and makes an economical way of increasing supply without installing new power plants.

For Example Morocco and Spain with two interconnection lines with total capacity 1400 MW is strengthening the market of RE and attract local Investors and Europe

Country Auto-producer

option TPA

Auto producer

Score

Normalized Auto producer

Score

Algeria yes no 1 0.333

Bahrain yes no 1 0.333

Egypt yes yes 2.5 0.833

Iraq yes no 1 0.333

Jordan yes no 1 0.333

Lebanon no (still in draft) no 0.5 0.1667

Libya no no 0 0

Morocco yes yes 3 1

Palestine yes no 1 0.333

Syria yes no 1 0.333

Sudan yes no 1 0.333

Tunisia yes yes 2 0.667

Yemen yes no 1 0.333

14

Investors to invest with guarantee that they will find a way to sell the generated electricity.

In spite of Arabian countries have a huge potential for renewable based generation development but the big part from it will remain unexploited unless the development walks in parallel with both installing RE projects and strengthen the transmission infrastructure and current interconnections.

In Europe countries, they have strong interconnection with high transfer capacity which let them invest cross border and establish the liberalization of the Market. [1]

The Interconnection between countries, length, voltage, Capacity of Interconnection and the status of the Interconnection are listed in the (Appendix D)

Numbers of Interconnections scoring process are listed in the table 7. It will be calculated on a scale from 0 to no. of interconnected countries)

15

Table 7: Numbers of Interconnections scoring process

Capacity of interconnections scoring process illustrated in the Table 8. It will be calculated on a scale (from 0 to aggregated MW capacity for all interconnected countries).

Country Actual no. of

Interconnection with neighbors

Normalized Interconnection with

neighbors Score

Algeria 2 0.667

Bahrain 1 0.333

Egypt 3 1

Iraq 0 0

Jordan 3 1

Lebanon 1 0.333

Libya 2 0.667

Morocco 2 0.667

Palestine 2 0.667

Syria 3 1

Sudan 0 0

Tunisia 2 0.667

Yemen 0 0

16

Table 8: Capacity of interconnections scoring process

3.3.1.2.2. Priority access & dispatch Indicator

When Renewable electricity resources are drawn prior to conventional resources, this will guarantee the continuity of RE equipment operation.

So, by applying Priority dispatch for Renewable generation, it is not allowed to shut down a Renewable power plant with an exception of system security constraints.

So if there is an excess power generation they have to regulate and reduce the output of the normal conventional power plants with this excess amount but this will be for a certain limit because after shutting down the conventional power plant and afterwards to start up it again, this will cause an additional start up cost, will take a time to make the Power Plant in service and as a result of stop and start from time to time it will increase maintenance and decrease the reliability of the system.

Country Actual Interconnection

Capacity

Normalized Interconnection Capacity Score

Algeria 3238 0.758

Bahrain 600 0.141

Egypt 807 0.189

Iraq 0 0

Jordan 1570 0.368

Lebanon 1000 0.234

Libya 891 0.209

Morocco 4270 1

Palestine 37 0.009

Syria 3000 0.703

Sudan 0 0

Tunisia 1019 0.239

Yemen 0 0

17

To avoid this issue it will be advisable to make it in service with its minimum output power and try to find a way for the excess generation like Interconnection with neighbored or encourage consumers to consume more for free at these times, this will save us the cost of starting the power plant again in addition it will increase stability of the system because immediately the conventional power plant can work with its maximum output generation. [8]

Priority access & dispatch scoring system will be calculated in a scale from (0 to 1) shown in table 9, and scoring process shown in table 10.

Table 9: Priority access &Dispatch scoring system

Priority access & dispatch for scoring system

Score

No Priority access & dispatch issued by law

0

Priority access & dispatch issued by law 1, Draft (0.5)

18

Table 10: Priority access &dispatch scoring process

3.3.1.2.3. Grid Connection Rules (Grid Code)

Grid code is required to cover all technical aspects relating to the connection with T.L. system. Grid code specifies data which system users are obliged to provide to national grid. So it consist of a set of rules for electricity producers whose connect to the electricity grid , they are usually required to adjust the amount of power that is sent through the grid according to the grid code and the max voltage allowed to not cause surges. [9]

With high RE generation, grid code must be issued to prevent of service interruption.

The system should compose of certified equipment, appropriate technical standards and some additional equipment like power conditioning equipment, safety equipment, meters and instrumentation. [10]

Country Priority access & dispatch

Actual Access & dispatch priority

Score

Normalized Access & dispatch priority Score

Algeria Yes 1 1

Bahrain No 0 0

Egypt Yes, draft 0.5 0.5

Iraq No 0 0

Jordan Yes 1 1

Lebanon No 0 0

Libya No 0 0

Morocco No 0 0

Palestine Yes 1 1

Syria No 0 0

Sudan No 0 0

Tunisia No 0 0

Yemen No 0 0

19

Grid Connection Rules (Grid Code) scoring system will be calculated in a scale from (0 to 3) in the Table 11, and scoring process in table 12

Table 11: Grid code scoring system

Grid Code scoring System Score There is no Grid Code exist 0, in Draft phase (1)

Wind Grid Code exist 1 CSP Grid Code exist +1 PV Grid Code exist +1

Table 12: Grid Code Scoring Process

Country Wind PV CSP Actual Grid code

Score Normalized Grid

code Score

Algeria Yes yes yes 3 1

Bahrain No no no 0 0

Egypt (draft) no no 1 0.333

Iraq No no no 0 0

Jordan Yes Yes Yes 3 1

Lebanon Under preparation 1 0.333

Libya No no no 0 0

Morocco Yes yes yes 3 1

Palestine Yes yes yes 3 1

Syria Yes yes no 2 0.667

Sudan No no no 0 0

Tunisia Yes yes yes 3 1

Yemen No no no 0 0

20

3.3.2. Policy Frame work

Policy framework is a principal to promote RE in a region as shown in figure 7, and that could be done by:

- Strategic decisions like issuing a RE target and oblige the existing organization to work on it and announcing a price for electricity which illustrate the strategic thinking for the future.

- Announcing Regulations to help in promoting and deployment of RE like FIT, Competitive Bidding and net metering.

Figure 7 Policy Framework construction as a sub-index for general Index

3.3.2.1. Strategy

3.3.2.1.1. Announcement of RE Target with an Action plan

By measuring if an ambitious RE target has been set by the country because it means that the country already knew the importance of RE to fulfill its needs in the future and estimated its resources which related to announced target.

To be sure that the country is serious to achieve its target, so this country should has an action plan to get the target which it announced before, and this could be by a policy paper issued from the Country called energy strategy, drafting the transition towards higher RE shares, and it could be measured by seeing the published RE Road map (PWMSP).

21

Announcement of RE Target with an action plan scoring system in a scale from (0-2) and scoring process illustrated in tables 13 and 14.

Table 13: Announcement of RE Target with an action plan scoring System

Announcement of RE Target scoring system

Score

No RE target announced 0 Announced general RE target 1

Draft Road Map (PWMSP) issued +1

Table 14: Announcement of RE Target with an action plan scoring Process

Country RE Target with an

action plan

RE Target with an action plan

Score

Normalized RE Target with action

plan Score

Algeria Yes 2 1

Bahrain No 0 0

Egypt Yes 2 1

Iraq Yes with no action plan 1 0.5

Jordan Yes 2 1

Lebanon Yes 2 1

Libya yes with no action plan 1 0.5

Morocco Yes 2 1

Palestine Yes 2 1

Syria Yes with no action plan 1 0.5

Sudan Yes with no action plan 1 0.5

Tunisia Yes 2 1

Yemen Yes with no action plan 1 0.5

22

3.3.2.1.2. Percentage of RE share in MW

RE share (all forms of Renewable resources including Hydro) as a percentage from the current all installed capacity in a country as illustrated in Figure 8. That will reflect how is the current situation of RE as a result of previous decisions have been made in the past.

Percentage of RE share in MW installed scoring process by taking the % directly as shown in the table 15.

Figure 8 Percentage of Total RE share in current MW installed capacity for RCREEE M.S.

0

10

20

30

40

50

60

70

% of RE

23

Table 15: RE share % in MW Scoring Process

Due to the high difference between scores, the min. value (0) and maximum value (58.391), the condition (skewness>2 AND kurtosis > 3.5) have been achieved so to evade from this condition we have to minimize this high score till we evade from this condition to solve this problematic Indicator. So the new score to evade from this condition is (55.391).

3.3.2.1.3. Residential price Indicator

Decisions on electricity prices are often very political and foreign advice can only exert a certain amount of influence.

So by announcing the price of electricity it reflects the strategic decision which includes two important factors which are:

Country RE share % in MW installed

RE share % in MW

normalized Score

Algeria 2.221 0.038

Bahrain 0.000 0

Egypt 10.888 0.186

Iraq 14.824 0.254

Jordan 0.856 0.015

Lebanon 11.933 0.204

Libya 0.000 0

Morocco 32.327 0.554

Palestine 0.127 0.012

Syria 16.119 0.276

Sudan 58.391 1

Tunisia 6.09 0.110

Yemen 1.645 0.028

24

- The cost of fuel especially if the country imports the fuel. - Subsidy of final electricity price as a social perspective for its People.

Selecting residential sector price which consider the highest sector in Electricity consumption in MENA region which is 43% from electricity consumption and after that Industrial sector which is 23% from electricity consumption but because lack of some data to know Industrial and commercial sector average prices, the residential average price will be selected (AUE). [11]

Three proposed ways to estimate the average Price:

1- By knowing tariff segments (cost and scale of users in this segment) and by knowing how many residential users whose in the first segment, second segment etc. , it could be calculated it as follow :

Summation of: number of users * scale of the segment (KWh) * price of KWh for this segment, but because of difficulties of getting number of users for each segment, this method will not be used.

2- To know all consumptions for the country in KWh, and to know all money collected for selling these Electricity and then by dividing them to get the average price of KWh as a general for (residential, commercial, industrial).

This method will not be used because the difficulties to get the money for sold electricity.

3- To see how many Residential consumers (Residential meters), how much Energy (KWh) consumed from Residential sector then by dividing them as follow:

(Res. Consumption in KWh / number of Res. Consumers) to have the average Residential consumption per Family but actually after estimating, it was found a large difference between the countries (Bahrain average consumption = 2164 KWh/consumer/month, Morocco average consumption= 87 Kwh/Consumer/month) so, to fix and unify the Power generated to can compare between countries, the average of all countries averages consumptions will be taken and the result was 482.5 KWh/month, then by estimating the average price of this consumption for all countries and the result illustrated in figure 9.

25

Figure 9: Average Price for KWh in $ cents based on 482.5 KWh consumption.

Residential price for scoring process: the average prices will be taken as it has seen in the table 16.

0 2 4 6 8 10 12 14 16

Syria

Bahrain

Iraq

Egypt

Libya

Yemen

Lebanon

Algeria

Jordan

Sudan

Tunis

Morocco

Palestine

Average

Average Price ($cent/kWh)

$ Cents/KWh

26

Table 16: Residential price scoring process

3.3.2.2. RE Regulations

3.3.2.2.1. NET Metering

Net metering is to generate your own electricity through a renewable source. It could be a solar panel or a micro wind in your home roof and if you have an excess production not be used in your home it will be sent to the electricity grid through just one electric 2 way Meter and you will be paid for this amount of extra Energy produced (total production minus self-consumption) according to the announced prices by the Government or electric utility and usually this price is more than the normal price which bought from Electric utility to encourage use of Renewable electricity.

By the way, it worth to mention gross metering to know the difference between them.

Country Residential price in $ cents/KWh

Residential price normalized

Score

Algeria 5.361 0.336

Bahrain 0.8 0

Egypt 2.744 0.143

Iraq 0.9 0.007

Jordan 9.069 0.610

Lebanon 4.701 0.288

Libya 1.6 0.059

Morocco 11.842 0.814

Palestine 14.36 1

Syria 0.8 0

Sudan 8.21 0.546

Tunisia 9.955 0.675

Yemen 4.033 0.238

27

Gross metering means that all of your renewable electricity will be sent to the grid and you will be paid for all of your Renewable electricity with a specified rate (cost) from electrical utility or government. [12]

Net Metering is a very important Electricity Policy for the promotion of Distributed Electricity Production from Renewable Energy Sources.

Net Metering scoring system will be calculated in a scale from (0 to 2) as shown in table 17 and scoring process in table 18.

Table 17: Net Metering Scoring System

Net Metering scoring system Score Net Metering policy 1

Net metering implemented +1 otherwise 0

28

Table 18: Net Metering Scoring Process

3.3.2.2.2. Competitive bidding

It is an announced tender for installing and operating a RE project with specified capacity or to comply a given quota from the Government and usually on the BOO system and the Winner will be paid above standard market levels for its renewable generation.

It helps in promotion of RE projects and attracts investors by organizing these kind of tenders.

Competitive bidding scoring system will be calculated in a scale from (0 to 2) as it illustrated in table 19 and scoring process in table 20.

Country Net Metering

policy and Implementation

Net Metering Score

Net Metering normalized

Score

Algeria no 0 0

Bahrain no 0 0

Egypt Yes without impl. 1 0.5

Iraq no 0 0

Jordan Yes and implemented 2 1

Lebanon Yes and implemented 2 1

Libya no 0 0

Morocco no 0 0

Palestine Yes and implemented 2 1

Syria Yes without implem. 1 0.5

Sudan no 0 0

Tunisia Yes and implemented 2 1

Yemen no 0 0

29

Table 19: Competitive Bidding Scoring System

Competitive Bidding scoring system Score Competitive Bidding Policy 1 are there announced tenders +1

otherwise 0

Table 20: Competitive Bidding Scoring Process

Country Competitive Bidding Competitive

Bidding Score

Competitive Bidding normalized

Score

Algeria yes 1 0.5

Bahrain no 0 0

Egypt Yes + tenders announced 2 1

Iraq no 0 0

Jordan yes + tenders announced 2 1

Lebanon Yes 1 0.5

Libya no 0 0

Morocco Yes + tenders announced 2 1

Palestine Yes + tenders announced 2 1

Syria Yes + tenders announced 2 1

Sudan yes 1 0.5

Tunisia no 0 0

Yemen Yes + tender announced 2 1

30

3.3.2.2.3. Feed in Tariff Indicator

A feed in tariff is an amount of money which is paid by the government or utility provider for energy produced by a renewable energy producer.

FIT is considered as a very important policy for accelerating RE deployment.

FIT scheme is used to promote RE electricity generation, encourage normal people to install their small RE systems by providing investment security and encourage multipoint generation which will strengthen the reliability of electricity system.

For issuing FIT as a policy, rules of FIT must be defined which are:

For which eligible RE technology, the size of generation, location, contract duration and the most important one is FIT payment which could be one of these ways:

- Levelized cost of RE generation plus a targeted return. - Value of the RE generation for either society or Utility

For society the value will be in a form of electricity, climate change mitigation and health impacts.

For the utility the value will be for avoided extra generation cost [13]

- Auction based mechanism through a bidding and it allow bidders to set their own price and the goal from using it to deliver the lowest cost electricity to the grid.[14]

FIT for scoring system it will be calculated in a scale from (0 to 3) as illustrated in table 21, and the scoring process illustrated in table 22.

Table 21: FIT Scoring System

FIT scoring system Score Wind FIT +1 CSP FIT +1 PV FIT +1

Otherwise 0

31

Table 22: FIT Scoring Process

3.3.3. Institutional Capacity

In Institutional Capacity, two areas will be evaluated as shown in figure 10, first one is the quality of public Institutions from corruption and difficulties to get a permit for a RE Project, second area is if the countries has a RE Institution and how many RE Policies are formulated.

Country Wind FIT CSP FIT PV FIT FIT normalized

core

Algeria 1 1 1 1

Bahrain 0

Egypt 0

Iraq 0

Jordan 1

Ceiling Tariff

1

Ceiling Tariff

1

Ceiling Tariff 1

Lebanon 0

Libya 0

Morocco 0

Palestine 1 1 1 1

Syria 1 1 0.666667

Sudan 0

Tunisia 0

Yemen 0

32

Figure 10 Institutional Capacity construction as a sub-index for general Index

3.3.3.1. Governance quality

3.3.3.1.1. Ease of doing business Index

Ease of doing business Index is ranking economies for 185 Countries by assesses regulations which affect on the domestic firms and institutions, based on 10 topics covering different areas of business regulation like starting business and dealing with construction permit, with a variety of indicators giving equal weight for each topic.

• Unfortunately the Ease of doing business scores not announced in their site so it will be assumed to take ranking as scores for the proposed composite RE Index and it means that the lowest number will take the highest score and vice versa.

• Unfortunately Ease of doing business Index didn’t mention Palestine and Libya, so the assumption her that Palestine and Libya will take the same score with the lowest country score. [15]

Ease of doing business for scoring process illustrated in table 23.

33

Table 23: Ease of doing business scoring process

3.3.3.1.2. Corruption perception index (CPI)

CPI indicates the corruption on the Public sector, so it gives:

- A motivation for the different governments to work anti-corruption and make a transparency process for rules and contracts.

- An idea for Investors about how is the level of corruption in the public sectors to help him to take a decision of accepting or cancelling to penetrate in this country market.

CPI include 176 countries and territories around the world and its scores on a scale from 0 to 100, (0 indicates high corruption) and (100 indicates very clean), these

Country Ease of doing

business Index Ranking

Ease of doing business Index

normalized Score

Algeria 152 0.106

Bahrain 42 1

Egypt 109 0.455

Iraq 165 0

Jordan 106 0.480

Lebanon 115 0.407

Libya 165 0

Morocco 97 0.553

Palestine 165 0

Syria 144 0.171

Sudan 143 0.179

Tunisia 50 0.935

Yemen 118 0.382

34

numbers really reflect the reality for people living in this country through views of analysts, business people and experts in countries around the world. [16]

Unfortunately CPI Index didn’t mention Palestine as well like ease of doing business Index, so by applying the same assumption that Palestine will take the same score with the lowest country score.

CPI scoring process illustrated in the table 24

Table 24: CPI scoring process

Country CPI Score

CPI

normalized Score

Algeria 34 0.553

Bahrain 51 1

Egypt 32 0.5

Iraq 18 0.132

Jordan 48 0.921

Lebanon 30 0.447

Libya 21 0.211

Morocco 37 0.632

Palestine 13 0

Syria 26 0.342

Sudan 13 0

Tunisia 41 0.737

Yemen 23 0.263

35

3.3.3.2. RE Institutions

3.3.3.2.1. No. of policies formulated

Due to a lack of reaching all policies formulated in all countries, this Indicator will be skipped and its weight will be moved to RE Agencies.

3.3.3.2.2. RE agencies

Ministry issue the Policies and stockholders which are RE Agencies implement the policy because it can’t be perfectly implemented by ministry as it has a lot of other issues, and It can’t be implemented also by Transmission companies because its main concern is profit and how to reduce the cost, that is why issuing RE Agencies will guarantee the targeted implementation.

For example, India exceeds this stage and established a Ministry for RE (MNRE) with an aim to develop and deploy RE for supplementing the energy requirements of the country.

India has 26.9 GW RE grid connected installed capacity and 819 MW off-grid installed capacity so it’s a good ideal for implementing RE Ministry. [17]

It is important to have an Energy Regulation Authority (ERA) as an independent Agency to control and supervise the policy implementation and assure from the adequate implementation and quality of service provided according to the policy. [18]

RE Agencies for scoring system and Scoring process in tables 25 and 26 in a scale from (0.5 to 3)

Table 25: RE Agencies scoring system

RE Agencies scoring system Score RE Agency +1

Specific RE Agency +1 Otherwise (Ministry) 0.5 Regulatory Authority +1

36

Table 26: RE Agencies Scoring Process

Country RE

Agency Regulator

Specific RE Agency

Score Normalized

score

Algeria NEAL CREG 2 1

Bahrain Electricity & Water Authority (EWA) 0.5 0

Egypt NREA Egypt ERA 2 1

Iraq Ministry of Industry and Minerals

(Environment and Energy Research Center) 0.5 0

Jordan Ministry of

MEMR (NERC)

ERC 1.5 0.666667

Lebanon LCEC 0 0 1 0.333333

Libya REAOL 0 0 1 0.333333

Morocco ADEREE 0 MASEN 2 1

Palestine PEA

(PEC) PERC 0.5 1.5 0.666667

Syria NERC 0.5 0

Sudan MWRE (Institute of Energy researches) 0.5 0

Tunisia ANME 0 0 1 0.333333

Yemen Public Electricity Corporation 0.5 0

37

3.3.4. Finance & Investment

Figure 11 Finance &Investment construction as a sub-index for general Index

It is important to know how is the weather of Investment in the country to help Investor in a decision making of his business like is there a highly customs duty for the component of a RE project and if the country can guarantee his continuity of his project with its profit, and the selected indicators of Finance &Investment illustrated in figure 11.

3.3.4.1. Tax measures/ Fiscal incentives

Fiscal incentive is “an economic incentive that provides individuals with a reduction in

their contribution to the public treasury via income or other taxes or with direct

payments from the public treasury in the form of rebates or grants”. [19]

3.3.4.1.1. Customs duty:

The main incentive to promote RE Energy for different technologies is an exemption of customs duty on import of specific goods which required installing RE Projects. The exemption should be subjected to compliances to the RE purposes otherwise the benefits will be lost. [20]

38

For example in Egypt which has a customs duty exemption for RE components but this will be achieved just in one condition that the importer should take the proof of the official RE Agency (NREA) for the list of RE components to admit the exemption.

Customs duty for scoring process, the tariffs data available in World Trade Organization site WTO.org, but unfortunately just 6 Countries found from the countries under the study, so the scoring system will be changed to the normal simple way (0 or 1) as illustrated in table 27 and scoring process in table 28

Table 27: Customs duty Scoring System

Customs duty scoring process Score Customs duty Exemption 1

otherwise 0

39

Table 28: Customs Duty scoring process

3.3.4.1.2. Existing Incentives Indicators (Grants, subsidies, soft loans)

Existing incentives could be in a form of Cash grant or with interest reduced Loan up to 100% of the investment.

For scoring process: the existing incentives for all countries under study will be recorded and scoring system, scoring process is illustrated in Table 29 and 30.

Table 29: Existing Incentives Scoring System

Existing incentives scoring system Score Existing incentives 1

otherwise 0

Country Customs duty Customs duty

Score

Customs duty

normalized Score

Algeria 5% 0 0

Bahrain 0 0 0

Egypt 0% 1 1

Iraq No exemption 0 0

Jordan 0% 1 1

Lebanon No exemption 0 0

Libya No exemption 0 0

Morocco 2.5% 0 0

Palestine 0% 1 1

Syria No exemption 0 0

Sudan For strategic invest. only 0 0

Tunisia 0% 1 1

Yemen No exemption 0 0

40

Table 30: Existing Incentives Scoring Process

3.3.4.2. Risk Mitigation

3.3.4.2.1. RE fund Indicator

Early stages of RE projects are the most risky especially in financing that is why by establishing a governmental RE fund will mitigate the risk for public utilities and private ones.

Normally Investors rely on the outside support (governmental agencies) for managing the risk either if it is a political and regulatory risk or financial risk. [21]

Country Existing incentives

Score

Existing incentives

normalized Score

Algeria 0 0

Bahrain 0 0

Egypt 1 1

Iraq 0 0

Jordan 1 1

Lebanon 1 1

Libya 0 0

Morocco 1 1

Palestine 1 1

Syria 1 1

Sudan 1 1

Tunisia 1 1

Yemen 0 0

41

RE fund for scoring system and process are illustrated in tables 31 and 32.

Table 31: RE fund scoring system

RE fund scoring system Score Existence of RE Fund 1

otherwise 0

Table 32: RE Fund scoring process

3.3.4.2.2. Sovereign Guarantee

It is important for large scales Investors to be sure from Sovereign guarantee existence to mitigate the risk of RE Projects but due to the lack of data, this Indicator will be excluded.

Country RE fund RE Fund

normalized Score

Algeria yes 1

Bahrain no 0

Egypt yes 1

Iraq yes 1

Jordan yes 1

Lebanon no 0

Libya no 0

Morocco yes 1

Palestine no 0

Syria no 0

Sudan yes 1

Tunisia yes 1

Yemen no 0

42

3.3.4.3. Investment size

3.3.4.3.1. Future RE Investment announced Indicator

To measure the size of Investment and how much it is high to give an idea for Investors how is the weather of investment in this country especially after transforming the investment into cash as it illustrated in table 33 for scoring process.

the announced investment money for the announced countries projects are recorded and aggregated.

Table 33: Future RE investment announced scoring process

Country Future RE Investment

announced (Million Euro)

Future RE Investment announced

normalized Score

Algeria 1207 0.450

Bahrain 0 0

Egypt 1602.34 0.597

Iraq 0 0

Jordan 2685 1

Lebanon 26.1265 0.010

Libya 131 0.049

Morocco 1421 0.529

Palestine 17.3029 0.006

Syria 140 0.052

Sudan 239.5 0.089

Tunisia 2075.6 0.773

Yemen 94 0.035

43

3.4. Technology Specific Indices(WIND, CSP, PV)

There are a lot of RE technologies, but just three promising technologies are selected because a lot of opportunities for solar Energy and good wind speed more than 5 meters/sec. in MENA region. Each technology consist of 4 Indicators as shown in figure 12.

Figure 12 Technology Specific Indices Construction

3.4.1. Installed base

3.4.1.1. Technology installed capacity Indicator

By measuring the current installed base for each technology, the size of the technology in the countries under study will be estimated.

For scoring process as shown in table 34, the current installed capacity for each technology has been recorded.

44

Table 34: current installed capacity scoring Process for diff. Technology Indices

Due to the high difference between scores, the min. value (0) and maximum value (550) for wind installed capacity for Egypt, the condition (skewness>2 AND kurtosis > 3.5) has been achieved so to evade from this condition we have to minimize this high score till we evade from this condition to solve this problematic Indicator. So the new score to evade from this condition is (520).

Country Wind

installed capacity

Wind installed capacity

score

CSP installed capacity

CSP installed capacity

score

PV installed capacity

PV installed capacity

Score

Algeria 0.7 0.001 25 1 0 0

Bahrain 0 0 0 0 0 0

Egypt 550 (520) 1 20 0.8 15 0.6

Iraq 0 0 0 0 0 0

Jordan 1.445 0.003 0 0 1.6 0.064

Lebanon 0.5 0.001 0 0 0.5 0.02

Libya 0 0 0 0 4 0.16

Morocco 290.9 0.529 14 0.56 20 0.8

Palestine 0 0 0 0 1 0.04

Syria 0.15 0.0003 0 0 0.5 0.02

Sudan 0 0 0 0 2 0.08

Tunisia 245 0.445 0 0 3 0.12

Yemen 0 0 0 0 25 1

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3.4.2. National Target

3.4.2.1. Technology yearly Target size Indicator

By issuing a target for each technology, it reflects how much the country is interested in this technology after estimating their potential and for which stage this technology fits the country.

Most targets are for shares of electricity production, primary energy, and/or final energy for a future year.

For measuring this indicator it has been assumed that the country will achieve equal MW from the target every year till the announced target year.

Installed capacities for RCREEE M.S. have been used with a simple formula to know the size of installed Target per year with an important assumption that the government should achieve the target by announced year otherwise it could be understood as it measures the lazy of the country if the countries didn’t achieve the target size in one year.

The Initial year will be used as a current year.

Technology target for scoring process is shown in the table 35 after using the following simple formula

Expected annual technology target MW Capacity =

(Announced Target MW- current Installed Capacity in MW) / (Target Year-Initial year)

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Table 35: Yearly Target size scoring Process for diff. Technology Indices

Due to the high difference between scores, the min. value (0) and maximum value (950) for Egypt Wind yearly target size, the condition (skewness>2 AND kurtosis > 3.5) has been achieved so to evade from this condition we have to minimize this high score till we evade from this condition to solve this problematic Indicator. So the new score to evade from this condition is (440). These yearly target sizes according to each technology target announced for specified year as shown in table 36.

Country Wind yearly

Target size

Wind yearly

Target size score

CSP yearly Target size

CSP yearly Target

size score

PV yearly Target size

PV yearly Target size

Score

Algeria 102.9 0.108 422.059 1 164.706 1

Bahrain 0 0 0 0 0 0

Egypt 950 (440) 1 198.571 0.471 48.929 0.297

Iraq 26.6 0.028 26.6 0.063 80 0.485

Jordan 171.222 0.180 42.857 0.102 42.629 0.259

Lebanon 57.071 0.060 0 0 0.013 8.67E-05

Libya 85.714 0.090 21.429 0.051 42.286 0.257

Morocco 244.157 0.257 283.714 0.672 0.009 6.03E-05

Palestine 6.286 0.007 2.857 0.007 6.286 0.038

Syria 117.638 0.124 2.941 0.007 102.912 0.625

Sudan 17.778 0.019 2.778 0.007 13.778 0.084

Tunisia 73.824 0.078 17.647 0.042 111.589 0.678

Yemen 33.333 0.035 8.333 0.020 11.917 0.072

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Table 36: Target announced for different technology in MW

3.4.2.2. Detailed action plan Indicator (planned projects)

To assure that the country is working to achieve the announced technology targets, projects as a MW planned have been recorded and aggregated.

Detailed action plan scoring process is illustrated in table 37, future technology projects announced in MW will be taken.

Country Wind Target (MW) CSP Target (MW) PV Target (MW)

Algeria 1750 at 2030 7200 at 2030 2800 at 2030

Bahrain 0 0 0

Egypt 7200 at 2020 2800 at 2027 700 at 2027

Iraq 80 at 2016 80at 2016 240 at 2016

Jordan 2200 at 2020 300 at 2020 300 at 2020

Lebanon 400 at 2020 1000 street lighting panels

Libya 600 at 2020 150 at 2020 300 at 2020

Morocco 2000 at 2020 2000 at 2020

Palestine 44 at 2020 20 at 2020 45 at 2020

Syria 2000 at 2030 50 at 2030 1750 at 2030

Sudan 320 at 2031 50 at 2031 250 at 2031

Tunisia 1500 at 2030 300 at 2030 1900 at 2030

Yemen 400 at 2025 100 at 2025 168 at 2025

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Table 37: Detailed action plan (planned Projects) scoring Process for diff. Technology

Due to the high difference between scores, the min. value (0) and maximum value (2200) for Algeria PV planned Projects, the condition (skewness>2 AND kurtosis > 3.5) have been achieved so to evade from this condition we have to minimize this high score till we evade from this condition to solve this problematic Indicator. So the new score to evade from this condition is (830).

Country

Wind

Planned Projects (MW)

Wind Planned Projects

score

CSP Planned Projects (MW)

CSP Planned Projects

score

PV

Planned Projects (MW)

PV

Planned Projects

Score

Algeria 50 0.020 370 1 2200 (830) 1

Bahrain 0 0 0 0 5 0.002

Egypt 2510 1 200 0.470 40 0.018

Iraq 0 0 0 0.063 0 0

Jordan 1385 0.552 575 0.106 695 0.316

Lebanon 0 0 5 0 0.1 4.55E-05

Libya 260 0.104 0 0.051 84 0.038

Morocco 1820 0.725 2000 0.672 20 0.009

Palestine 0.1 3.9E-05 10 0.007 5 0.002

Syria 50.6 0.020 0 0.007 1 0.001

Sudan 300 0.120 0 0.007 20 0.009

Tunisia 160 0.064 2125 0.042 37 0.017

Yemen 121 0.048 0 0.020 5.48 0.002

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3.4.3. Resource potential

3.4.3.1. Resource Quality assessment (map, Atlas)

It is important to differentiate between 3 categories:

1- Theoretical potential (Wind map which is useful for prefeasibility study (Satellite data)

Advantages: spatial resolution, long term data (more than 20 years), effectively no failures, no soiling, no ground site necessary, low costs

Disadvantages: lower time resolution, low accuracy at high time resolution

2- Atlas for specific areas as wind atlas for Gulf Suez (Ground measurements)

Advantages: high accuracy (depending on sensors), high time resolution

Disadvantages: high costs for installation and O&M, soiling of the sensors, sometimes sensor failure, no possibility to gain the data of the past. [22]

3- Detailed technology atlas for whole the country (Wind atlas for Egypt 2005)

Due to there is no trustable data confirms Atlases and Maps existence for some Countries, this indicator will be excluded from the Index.

3.4.3.2. Resource potential Indicator in TWh/Year

RE technology potential in TWh/year for specified area or country is to measure the amount of electricity that could be generated annually and it is important to differentiate between technical potential and Economic potential

Technical Potential: is to measure the potential in TWh for identified areas which are suitable for applying specific RE technology.

Economic Potential: her they select the competitive cost areas and high resources, like excluding the areas which are a way from the grid or which have a terrain slopes. [23]

Resource potential in TWh/year scoring process: data for Economic potential for each technology (Wind, CSP, PV) from MED-CSP study which done by DLR at 2005. [24]

Assumption:

Because of MED-CSP study didn’t include Palestine and Sudan:

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- By assuming that Palestine takes the same score with the lowest neighbored country score which is Lebanon because the solar and wind characteristics almost the same.

- By assuming that Sudan takes the same score with its neighbor country Egypt for CSP potential and PV Potential, but for Wind potential because Sudan in the south of Egypt, in addition that the high wind speed in Egypt than Sudan, so Sudan will take half of the score of Egypt for Wind economic Potential.

Economic potential Indicator in TWh/Year scoring process is illustrated in table 38

Table 38: Resource potential Indicator in TWh/Year scoring process

Due to the high difference between scores, the min. value (0) and maximum value (90) for Egypt, the condition (skewness>2 AND kurtosis > 3.5) has been achieved so to

Country

Wind Resource

potential in TWh/Year

Wind Resource potential

score

CSP Resource

potential in TWh/Year

CSP Resource potential

score

PV Resource

potential in TWh/Year

PV Resource potential

score

Algeria 35 0.388 168972 1 13.9 0.381

Bahrain 0.1 0 33 0.0001 0.3 0

Egypt 90 (87) 1 73656 0.436 36 1

Iraq 10 0.110 28647 0.170 6.8 0.182

Jordan 2 0.021 6429 0.040 4.5 0.118

Lebanon 0.2 0.001 14 0 1.5 0.034

Libya 15 0.166 139477 0.825 3.9 0.101

Morocco 25 0.277 20146 0.119 17 0.468

Palestine 0.2 0.001 14 0 1.5 0.034

Syria 12 0.132 10210 0.060 8.5 0.230

Sudan 45 1 73656 0.436 36 1

Tunisia 8 0.088 9244 0.055 5 0.132

Yemen 3 0.032 5100 0.030 25.8 0.71

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evade from this condition we have to minimize this high score till we evade from this condition to solve this problematic Indicator. So the new score to evade from this condition is (87).

3.5. Conclusion

A composite RE Index has been constructed for Thirteen Arabian Countries depending on the barriers of RE development.

Theoretical framework has been developed and divided into 2 main aspects equally weighted (general Index 50% (4/8), Technology Indices 50% (4/8)

First aspect is the General Index which measures 4 equally weighted sub Indices and they are:

1- Market Structure (include 7 equally weighted Indicators) 2- Policy Framework (Include 6 equally weighted Indicators) 3- Institutional Capacity (it include 3 indicators, one of them is double weight of

the others which is ‘RE Agencies’ because of excluding forth related indicator due to lack of data and moving its weight to RE Agencies Indicator.

4- Finance & Investment (It include 4 equally Indicators)

Second aspect measures the Technologies development and potential of three promising RE technologies( each technology include 4 equally Indicators) with different technologies weight (Wind= 47.6%, CSP= 32.8%, PV= 19.6%) according to the percentage size of each technology by aggregating the current and future planned Projects in these Arabian countries.

Collection data has been done in Regional Center for RE and EE based on a prepared general questionnaire for the Regional Center focal point in each country in addition to including some other sources for verifying the data and to fill the missing data in their answers and get some other data which wasn’t covered in the questionnaire.

Using a simple formula to normalize the Indicators values, and to get the arithmetic average in the Excel Program for each country Indicators to generate the result of the Composite Index.

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Chapter 4 The Results and Robustness analysis

4.1. Introduction

As it has seen in chapter 3 the whole procedures for constructing the proposed composite Index from selecting Indicators, data imputations, scoring process and mathematically procedures in the Annex, now this is the time to announce the result of the Composite RE Index for MENA region, result of the General Index and the results of the selected technology Indices (Wind, CSP, PV)

4.2. Composite RE Index Results

The following Table no. 39 illustrates the Final Composite RE Index Ranking, and Figure 13 illustrates the Final Composite RE Index scores.

The results for the General Index, Wind Index, CSP Index and PV Index are illustrated in tables (40, 41, 42, and 43).

It doesn’t mean that the countries whose take high ranks have a perfect situation but this is just because 13 Arabian countries are included so it reflects the situation of the country among RCREEE Countries.

For Example Egypt took Rank number 1 with score (5.598 out of 8) so it means that Egypt still has a gap and need to do more to improve its score.

Figure 13 Final Composite RE Index Scores

0

1

2

3

4

5

6 Ranking Scores

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Table 39: Composite RE Index Ranks and Scores

Table 40: General Index Ranking Results

Scores out of 4 Countries Ranks

3.162 Jordan 1

2.804 Morocco 2

2.734 Egypt 3

2.502 Tunisia 4

2.258 Algeria 5

2.241 Palestine 6

1.413 Syria 7

1.357 Lebanon 8

1.110 Sudan 9

0.687 Bahrain 10

0.584 Yemen 11

0.531 Iraq 12

0.450 Libya 13

Table 41: Wind Index Ranking Results

Scores out of 1.893 Countries Ranks

1.893 Egypt 1

1.006 Morocco 2

0.457 Jordan 3

0.375 Tunisia 4

0.320 Sudan 5

0.311 Algeria 6

0.222 Libya 7

0.201 Syria 8

0.083 Iraq 9

0.074 Yemen 10

0.062 Lebanon 11

0.007 Palestine 12

- Bahrain 13

Scores out of 8 Countries Ranks

5.598 Egypt 1

4.816 Morocco 2

4.076 Algeria 3

4.003 Jordan 4

3.428 Tunisia 5

2.275 Palestine 6

1.808 Sudan 7

1.807 Syria 8

1.431 Lebanon 9

1.081 Libya 10

1.026 Yemen 11

0.821 Iraq 12

0.688 Bahrain 13

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Table 42: CSP Index Ranking Results

Scores out of 1.3 Countries Ranks

1.042 Algeria 1

0.753 Morocco 2

0.591 Egypt 3

0.360 Tunisia 4

0.288 Libya 5

0.145 Sudan 6

0.135 Jordan 7

0.076 Iraq 8

0.022 Syria 9

0.016 Yemen 10

0.004 Palestine 11

0.001 Lebanon 12

0.000 Bahrain 13

Table 43: PV Index Rankin Results

Scores out of 0.78 Countries Ranks

0.466 Algeria 1

0.381 Egypt 2

0.351 Yemen 3

0.253 Morocco 4

0.250 Jordan 5

0.232 Sudan 6

0.191 Tunisia 7

0.171 Syria 8

0.131 Iraq 9

0.121 Libya 10

0.023 Palestine 11

0.011 Lebanon 12

0.001 Bahrain 13

Now with the end with the results of the Composite RE Index, Robustness should be assessed to check the strength of the composite RE Index.

4.3. Robustness Analysis for Composite RE Index

Robustness analysis is important to assure the accuracy of the final result and to improve it.

In order to be able to derive robustness and to check if the composite RE Index provide a real picture for the Countries under the study, it has been decided to do three types of analysis.

1. Correlation analysis 2. Indicators Sensitivity Analysis 3. Expert Survey Analysis

4.3.1. Correlation analysis

By doing correlation, relationship between Indicators will be measured, and the idea from correlation is to check is there a double counting if the high correlation found between two indicators, but on the other hand Correlation sometimes don’t reflect the real relationship between two indicators if they measuring different phenomena or there is a reasonable cause.

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Correlation Coefficient is a numerical data for two variables with interval [-1 to 1]

(1) means perfect positive correlation and it happens between the indicator and itself.

(0) means there is no correlation between these two indicators. (-1) means perfect negative correlation and it happens between the indicator and itself but one in increasing way and the other in decreasing way. (From 0 to 1) positive Correlation If the two variables are increasing in the same direction and it is the issue in this proposed work.

Now, by using the Excel correlation function to measure the correlation coefficient, highly correlated Indicators have been chosen and it illustrated in the table 44.

Table 44: the correlation coefficient between highly correlated Indicators

First Indicator name Second Indicator name Correlation Coefficient

IPP Auto Producer 0.81 PPA Interconnection Capacity 0.76 PPA Grid code 0.81

Priority dispatch FIT 0.85

Priority dispatch Detailed PV planned Projects

(MW) 0.73

Ease of doing Business CPI Index 81 RE Agencies PPA 0.86 RE Agencies RE target with a map 0.78 RE Agencies CSP installed capacity 0.79 RE Agencies CSP yearly target size 0.79

CSP yearly target size CSP installed capacity 0.95 Wind installed capacity Wind yearly target size 0.85

Wind installed capacity Detailed wind planned Projects

(MW) 0.81

Wind yearly target size Detailed wind planned Projects

(MW) 0.93

Practical rule: Highly correlation between Two Indicator > 0.92 in the same dimension, need to be treat by removing one of them. [24]

- IPP and Auto Producer (0.81) there is a positive correlation between them

because they are common in private generation but the difference is that IPP to generate electricity to sell it to the Utility and the latter to generate electricity for his own use.

- PPA and Interconnection capacity (0.76) (measuring different phenomena)

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- PPA and Grid code (0.81) (measuring different phenomena but, they must be positively correlated because when number of PPA increase the grid code must be issued to guarantee the network security.

- Priority dispatch and FIT (0.85) they have different procedure, normally FIT for

small RE generation, and Priority dispatch for general RE generation, they have been issued as a different Laws in the countries.

- Priority dispatch and Detailed PV planned Projects (MW)(0.73) (measuring

different phenomena)

- Ease of doing Business and CPI Index (0.81) (measuring different phenomena) but they are correlated because there is a positive relationship between the corruption and the difficulty of doing business in the same country.

- RE Agencies and PPA (0.86) they are positively correlated because if the country has a RE Agency, the purpose of this agency will be a RE promotion and that is happen by encourage investors to make a RE projects and to guarantee of buying all their generation and that is happen by PPA.

- RE Agencies and RE target with a map (0.78) they are positively correlated

because if there is a RE Agency exist in the country, it will work for promotion RE sector by issuing a target and may be a map for how to achieve it but not a must like in Libya they have a RE Agency but they don’t have a map illustrating how to achieve it.

- RE Agencies and (CSP Installed capacity, CSP yearly target size) (0.79)

(measuring different phenomena) because it is not a must that with the existence of RE Agency in the country to has in the same time CSP installed capacity or high potential for this specific technology like Palestine, Lebanon and Libya. If this is a real correlation it should appear in different technologies like Wind and PV but it didn’t happen.

- Wind Installed Capacity and (Wind yearly Target size (0.85), Detailed wind

planned Projects (0.81)) There is a correlation between them because normally the country who started to invest in Wind technology and has a current Wind installed capacity; it will work to cover the rest of the competitive Wind areas by planning extra projects like (Egypt, Morocco and Tunisia), but on the other hand (Libya, Sudan and Yemen) they has a zero installed capacity and in the same time they have a wind competitive target and some planned projects.

- Wind Yearly Target size and Detailed wind planned Projects (0.93)

Normally it should has a highly correlation because if the country has a Wind target, the normal way to announce about the future projects but on the proposed composite Index (Iraq and Lebanon) they have a Wind Target but without any announced future projects.

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By applying the rule for these two Indicators and remove one of them, the result did not change.

- CSP yearly target size and CSP Installed capacity (0.95)

(Measuring different phenomena) and the witness is Tunisia and Jordan have 0 installed capacity and issued a reasonable target for CSP. This highly correlation happen because just 3 countries have a CSP installed capacity and the rest of countries have zero CSP Installed capacity that is why correlation is so high, and if 3 countries whose have CSP installed capacity have been taken, the correlation between them will be 57%. By applying the rule for these two Indicators and remove one of them, the result did not change.

By applying the rule for the 4 highly correlated Indicators together the result did not change.

By the end of correlation analysis it has found high correlation between some indicators, and by analyzing this correlation it was found that: It doesn’t reflect a strong influence between them because some of them are measuring different phenomena and the others didn’t exceed the highly correlation to exclude one of them. By applying the rule which say that it should remove one of correlated indicator if the correlation coefficient exceeds 0.92, and generate the Composite Index ranking again, the result was no change happened.

4.3.2. Indicators Sensitivity Analysis

Indicator sensitivity analysis used to measure the robustness of the Composite Index.

It will be done by changing the Input by exclusion of one indicator at a time (for all 32 Indicators) and regenerate the result of the Index to see how much are the sensitivity of this indicator and the effect of excluding this indicator to get a new ranking compared with the original Composite RE Index ranking.

The weight of the excluded Indicator will be distributed with the other indicators in the same sub index to make the weight of all sub-Indices the same as before.

Type of sensitivity Indicators are illustrated in table 45.

Note:

Regarding to the Countries whose have very close value from each other and they are:

- Sudan with score: 1.8083, Syria with score: 1.8076. - Algeria with score: 4.076, Jordan with score: 4.003. - Libya with score: 1.081 , Yemen with score: 1.026

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According to the low difference between these countries, any simple change in almost Indicators in the Index will affect on their ranking, so the changes with these countries will not be considered.

The result of Indicators Sensitivity analysis will be divided into two categories:

Table 45: Sensitivity Indicators which affect the Composite RE Index Ranking result

High sensitivity Indicator Low sensitivity Indicator RE Agencies Indicator: Bahrain exceeds Yemen, Libya

and Iraq.

RE fund:

Bahrain exceeds Iraq

4.3.2.1. High sensitivity Indicators

It includes the Indicators whose cause more than 2 changes in countries ranking due to excluding it and just one Indicator found which is:

- RE Agencies Indicator (3 changes)

- Bahrain exceeds Libya, Yemen and Iraq.

Bahrain exceeds Libya because Libya has RE Agency and by excluding this indicator especially with its high weight for this Indicator among the others, Libya lost this high weight which depends on, in addition to Bahrain has the highest scores in ease of doing business and CPI which added more weight to its score and pulled Bahrain to be number 10 in ranking instead of number 13.

Bahrain exceeds Yemen and Iraq, they have the same score in this indicator but Bahrain has the highest scores in ease of doing business and CPI which added more weight to its score.

4.3.2.2. Low sensitivity Indicators

It includes the Indicators whose cause one change in countries ranking due to excluding it and just one Indicator found which is:

- RE fund (Bahrain exceeds Iraq)

The scores in this indicator are (0 or 1) Iraq has the high score and Bahrain has the low score in this indicator. By removing this indicator Iraq lost the score of this indicator. In spite of both of them are equal in all indicators in this sub index (Finance &Inverstment), Bahrain became more competitive by aggregation the rest of indicators.

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So we can see the effectiveness of the Indicator who include just 2 scores 0 or 1.

By the end of Indicator Sensitivity analysis it has found that the highly sensitive Indicator is RE Agencies and that is because it has highest weight in the Index and that is because the lack of collecting information about another Indicator in Institutional Capacity Sub Index which was number of policies formulated in the countries so the score of the absent indicator moved to RE Agencies Indicator.

4.3.3. Experts survey analysis

A prepared survey has been done (Appendix E) and sent to 5 regional Experts in MENA region, but unfortunately we have received one reply and by comparing the result of the Expert and the result of Composite RE Index, it has found highly correlation between two results as it illustrated in the figure 14 and table 46 with a correlation coefficient = 87%.

Table 46: Correlation between Composite RE Index and Expert survey Results

Countries Composite Index

Rank

Expert

evaluation

Egypt 1 2

Morocco 2 1

Algeria 3 4

Jordan 4 7

Tunisia 5 3

Palestine 6 6

Sudan 7 10

Syria 8 9

Lebanon 9 5

Libya 10 8

Yemen 11 11

Iraq 12 12

Bahrain 13 13

Correlation coefficient 0.873626374

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Figure 14: Correlation between Composite RE Index and Expert survey Results

Table 47: Correlation between the results of Technology Indices and Expert evaluation

Wind Index Expert

evaluation CSP Index

Expert

evaluation PV Index

Expert evaluation

Egypt 1 1 Algeria 1 1 Egypt 1 2

Morocco 2 2 Morocco 2 2 Morocco 2 1

Tunisia 3 3 Egypt 3 3 Tunisia 3 3

Wind Corr. Coef. 1 CSP Corr. Coef. 1 PV Corr. Coef. 0.5

It has been found that there is perfect correlation between the results in Wind Index and PV Index for the available ranks and just 50% correlation on the PV Index illustrated in table 47.

4.3.4. Ernst & Young Comparison

By comparing the results of the proposed Indices with Ernst & Young, taking into account that E&Y just include 3 countries.

0

2

4

6

8

10

12

14

0 2 4 6 8 10 12 14

Composite Index Ranks

Expert Ranks

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Table 48: Correlation between E&Y all renewables Index and Composite RE Index

Composite RE Index

E &Y All Renewables

Index

Egypt 1 2

Morocco 2 1

Tunisia 3 3

General Corr. Coef. 0.5

Table 49: Correlation between E&Y renewable Indices and Composite RE Index

At the End of the Expert survey which was so valuable and illustrated strongly correlation between the composite Index result 87%, for Wind Index 100% for CSP Index 100%, but for PV Index 50%.

Generally it is worth to mention that the result which include just 3 countries is has no good accuracy because the absence of almost countries.

At the end of the comparison between Ernst & Young and the proposed Indices, it was found that 50% correlation in the Composite Index, 50% correlation for the General Index, 100% correlation for the Wind Index, 50% correlation for CSP Index, and – 50% correlation for PV Index as shown in tables 48 and table 49.

But generally as it has said before due to the absence of almost of the countries we will not take it in consideration.

General Index E &Y

Infrastructure Index

Wind Index

E &Y Wind Index

CSP Index

E&Y CSP Index

PV Index

E&Y PV

Index

Morocco 1 1 Egypt 1 1 Morocco 1 1 Egypt 1 3

Egypt 2 3 Morocco 2 2 Egypt 2 3 Morocco 2 1

Tunisia 3 2 Tunisia 3 3 Tunisia 3 2 Tunisia 3 2

General Corr.

Coef. 0.5

Wind Corr.

Coef. 1 CSP Corr. Coef. 0.5

PV Corr.

Coef. -0.5

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- Countries have been divided into two groups according to the result of the Composite Index:

1- Transition phase countries:

They are the countries whose took a further step towards RE promotion as a large scale development according to the Composite RE Index result and they are:

Egypt, Morocco, Algeria, Jordan, Tunisia

2- Pre transition phase countries:

They are the countries which need extra efforts to promote RE and they are:

Palestine, Sudan, Syria, Lebanon, Libya, Yemen, Iraq, Bahrain

4.4. Highlighting the Weak areas for future Improvement

In the following tables 50, 51 ,52 and 53, it has illustrated that the countries whose take a low scores out of 1, Weak areas are clearly displayed from this low scores, so it will be easy to see the areas which need improvement in the future for each Country.

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Table 50: Market Structure sub general Index scores and Ranks

scores out of 1 Countries Ranks

0.810 Morocco 1

0.751 Algeria 2

0.707 Jordan 3

0.622 Egypt 4

0.573 Palestine 5

0.529 Syria 6

0.510 Tunisia 7

0.224 Lebanon 8

0.187 Bahrain 9

0.125 Libya 10

0.119 Sudan 11

0.119 Iraq 11

0.119 Yemen 11

Table 51: Policy Framework sub general Index scores and Ranks

Scores out of 1 Countries Ranks

0.834 Palestine 1

0.771 Jordan 2

0.566 Morocco 3

0.501 Lebanon 4

0.493 Syria 5

0.479 Algeria 6

0.473 Egypt 7

0.464 Tunisia 8

0.424 Sudan 9

0.295 Yemen 10

0.129 Iraq 11

0.093 Libya 12

- Bahrain 13

Table 52: Institutional Capacity sub General Index scores and Ranks

Scores out of 1 Countries Ranks

0.796 Morocco 1

0.739 Egypt 2

0.684 Jordan 3

0.665 Algeria 4

0.585 Tunisia 5

0.500 Bahrain 6

0.380 Lebanon 7

0.333 Palestine 8

0.219 Libya 9

0.161 Yemen 10

0.128 Syria 11

0.045 Sudan 12

0.033 Iraq 13

Table 53: Finance &Investment sub general Index scores and Ranks

Scores out of 1 Countries Ranks

1.000 Jordan 1

0.943 Tunisia 2

0.899 Egypt 3

0.632 Morocco 4

0.522 Sudan 5

0.502 Palestine 6

0.362 Algeria 7

0.263 Syria 8

0.252 Lebanon 9

0.250 Iraq 10

0.012 Libya 11

0.009 Yemen 12

- Bahrain 13

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4.5. Conclusion

The results of (Composite Index, General Index, Wind Index, CSP Index and PV Index) have been seen and then the robustness for the Composite Index result will be checked with different ways, and it has been found that:

1- Correlation Analysis:

It has found high correlation between some indicators, and by analyzing this correlation it was found that: It doesn’t reflect a strong influence between them because some of them are measuring different phenomena and the others didn’t exceed the highly correlation to exclude one of them.

- CSP yearly target size and CSP Installed capacity (correlation coefficient=0.95) By analyzing this correlation it has found that there is no real strong influence between them because there are just 3 countries who have CSP installed capacity and if correlation just done with these 3 Indicators because they have real numbers not zeros, the correlation will be 57%.

- Wind Yearly Target size and Detailed wind planned Projects (Correlation coefficient=0.93)

By applying the rule which say that it should remove one of correlated indicator if the correlation coefficient exceeds 0.92 for the Indicators which comply with this rule which are:

The result of the Composite RE Index was no change happened. 2- Indicator sensitivity analysis: - It has found that high sensitivity for RE Agencies Indicator due to the highest

weight for this Indicator in the composite Index, and this high weight was because the lack of collecting information for another Indicator in Institutional Capacity so the score of the absent indicator moved to RE Agencies Indicator.

- The effectiveness of the Indicator who include just 2 scores 0 or 1.

- Regarding to the Countries whose have very close value from each other and they are:

- Sudan with score: 1.8083, Syria with score: 1.8076. - Algeria with score: 4.076, Jordan with score: 4.003. - Libya with score: 1.081 , Yemen with score: 1.026

According to the low difference between these countries, any simple change in almost Indicators in the Index will affect on their ranking, so the changes with these countries will not be considered.

3- Expert Survey

After checking the Robustness of the Composite Index by asking the Experts to give a real rank for the countries from their experience in the Region, and it ended with highly

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positive correlation for Composite Index 87% which illustrate the strength of the Composite Index Results.

4- By comparing the results with Ernst & Young

It has found that there is moderate Positive correlation 50% between E&Y all Renewables Index and Composite RE Index, but generally because E&Y include just 3 countries, so with these small samples the reality of comparison will not be achieved. Generally Robustness analysis is not enough to guarantee the strength of the Composite Index for measuring the real phenomena without establishment a good Theoretical framework by participation of regional Experts.

It doesn’t mean that the countries which take high ranks have a perfect situation but this is just because 13 Arabian countries are included so it just reflects the situation of the country among RCREEE Countries.

According to the result of the Composite Index, Countries have been divided into two groups:

- Transition phase countries:

They are the countries whose took a further step towards RE promotion as a large scale development and they are:

(Egypt, Morocco, Algeria, Jordan, Tunisia)

- Pre transition phase countries:

They are the countries which need extra efforts to promote RE sector and they are:

(Palestine, Sudan, Syria, Lebanon, Libya, Yemen, Iraq, Bahrain)

Weak areas are clearly displayed from the low scores in sub Indices tables (Market, Policy, Institutional, Finance and Investment), so it will be easy to see the areas which need improvement in the future for each Country.

66

Chapter 5 Conclusions and Future work

5.1. Conclusion

By reviewing previous Indices frameworks, it was found that:

Ernst&Young Renewables Index depends more on Expert analysis and deep investigation for each country as a separate case study from experienced teams so it has no clear scoring process.

RE Market Competence Index measure the motivation which make the country go forward to RE and it was so valuable for the countries to see how they should plan for the future regarding to Energy.

So, it was important to construct a transparent Index which measure the actual situation of RE.

A composite RE Index has been constructed for Thirteen Arabian Countries in MENA Region depending on the barriers of RE development.

Theoretical framework has been developed and divided into 2 main aspects equally weighted (general Index 50% (4/8), Technology Indices 50% (4/8)

First aspect is the General Index which measures 4 equally weighted sub Indices and they are:

1- Market Structure (include 7 equally weighted Indicators) 2- Policy Framework (Include 6 equally weighted Indicators) 3- Institutional Capacity (it include 3 indicators, one of them is double weight of

the others which is ‘RE Agencies’ because of excluding forth related indicator due to lack of data.

4- Finance & Investment (It include 4 equally Indicators)

Second aspect measures the Technologies development and potential of three promising RE technologies( each technology include 4 equally Indicators) with different technologies weight (Wind= 47.6%, CSP= 32.8%, PV= 19.6%) according to the percentage size of each technology by aggregating the current and future planned Projects in these Arabian countries.

Collection data has been done in Regional Center for RE and EE based on a prepared general questionnaire for the Regional Center focal point in each country in addition to including some other sources for verifying the data and to fill the missing data in their answers and get some other data which wasn’t covered in the questionnaire.

67

Using simple formula to normalize the Indicators values and to get the arithmetic average in the Excel Program for each country Indicators to generate the result of the Composite Index.

After getting the result of Composite Index, General Index, Wind Index, CSP Index and PV Index, robustness for the Composite Index result will be checked with different ways, and it has been found that:

1- Correlation Analysis:

It has found high correlation between some indicators, and by analyzing this correlation it was found that: It doesn’t reflect a strong influence between them because some of them are measuring different phenomena and the others didn’t exceed the highly correlation to exclude one of them. By applying the rule which say that it should remove one of correlated indicator if the correlation coefficient exceeds 0.92 for the Indicators which comply with this rule which are:

- CSP yearly target size and CSP Installed capacity (correlation coefficient=0.95) - Wind Yearly Target size and Detailed wind planned Projects (Correlation coefficient=0.93) The result of the Composite RE Index was no change happened.

2- Indicator sensitivity analysis: Which ended with highly sensitivity for RE Agencies Indicator due to the highest weight for this Indicator, and this high weight was because the lack of collecting information for another Indicator in Institutional Capacity so the score of the absent indicator moved to RE Agencies Indicator.

Regarding to the Countries whose have very close value from each other and they are:

- Sudan with score: 1.8083, Syria with score: 1.8076. - Algeria with score: 4.076, Jordan with score: 4.003. - Libya with score: 1.081 , Yemen with score: 1.026

According to the low difference between these countries, any simple change in almost Indicators in the Index will affect on their ranking, so the changes with these countries will not be considered.

3- Expert Survey:

After checking the Robustness of the Composite Index by asking the Experts to give a real rank for the countries from their experience in the Region, and it ended with highly positive correlation for Composite Index 87% which illustrate the strength of the Composite Index Results.

4- Ernst & Young Comparison

68

It has found that there is a moderate Positive correlation 50% between E&Y all Renewables Index and Composite RE Index, but generally because E&Y include just 3 countries, so with these small samples the reality of comparison will not be achieved. Generally Robustness analysis is not enough to guarantee the strength of the Composite Index for measuring the real phenomena without establishment a good Theoretical framework by participation of regional Experts.

It doesn’t mean that the countries which take high ranks have a perfect situation but this is just because 13 Arabian countries are included so it just reflects the situation of the country among RCREEE Countries.

- According to the result of the Composite Index, Countries have been divided into two groups:

- Transition phase countries:

They are the countries who took a further step towards RE promotion as a large scale development and they are:

(Egypt, Morocco, Algeria, Jordan, Tunisia)

- Pre transition phase countries:

They are the countries which need extra efforts to promote RE sector and they are:

(Palestine, Sudan, Syria, Lebanon, Libya, Yemen, Iraq, Bahrain)

Weak areas are clearly displayed from the low scores in sub Indices tables (Market, Policy, Institutional, Finance and Investment), so it will be easy to see the areas which need improvement in the future for each Country.

69

5.2. Future Work

1- Include additional Indicators like (resource quality assessment with technologies maps and atlases, Grid parity map for each technology…)

2- Investigate the week areas according to the Index result and provide

improvement suggestions for each country as a separate case.

3- Widen the area of the composite Index by dragging other countries.

4- Using different weighting and scoring schemes.

70

Appendix A

General Index Components in the current three RE Indices framework:

E & Y Index Brit Samborsky

Framework

Market competence

Index Renewable infrastructure index 35%

General Indicators

13 General indicators

Electricity market regulatory and political risk (29%) Potential risks inherent in generating RE; e.g. what type of electricity market exists; is it fully deregulated, stable, and reliable? Who manages the electricity market in the country? Political Risk How strong is the government’s commitment to developing the local renewable energy industry? What role has Government played so far in promoting and developing the industry? Are there any delays from the government’s side that are stalling the market? What legislation is in place to govern the country’s RE industry? Planning Environment and grid connection issues (42%) Is it necessary to obtain planning permission for new renewable projects? Who does the planning permission need to be obtained from? What are the costs involved in obtaining planning permission? What documentation needs to be submitted? Is there any legislation governing the granting of planning permission? How long does it take to obtain planning permission for renewable energy projects? Is an Environmental Impact Assessment

Market: Separation of generation, transmission, Distribution (IPP) option or not Dispatch priority for renewable or not Competitive bids and offers on electricity or prices set by government (PPA) availability Policy: National RE target, RE Policy, RE Agency indicate strategy for development of RE Member of regional collaboration on RE indicates coordinated approach with RCREEE member states Proxy for subsidy amount - implied subsidy vs Palestine price (residential, industrial) Institutional / Planning: Target value Country score from World Bank index Country score from Bertelsmann status index Country score from

Political and Economic Indicator (3 indicators). Global competitive Index Political Instability Index Corruption Perception Index.

Energy Sector Indicator (8 indicators). • Energy Intensity Indicator • Non Electricity Final Indicator • Electricity Consumption Growth Indicator • Net Imported Electricity Indicator • Non-RE Electricity Production Indicator • Oil Insecurity Indicator • Gas Insecurity

71

(EIA) necessary? If so, for which technologies? How long does it take to conduct an EIA for the different technologies? Grid Connection Issues What is the coverage of suitable grid infrastructure? Does existing technology allow for effective connection of renewable energy projects to the national grid? Are there incentives for grid providers? Who carries the cost for connection to the grid? Does renewable energy have “priority dispatch”? How long does it take to be connected to the grid? Are there any restrictions / minimum requirements placed on renewable energy projects that apply for connection to the national grid? Access to Finance (29%) Who are the main providers of finance for renewable energy projects in the country? Is finance equally available for all technologies? If not, which technologies are favored by financiers? Are there easy and / or cheap financing opportunities from local / international banks? How mature is the renewable energy financing market?

Bertelsmann management index Investment / Finance: Average interest on new external debt commitments Foreign direct investment (FDI in relation to annual RE kWh generate FDI per new MW installed? Private funds invested in RE or support (% of new MW installed)

Indicator • RE Target Indicator

Financial and Environmental Indicators (2 indicators).

Financial Indicator Regulatory Policies Fiscal Incentives Public Financing

Environmental Indicator

72

Appendix B

Technology specific Indicators in the current three RE Indices framework:

E & Y Index Brit Index Market

competence Index

Technology Factors 65%

7 Technology-specific indices for

each renewable.

5 Technology specific

indicators CURRENT INSTALLED BASE What is the total current installed capacity (MW/GW and/or MWh/GWh)? Give figure as at end of previous calendar year, and any more recent updates if available. Enter figures in datebook if appropriate. RESOURCE QUALITY Details of the resource quality available for this specific technology POWER OFFTAKE Are there any power off take incentives /subsidies in place for this technology? Please give details of the price, longevity, and conditions associated with any support mechanism (e.g. feed-in tariff, green certificate, RPS mechanisms, etc.), and include in datebook where appropriate. TAX CLIMATE What tax breaks or tax-related incentives are in place for the specific technology? (e.g. accelerated depreciation, no import duties on RE components etc) GRANT / SOFT LOAN AVAILABILITY Please provide details of any grants, government backed loans or other financial support (e.g. low-interest loans) that is made available in respect of this technology. MARKET GROWTH POTENTIAL

What is the expected future capacity (per targets) or estimated maximum potential

Installed Base: Indicates commitment to developing the resource, as percentage of total base or usage Resource Quality: Published data on amount of resource per unit area Target: National RE target – indicates strategy for development of RE Power Off take: Low Delta FIT for country indicates more productive use of FIT funds (Delta FIT =(FIT offered / retail electricity price) Length of agreement for FIT IPP option or not

Manufacturability Indicator Economic Potential Indicator Institute Indicator Technology Target Indicator Feed-in Tariff Indicator

73

(in MW/GW or MWh/GWh if possible)? Provide details of any other indications / government targets, which indicate the future growth potential of the technology. What is the potential for large projects? Is there an established supply / manufacturing base for the specific technology? PROJECT SIZE What is the average project / facility size for this technology? If appropriate, give examples of operating and/or planned projects.

Taxation: Lower import duty, accelerated depreciation, investment tax credit Grants or soft loans: Yes or no - High is good for developer / Low is good for country ($ of funds per new MW installed) Investment: Private funds invested in RE or support (% of new MW installed)

74

Appendix C

RE Index questionnaire (prepared by RCREEE Experts)

Questions to RCREEE focal points on Renewable Energy Index

1. Market Structure 1.1. Independent Power Producer (IPP) (for all energy: renewable and non-

renewable)

Is there an authorization (permission) in law for (IPP)? Yes/No

If yes, please indicate the name and reference of the law

Are there any IPPs in practice? Yes/No

1.2. Power Purchase Agreement (PPA)(for renewable energy)

Is there an obligation in law for concluding PPA for renewable energy? Yes/No

Is there practice of concluding PPAs? Yes/No

Please list all PPAs and projects:

1.3. Auto-production (for all energy: renewable and non-renewable)

Please indicate whether it is permitted to produce electricity for own use and for sale to third parties? Yes/No

Please list all auto-producer projects:

1.4. Priority dispatch and access to the grid (for renewable energy)

Is there access and dispatch priority to the grid for RE? Yes/No

If yes, please indicate the name and reference of the policy

1.5. Grid Connection Rules (Grid Code)

Has the country developed grid connection rules for RE? Yes/No

Reference to the law/regulation

PV CSP Wind

75

1.6. Grid Interconnections

Existing electrical interconnections

Length Voltage (KV) Capacity Status

2. Policy Framework 2.1. RE Targets

Target

(%)

Target

base1

Target

in MW

Target

Date

Total RE

installed

capacity

MW

Total

Installed

Capacity

in MW

(all

energy)

Please indicate

document where

these targets are

expressed (for

example: action plan,

strategy, working plan

etc):

All RE

Wind

PV

CSP

Others

2.2. Competitive Bidding

Is there policy or practice of Competitive Bidding for RE? Yes/No

If yes, please list all announced tenders:

2.3. Feed-in-Tariff (only approved ones)

Details of FIT (price & capacity)

Duration of FIT Is FIT already implemented? Yes/No

Wind PV CSP

1 Please indicate how the target is expressed: for example in GWh generated or primary energy or

MW installed?

76

2.4. Net-Metering

Is there any provision in law for Net Metering? Yes/No

Indicate name and reference of the law

Provide the rules Net Metering

Is Net Metering implemented? Yes/No

2.5. Local Content Incentives

Please provide existing incentives for local content:

3. Institutional Capacity 3.1 RE Institutions

Function Responsible Institution

Please describe activities of the institution

Policy design and formulation

Promoting RE projects (seeking funds, establishing cooperation activities, coordination among various stakeholders such as investors, donors and network operators etc)

Facilitating deployment of RE projects (facilitating licensing procedures, environmental impact assessment, land allocation for RE, construction permit etc)

Research & development (studies, reports, resource quality assessment)

3.2. Please describe what kind of institutional support the country provides to RE projects:

77

4. Finance & Investment

4.1. Customs (import) duty

Has the country developed a list of eligible technology and spare parts for customs duty exemption or reduction? Yes/No

If yes, please specify key eligible technologies

Customs duty (%)

Please provide reference to the law

4.2. Internal taxes

Does the law specify tax relief to RE technologies and spare parts? Yes/No

If yes, describe tax relief and key eligible technologies

Please provide reference to the law

4.3. If tax relief is not stipulated by law, does the country still provide tax relief to RE technologies and spare parts? Yes/No

If yes, please describe the procedure for granting tax relief:

4.4. RE Fund

Is there a Renewable Energy Fund? Yes/No

Amount Declared

Yes 4.5. Please provide information on currently existing grants, subsidies and soft

loans for RE projects

Name of the incentive

Description of incentive (eligible technology, payback period, other conditions)

Total available amount in USD/EUR

Source of funding

Grants Subsidies Soft loans

78

4.6. Information on RE projects

Wind

Project Installed Capacity in MW

Project Status

Commissioning Date

Total investment

cost in million

USD/EUR

Amount already invested by Dec.

2012

Share of private

investment (% of total investment

costs)

Name of key privat

e invest

ors

Source of

funding

CSP & PV

Project Installed Capacity in

MW

Project Status

Commissioning

Date

Total investment cost

in million USD/E

UR

Amount already invested by Dec.

2012

Share of private

investment (% of

total investment costs)

Name of key

private investors

Source of

funding

79

Appendix D

Direct Grid interconnections

country length (km)

voltage (KV)

capacity (MW)

status Capacity of

Interconnection

Algeria

Tunisia 35.5 90 74 in operation

3238

60 90 63 in operation

65 150 14 in operation

60 225 217 in operation

160 400 961 under

construction

Morocco 49 225 235 in operation

67 225 235 in operation

230 400 2400 in operation

Bahrain Saudi Arabia

40 400 600 synchronized 600

Egypt

Jordan 13 400 550 in operation

807 Palestine 17

Libya 180 220 240 in operation

Iraq Syria 140 400 1000 under

construction no

Jordan

Egypt 13 400 550 in operation

1570 Syria 60 400 1000 in operation

Palestine 33 20 in operation

Lebanon Syria 22 400 1000 in operation

1000

Libya

Egypt 180 220 240 in operation

891

Tunisia 110 225 217 not in operation

110 225 217 not in operation

160 225 217 not in operation

330 400 961 planned for

2015

Morocco

Algeria 49 225 235 in operation

4270

67 225 235 in operation

230 400 2400 in operation

Spain 61 400 700 in operation

61 400 700 in operation

Palestine Jordan 33 20 in operation

37 Egypt 33 17 in operation

Syria Jordan 60 400 1000 in operation

3000 Lebanon 22 400 1000 in operation

80

Iraq 140 400 1000 under

construction

Turkey 61.6 400 1000 in operation

Sudan 0

Tunisia

Algeria 35.5 90 74 in operation

1019

60 90 63 in operation

65 150 14 in operation

60 225 217 in operation

160 400 961 under

construction

Libya 110 225 217

110 225 217

160 225 217

330 400 961 planned for

2015

Italy 200 400 1000 planned for

2016

Yemen 0

81

Appendix E

Regional Experts survey for RE Index in MENA Region

Using opinions of Regional Experts to check the strength of a newly developed RE Index results

Dear Sir

A new RE index methodology is being developed to measure the:

• The existing RE situation and opportunities of the RE markets in RCREEE Member States.

• Policies that governments are adopting to promote RE market and industry for the future.

• Effectiveness of relevant Institutions.

• Easiness of doing Investment for different RE technologies.

You are kindly requested to rank RCREEE countries for the following two tables according to your own experience, which will help us to check the quality of the proposed Renewable Energy Index results.

Note: You can neglect any country from the ranking if you don’t have enough data or information about it.

Country

General Ranking according to the previous criteria

Algeria

Bahrain

Egypt

Iraq

Jordan

Lebanon

Libya

Morocco

Palestine

Sudan

Syria

Tunis

Yemen

82

Ranking RCREEE Member states Countries according to each technology

Country Wind Photovoltaic CSP Algeria Bahrain Egypt Iraq Jordan Lebanon Libya Morocco Palestine Sudan Syria Tunis Yemen

The name of Renewable Energy Regional Expert: Institution: E-mail: Date:

83

Annex

The mathematical methodology for constructing the Composite Renewable Energy Index as follows [25]:

1- Filling collected raw data for the given 13 Countries covering 32 different Indicator.

2- Calculate descriptive statistics, such as missing values, min, max, skewness,

kurtosis for each indicator. Treat potentially problematic indicators (i.e. those with skewness >2 AND kurtosis > 3.5) If this condition achieved skewness >2 AND kurtosis >3.5 it means that we have one or more value with high score comparing to the other scores and we have to minimize this high score till we evade from this condition.

3- Normalizing indicators The Indicators used are expressed in different units so by normalizing all Indicators data to common scale from 0 to 1 is preferred. Most commonly used method is min-max. and to take into account the direction of the indicators (highest value is the Best and the lowest value is the bad (direction = 1) or vice versa (direction= -1). General formula: New value = (old value-min)/(max-min)*direction+0.5*(1-direction)

4- Aggregation Normalized data are aggregated using arithmetic averaging. Formula-unequal weights: score=sum product(weights*normalized values)

5- Estimating the final Rank using this formula: Rank (Arithmetic averaging of the country, range of arithmetic averaging of all countries) [25]

84

The weights are selected as 50% for General Index, 50% for 3 Technology Indices (8/8)

• General Index (weight = 4) • Market structure (weight = 1, equally weighted for its indicators) • Policy Frame work (weight = 1, equally weighted for its indicators) • Institutional Capacity (weight = 1, equally weighted for its indicators) • Finance & Investment (weight = 1, equally weighted for its indicators)

• Technology Indices (weight = 4)

For estimating a weight for each technology Index, I aggregated the installed Capacity with the announced MW future projects for each technology so see the size of this technology in the market with taking into account that all 3 technologies (Wind, CSP, PV) = 100% from the RE market and according to the following table I found that:

Wind technology size = 47.6%, CSP tech. size = 32.8%, PV tech. size = 19.6%

According to the weight of Technology Indices which equal 4, it has shown in table 54, the new weights for these technologies are:

• Technology Specific (Wind) (weight = 1.89265124, equally weighted for its indicators)

• Technology Specific (CSP) (weight = 1.313016064, equally weighted for its indicators)

• Technology Specific (PV) (weight = 0.782718753, equally weighted for its indicators)

85

Table 54: Weight of each technology Indices

Technologies Wind PV CSP Total

(Installed+Planned)

MW Countries Installed

Capacity

(planned

projects

MW)

Installed

Capacity

(planned

projects

MW)

Installed

Capacity

(planned

projects

MW)

Algeria 0.7 50 0 2200 25 370 2645.7

Bahrain 0 0 0 5 0 0 5

Egypt 550 2510 15 40 20 200 3335

Iraq 0 0 0 0 0 0 0

Jordan 1.445 1385 1.6 695 0 575 2658.045

Lebanon 0.5 5 0.5 0.1 0 5 11.1

Libya 0 260 4 84 0 0 348

Morocco 290.9 1820 20 20 14 2000 4164.9

Palestine 0 0.1 1 5 0 10 16.1

Syria 0.15 50.6 1 1 0 0 52.75

Sudan 0 300 2 20 0 0 322

Tunisia 245 160 3 37 0 2125 2570

Yemen 0 121 25 5.48 0 0 151.48

Total MW 1088.7 6661.7 73.1 3112.58 59 5285 16280.075

Installed +

Planned

projects

7750.395 3185.68 5344 16280.075

% of each

technology 47.60662958 19.56796882 32.8254016 100%

Weights of

Each

technology out

of 4 (50%) from

Index

1.89265124 0.782718753 1.313016064

86

References

[1] MENICHETTI Emanuela et al., 2011, OME Mediterranean energy perspectives

[2] RCREEE website, January 2013, http://www.rcreee.org/

[3] Hosting diplomacy website, January 2013 http://hostings.diplomacy.edu/baldi/malta2001/statint/Statistics_Int_Affairs-27.htm

[4] ELREFAEI Hatem, 2012, a Methodology for Deriving a Renewable Energy Market Competence Index with Application to CSP Technology, MSc. Thesis, REMENA, Cairo University, Giza, Egypt, Uni- Kassel, Germany.

[5] Renewable Energy Country Attractiveness Indices, January 2013, http://www.ey.com/GL/en/Industries/Cleantech/Renewable-energy-attractiveness-indices---August-2012---CAI-scoring-methodology

[6] SAMBORSKY Brit, 2012, the Arab State of Renewable Energy, an Investigation of Potential for Progress in Arab Electricity Markets, MSc. Thesis, Environmental Management and Policy, Lund, Sweden.

[7] South African IPP Association, February 2012, http://www.saippa.org.za/main.html

[8] CAILLIAU Marcel,et.,al, 2010, Integrating intermittent renewables sources into the EU electricity system by 2020

[9] Wise Geek, February 2012, http://www.wisegeek.com/what-is-a-grid-code.htma

[10] U.S. Government, Department of Energy, February 2013, http://energy.gov/energysaver/articles/planning-home-renewable-energy-systems

[11] Arab Union of Electricity Statistical Bulletin 2012. AUE.

[12] Green Solar Group, February 2013,

http://www.greensolargroup.com/index.php?url=/default/page/129

[13] COUTURE Toby,et.al, 2010, A policy maker’s guide to feed in tariff policy design, Technical Report NREL TP-6A2-44849

[14] Renewable Energy World, February 2013, http://www.renewableenergyworld.com/rea/news/article/2011/03/feed-in-tariffs-or-bidding-how-best-to-assign-renewable-contracts,

[15] Doing Business, International Finance Corporation and World Bank, January 2013, http://www.doingbusiness.org/rankings

[16] Corruption Perceptions Index 2012, January 2013,

http://cpi.transparency.org/cpi2012/results/

87

[17] Government of India, Ministry of New and RE, February 2013, http://www.mnre.gov.in/

[18] GARCIA David et.al., 2010, FEMIP, Study on the Financing of Renewable Energy Investment in the Southern and Easter Mediterranean Region, European Investment Bank, Summer report [19] REN21-2012, Renewable Energy Policy Network for 21st century (REN21); Renewables 2012: Global Status Report; http://www.ren21.net/Portals/97/documents/GSR/REN21_GSR2012.pdf

[20] LEWIS Catherine, 2012, Taxes and incentives for Renewable Energy. KPMG International

[21] Risks and Renewables, managening the Risk in RE http://digitalresearch.eiu.com/risksandrenewables/report/section/executive-summary

[22] HOYER-KLICK Carsten, Introduction to Solar Resource Assessment, German Aerospace Center, Institute of Technical Thermodynamics

[23] Open Energy Information, February 2013, http://en.openei.org/wiki/Renewable_Energy_Technical_Potential_Toolkit

[24] Concentrating Solar Power for the Mediterranean Region, German Aerospace Center (DLR), Institute of Technical Thermodynamics, System Analysis and Technology Assessment Section, April 2005. http://www.dlr.de/tt/Portaldata/41/Resources/dokumente/institut/system/publications/MEDCSP_complete_study.pdf [25] MICHAELA Saisana, A do-it-yourself guide in Excel for composite indicator development, European Commission Joint Research Centre, Ispra, Italy, Version: October 2012 [D] Data collection sources:

1- RCREEE Focal Points, (Someone in each country with a position in Energy sector assist RCREEE with the implementation of the work plan at the national level.)

2- Arab Union of Electricity Statistical Bulletin 2012. AUE. 3- Arab Union of Electricity, Electricity Tariff in the Arab Countries, June 2012

4- GARCIA David et.al., 2010, FEMIP, Study on the Financing of Renewable Energy Investment in the Southern and Easter Mediterranean Region, European Investment Bank, Summer report

5- REN21-2012, Renewable Energy Policy Network for 21st century (REN21); Renewables, 2012: Global Status Report;

http://www.ren21.net/Portals/0/documents/Resources/%20GSR_2012%20highres.pdf

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tــd�f}Gا fـ·l tـiر��Ls ، ـ®ةdxGا

2013

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إbsاد

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�~n� t}lns

�~n� ,tiدnue§ا nd�nLGأ tiر��Ls

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tــd�f}Gا fـ·l tـiر��Ls ، ـ®ةdxGا

2013

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[\_id~�fUPا Vدر� �Ts ل��{Pت اfyTXdZ �Z ء�c^

VefXPءة اf�^دة وbcdUPا VefXPا

fiWj_\ل أfUgو noوpق ا_rPا VWXYZ [\ ]^_UPدة اbcdUPا VefXPا _ghZ

إbsاد

bU{Z |Z}o أbys bUzاP_ءوف/ bYvZس

�~n� t}lns

�~n� ,tiدnue§ا nd�nLGأ tiر��Ls

�bo~ــlns ، t{ــt اn GھــfةGا tــdK�

tــd�f}Gا fـ·l tـiر��Ls ، ـ®ةdxGا

2013

���ل ����� و ا��ھرة ����� ا���د��، � �� إ� �د�� ر����

Vدر� �Ts ل��{Pت اfyTXdZ �Z ء�c^_id~�fUPا [\

VefXPءة اf�^دة وbcdUPا VefXPا