Final Report Feasibility Study on a JCM Project with Japanese Mid ...

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Final Report

Feasibility Study

on a JCM Project with Japanese Mid-size Wind Turbines

in outer islands of the Maldives

(A Study Project of Ministry of Economy, Industry and Trade of Japan)

March, 2015

KOMAI HALTEC Inc.

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INDEX

1. Proposal for Wind Energy Project the Maldives with 300kW turbines ........................................ 4

1.1. Outline of the technology............................................................................................................. 4

1.2. Selection of Projects Sites............................................................................................................ 6

1.2.1. Collection and analysis of existing wind data .................................................................... 6

1.2.2. Electricity Demand in each islands of the Maldives ........................................................ 24

1.2.3. Potentials around Male region........................................................................................... 26

1.2.4. Selected islands for Wind Monitoring ............................................................................... 26

1.3. Conditions of potential site（Kulhudhuffushi） ..................................................................... 27

1.3.1. Information of the existing grid in Kulhudhuffushi......................................................... 27

1.3.2. Land use plan and the siting in Kulhudhuffushi ............................................................. 30

1.3.3. Transportation and Construction conditions in Kulhudhuffushi.................................... 31

1.3.4. Wind monitoring at Kulhudhufushi .................................................................................. 32

1.4. Conditions of potential site（Naifaru） ................................................................................... 37

1.4.1. Information of the existing grid in Naifaru ...................................................................... 37

1.4.2. Land use and siting in Naifaru, Installation and construction....................................... 40

1.4.3. Wind monitoring at Naifaru............................................................................................... 41

1.5. Conditions of potential site（GulhiFalhu）............................................................................. 45

1.5.1. Existing Grid Conditions（GulhiFalhu）......................................................................... 45

1.5.2. Land Use plan（GulhiFalhu） .......................................................................................... 45

1.5.3. Transportation and construction conditions（GulhuFalhu） ......................................... 46

1.5.4. Wind monitoring at GulhiFalhu ........................................................................................ 47

1.6. Other site conditions.................................................................................................................. 49

1.7. System Design ............................................................................................................................ 51

1.7.1. Conditions for the Simulation............................................................................................ 52

1.7.2. Supply Demand Balance Simulation (Long term)............................................................ 55

1.7.3. Control of short term output fluctuation........................................................................... 69

1.7.4. Proposed System design ..................................................................................................... 72

1.7.4.1. Kulhudhuffushi ............................................................................................................... 72

1.7.5. Self-control system of wind turbines ................................................................................. 75

1.8. Evaluaton of the project economy ............................................................................................. 76

1.8.1. Outline of the proposed project.............................................................................................. 76

1.8.2. Project cost (rough estimate) ................................................................................................. 76

1.8.3. Analysis of Project economy................................................................................................... 77

1.9. Implementation Framework ..................................................................................................... 78

1.9.1. Implementation Framework.................................................................................................. 78

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1.9.2. Financing arrangemnt ........................................................................................................... 79

1.10. Timeline for implementaion................................................................................................... 79

1.11. Other potencial sites in the Maldives ................................................................................... 80

2. Policy recommendation................................................................................................................... 81

2.1. Setting technical requirements for wind turbines................................................................... 81

2.2. FIT reflecting the real generation cost of islands.................................................................... 82

2.3. Interconnection of islands for increasing penetration rate..................................................... 82

2.4. Action plan for wind power projects with mid-size wind turbines ......................................... 83

3. MRV Methodology........................................................................................................................... 84

3.1. Eligibility criteria....................................................................................................................... 84

3.2. GHG emission sources ............................................................................................................... 84

3.3. Establishment of reference emissions ...................................................................................... 85

3.4. Emissions from existing diesel generation............................................................................... 85

3.5. Calculation of reference emissions............................................................................................ 86

3.6. Calculation of project emissions................................................................................................ 86

3.7. Monitoring .................................................................................................................................. 87

4. Calculation of GHG emission reductions ...................................................................................... 87

JCM Proposed Methodology Form........................................................................................................ 89

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1. Proposal for Wind Energy Project the Maldives with 300kW turbines

1.1. Outline of the technology

The wind turbine system proposed in this proposal is 300kW wind turbine manufactured by

Komaihaltec Inc, Japan, “KWT300”.

The model has characteristics suitable for the conditions in the Maldives. The outline of features

are described below.

Proposed Wind Turbine Model： a Mid-size wind turbine by Komaihaltec, “KWT300.

Rated output: 300kW

In the world wind market, as the new wind turbines are getting larger and larger, major

manufactured in Europe, U.S., China and India no longer manufacture mid-size models. The French

manufacture Vergnet’s 275kW model is practically the only one other than Komaihaltec in this

capacity class available in the world market. Vergnet has deployed its products mainly to the former

French colonies such as Polynesia and Carrabin countries but none in the Maldives. Moreover, they

usually do not design or propose the micro-grid system, which is essential to the technology transfer

to the Maldives.

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Komaihaltec 300kW wind turbine KWT300

＜Remote Monitoring System＞

In CDM, the monitoring and verification of renewable energy projects require the evidence of the

utility bills or verification of electric meter on site, which are burdensome especially for small scale

projects. The cost in monitoring and verification in small scale projects might possibly cancel out

the merit of CO2 emission credits. In the system proposed here, the energy generation data will be

collected remotely via existing network of the remote monitoring system of the wind turbine,

which can be monitored and collected in Japan, or in capital cities. This would decrease the cost

and energy of the project owner in monitoring and verification.

JCM

electric

meter

Utility

electric

meter

Grid connection point

To Utility Grid

To Utility Grid

Operation monitoring

Data

Logger

Komaihaltec Project owner

Internet

Internet router

Communication

Cable

Generation data

storage

Download data from data logger

Monitor operation status

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1.2. Selection of Projects Sites

To select 300kW wind turbine project sites in the Maldives, we have investigated two data: 1) Wind

resource potential, and 2) electricity demand of the islands large enough to accommodate a 300kW

wind turbine.

1.2.1. Collection and analysis of existing wind data

We have collected and analyzed the wind resource map of the Maldives developed by NREL of the

U.S., data from the Meteorological Agency in the Maldives, and the data taken on telecommunication

towers collected by Ministry of Environment and Energy in the Maldives.

１）NREL Wind Resource Map

Figure 1-1 NREL Wind Resource Map

Figure 3-1 NREL Wind resource map is developed based on satellite data simulation. Yellow and

the brown areas, northern part of the country indicate annual average wind speed over 6.4m/, whichi

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is relatively higher than other areas of the country.

２）Meteorological Agency data

There are five observatories: Hanimaadhoo, Male

（Hulule）, Kadhudhuo, Kaadeshushuoo and Gan.

The wind data is recorded every one hour in case of

Hanimaadhoo.

The original data was in knots, which was converted

to m/s and then summarized. The summary is in chart

3-1. Hanimaadhoo and Male showed higher wind speed

than others.

Location Height Year 2009 Year 2008 Year 2007 average

Hanimaadhoo 12m 3.53m/s 3.40m/s 3.45m/s 3.46m/s

Male(Hulule) 20m 4.51m/s 4.29m/s 4.72m/s 4.51m/s

Kadhdhoo - 3.18m/s 3.30m/s 3.30m/s 3.26m/s

Gan - 3.11m/s 3.16m/s 3.23m/s 3.17m/s

Kaadehdhoo - 2.82m/s 2.93m/s 2.88m/s 2.88m/s

Figure 1-2 Locations of Observatories

and measuring point by MoEE

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Below is the analysis of wind data of Male(Hulule) and Hanimaadhoo observatory.

Hulhule

hulhuleの月平均風速(m/s)

1月 2月 3月 4月 5月 6月 7月 8月 9月 10月 11月 12月年平均

2009年 6.41 4.48 2.59 3.74 5.49 5.66 3.92 5.16 5.28 2.85 4.89 3.88 4.53

2008年 4.80 3.83 3.95 4.17 4.60 4.34 4.96 4.07 4.20 4.53 3.52 4.50 4.29

2007年 7.38 5.35 3.50 2.90 5.31 4.00 4.81 3.85 4.87 6.16 3.17 5.39 4.72

月別平均 6.20 4.55 3.35 3.60 5.13 4.66 4.56 4.36 4.78 4.51 3.86 4.59 4.51

Monthly Average Wind Speed at Hulhule

Monthly Average Wind Speed at Hulhule

Yr2009 Yr2008 Yr2007 Monthly Average

Avera

ge

Win

dS

pee

d

Year Average Wind Direction at Hulhule

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Wind Direction at Hulhule in January Wind Direction at Hulhule in February

Wind Direction at Hulhule in March Wind Direction at Hulhule in April

Wind Direction at Hulhule in May Wind Direction at Hulhule in June

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Wind Direction at Hulhule in July Wind Direction at Hulhule in August

Wind Direction at Hulhule in September Wind Direction at Hulhule in October

Wind Direction at Hulhule in November Wind Direction at Hulhule in December

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2. Hanimaadhoo

hanimaadhooの月平均風速(m/s)

1月 2月 3月 4月 5月 6月 7月 8月 9月 10月 11月 12月年平均

2009年 2.97 2.26 2.11 3.02 4.63 5.20 4.28 5.16 4.68 2.49 3.00 2.57 3.53

2008年 2.87 3.09 2.90 2.88 3.68 4.46 5.23 4.10 3.72 2.92 2.44 2.62 3.41

2007年 3.27 2.94 2.51 2.28 3.50 4.30 5.31 3.70 4.53 3.90 2.56 2.61 3.45

月別平均 3.04 2.77 2.51 2.73 3.94 4.65 4.94 4.32 4.31 3.10 2.66 2.60 3.46

Monthly Average Wind Speed at Hanimaadhoo

Monthly Average Wind Speed at Hanimaadhoo

Yr2009 Yr2008 Yr2007 Monthly Average

Avera

ge

Win

dS

pee

d

Year Average Wind Direction at Hanimaadhoo

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Wind Direction at Hanimaadhoo in January Wind Direction at Hanimaadhoo in February

Wind Direction at Hanimaadhoo in March Wind Direction at Hanimaadhoo in April

Wind Direction at Hanimaadhoo in May Wind Direction at Hanimaadhoo in June

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Wind Direction at Hanimaadhoo in July Wind Direction at Hanimaadhoo in August

Wind Direction at Hanimaadhoo in September Wind Direction at Hanimaadhoo in October

Wind Direction at Hanimaadhoo in November Wind Direction at Hanimaadhoo in December

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写真：Hanimaadhoo Observatory

３）Data of Ministry of Environment and Energy in the Maldives

Ministry of Environment and Energy in the Maldives installed wind speed and wind direction

sensors on telecommunication towers in Villingili and Eydaffushi in 2004. We have analyzed the

data. Since the sensors are installed on the existing telecommunication tower, there might be some

uncertainty in terms of the accuracy of the data, but still, it is a very useful data since it has the data

at 40 meter from the ground.

At Villingili, the annual average wind speed was 5.3m/sat 40 meter height.

The highest average wind speed is in May, followed by January.

The analysis of hourly average wind speed indicates that the wind speed variation is small in

different hours in a day. The most frequent wind speed is East but the wind speed with the most

energy is West.

Vilingili

GulhiFalhuuThilafushi

Male

Hulhule(Airport )

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K.Villingili

※ Difference of sensor 1 and sensor 2 may be caused by some failure in sensor 2 since July 2004.

Villingili 2004年の月平均風速(m/s)

1月 2月 3月 4月 5月 6月 7月 8月 9月 10月 11月 12月年平均40m高 6.64 4.97 4.23 4.16 8.30 5.68 5.24 4.53 5.77 4.20 4.55 5.34 5.3030m高 6.15 4.58 4.06 4.03 8.18 5.65 5.14 4.42 5.74 4.10 4.38 5.06 5.1320m高 5.27 3.92 3.73 3.72 7.96 5.39 4.96 4.05 5.42 3.83 3.92 4.33 4.71

Monthly Average Wind Speed at Villingili in 2004

Monthly Average Wind Speed at Villingili

Year Average Wind Direction at Villingili Sensor 1

Sensor 2

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Wind Direction at Villingili in January Wind Direction at Villingili in February

Wind Direction at Villingili in March Wind Direction at Villingili in April

Wind Direction at Villingili in MayWind Direction at Villingili in June

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Wind Direction at Villingili in July Wind Direction at Villingili in August

Wind Direction at Villingili in SeptemberWind Direction at Villingili in October

Wind Direction at Villingili in November Wind Direction at Villingili in December

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Villingili地上高40mの時間別平均風速

01 02 03 04 05 06 07 08 09 10 11 1200 6.55 4.91 4.03 4.14 8.07 5.64 5.21 3.96 5.74 4.51 4.59 5.34 5.2301 6.49 4.80 3.97 4.41 8.21 5.79 5.19 4.10 5.96 4.17 4.62 5.26 5.2602 6.41 4.69 4.07 4.36 8.23 5.83 5.23 4.08 6.09 3.88 4.83 5.16 5.2503 6.46 4.78 4.09 4.26 8.53 5.77 5.59 4.33 6.48 4.10 4.71 5.30 5.3804 6.49 4.83 4.13 4.31 8.46 5.93 5.52 4.39 6.05 4.14 4.51 5.39 5.3605 6.43 4.61 4.27 4.40 8.26 5.84 5.49 4.42 5.90 4.41 4.40 5.16 5.3106 6.32 4.56 4.39 4.31 8.30 5.71 5.14 4.49 5.95 4.34 4.58 5.18 5.2907 6.31 4.66 4.38 4.19 8.02 5.77 5.10 4.52 5.86 4.46 4.51 5.26 5.2708 6.53 4.60 4.31 4.02 8.10 5.59 5.05 4.72 5.74 3.70 4.77 5.35 5.2209 6.69 4.63 4.42 3.99 8.18 5.24 5.07 4.64 5.58 3.70 4.56 5.32 5.1810 6.92 4.84 4.46 3.91 8.15 5.38 5.03 4.81 5.63 3.72 4.57 5.05 5.2211 6.96 5.12 4.38 3.79 8.17 5.35 5.40 4.88 5.78 4.10 5.06 5.20 5.3612 7.05 5.08 4.37 3.75 8.35 5.46 5.41 4.90 5.60 4.25 5.01 5.18 5.3813 6.84 4.94 4.40 3.78 8.54 5.85 5.34 4.65 5.46 4.16 5.02 4.88 5.3414 6.72 5.07 4.42 3.98 8.75 5.71 5.52 4.71 5.77 4.31 4.69 5.14 5.4215 6.49 5.17 4.30 4.05 8.84 5.61 5.33 5.19 5.86 4.46 4.70 5.40 5.4616 6.35 5.11 4.27 4.29 8.74 5.70 5.36 4.91 5.94 4.58 4.72 5.35 5.4617 6.45 5.13 4.31 4.23 8.66 5.80 5.14 4.72 6.01 4.38 4.73 5.58 5.4318 6.75 5.26 4.19 4.06 8.35 5.72 5.69 4.57 5.59 4.13 4.60 5.62 5.3819 6.80 5.13 4.10 4.24 8.24 5.92 5.37 4.49 5.77 4.07 3.99 5.59 5.3220 6.89 5.31 4.11 4.18 8.03 5.68 5.09 4.39 5.47 4.16 4.04 5.62 5.2521 6.95 5.45 4.00 4.39 8.10 5.69 5.13 4.30 5.28 4.24 3.97 5.88 5.2922 6.76 5.42 4.03 4.34 7.93 5.77 4.81 4.30 5.37 4.34 3.95 5.66 5.2323 6.71 5.12 4.05 4.38 7.89 5.60 4.65 4.34 5.53 4.62 4.00 5.39 5.19

6.64 4.97 4.23 4.16 8.30 5.68 5.24 4.53 5.77 4.20 4.55 5.34 5.31

月

時間

平均風速年間

月別

Villingili地上高40mの風向別風速出現率（％）

N NNE NE ENE E ESE SE SSE S SSW SW WSW W WNW NW NNW0 ≦ V ＜ 1 0.13 0.50 1.10 0.73 0.18 0.07 0.07 0.12 0.05 0.10 0.24 0.08 0.06 0.06 0.09 0.08 3.651 ≦ V ＜ 2 0.15 1.17 1.83 1.03 0.39 0.08 0.10 0.30 0.22 0.32 0.22 0.22 0.21 0.06 0.09 0.13 6.522 ≦ V ＜ 3 0.65 1.40 1.73 1.57 0.69 0.18 0.15 0.23 0.45 0.38 0.28 0.24 0.27 0.25 0.18 0.21 8.863 ≦ V ＜ 4 1.08 1.68 2.54 2.84 1.12 0.38 0.13 0.38 0.57 0.24 0.38 0.21 0.32 0.57 0.32 0.38 13.144 ≦ V ＜ 5 0.84 1.59 2.24 2.90 1.32 0.63 0.25 0.29 0.32 0.20 0.37 0.39 0.46 0.62 0.70 0.90 14.035 ≦ V ＜ 6 0.66 2.19 2.33 3.29 1.67 0.53 0.50 0.10 0.32 0.25 0.37 0.52 0.73 0.84 0.98 0.46 15.756 ≦ V ＜ 7 0.24 2.04 1.74 3.25 1.45 0.29 0.47 0.12 0.20 0.27 0.38 0.89 1.08 0.84 0.92 0.20 14.397 ≦ V ＜ 8 0.02 1.26 0.82 2.34 1.32 0.14 0.17 0.05 0.16 0.10 0.29 0.38 1.07 0.75 0.51 0.06 9.448 ≦ V ＜ 9 0.05 0.65 0.28 1.17 0.55 0.12 0.07 0.01 0.08 0.08 0.18 0.08 0.44 0.59 0.33 0.03 4.719 ≦ V ＜ 10 0.01 0.39 0.07 0.69 0.55 0.06 0.08 0.01 0.00 0.08 0.17 0.06 0.48 0.62 0.50 0.01 3.8010 ≦ V ＜ 11 0.00 0.33 0.10 0.39 0.52 0.00 0.03 0.01 0.01 0.06 0.05 0.14 0.13 0.36 0.43 0.02 2.5911 ≦ V ＜ 12 0.00 0.32 0.06 0.29 0.10 0.01 0.01 0.02 0.00 0.01 0.03 0.03 0.09 0.25 0.12 0.01 1.3712 ≦ V ＜ 13 0.00 0.17 0.09 0.06 0.01 0.01 0.01 0.01 0.00 0.00 0.03 0.00 0.22 0.17 0.01 0.00 0.8113 ≦ V ＜ 14 0.00 0.05 0.09 0.06 0.00 0.00 0.02 0.01 0.00 0.00 0.00 0.00 0.25 0.20 0.00 0.00 0.6814 ≦ V ＜ 15 0.00 0.01 0.00 0.02 0.01 0.01 0.00 0.03 0.00 0.00 0.01 0.00 0.05 0.06 0.00 0.00 0.2115 ≦ V ＜ 16 0.00 0.00 0.00 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.0316 ≦ V ＜ 17 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.0117 ≦ V ＜ 18 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.0018 ≦ V ＜ 19 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.0019 ≦ V ＜ 20 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.0020 ≦ V ＜ 21 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.0021 ≦ V ＜ 22 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.0022 ≦ V ＜ 23 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.0023 ≦ V ＜ 24 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.0024 ≦ V ＜ 25 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

3.96 5.24 4.22 5.38 5.77 4.97 5.50 4.04 4.14 4.37 5.12 5.50 6.91 7.08 6.42 4.44 100.0平均風速(m/s)

風速風向

total

Hourly Average Wind Speed in Villingili

m/s

Month

Hou

rof

the

da

y

year

average

Frequency Distribution of Wind Class in Villingili at 40meter height

Wind Direction

m/s

Average m/s

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Eydhafushi

At Eydafushi, the annual average wind speed was 5.39m/sat 48m height. The highest monthly

average wind speed is recorded in May, June July, and December and January. There is no

significant difference in hours of the day, which indicates the constant wind speed throughout a day.

The most frequent and the strongest wind direction is West followed by East.

Eydhafushi

Eydhaffushi 2004年の月平均風速(m/s)

1月 2月 3月 4月 5月 6月 7月 8月 9月 10月 11月 12月年平均48m高 6.19 4.15 3.71 3.22 8.42 6.93 6.91 4.99 5.85 4.20 4.04 6.08 5.3928m高 6.06 4.13 3.77 3.31 8.07 6.42 6.83 5.02 5.69 4.14 4.04 5.94 5.2920m高 5.85 4.09 3.63 3.04 7.26 5.73 6.18 4.61 5.14 3.62 3.68 5.63 4.87

←Eydhafushi

Naifaru→

Monthly Average Wind Speed at Eydafushi in 2004

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Monthly Average Wind Speed at Eydafushi

Year Average Wind Direction at Eydafushi Sensor 1

Sensor 2

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Wind Direction at Eydafushi in January Wind Direction at Eydafushi in February

Wind Direction at Eydafushi in March Wind Direction at Eydafushi in April

Wind Direction at Eydafushi in MayWind Direction at Eydafushi in June

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Wind Direction at Eydafushi in July Wind Direction at Eydafushi in August

Wind Direction at Eydafushi in September Wind Direction at Eydafushi in October

Wind Direction at Eydafushi in November Wind Direction at Eydafushi in December

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Eydhafushi地上高48mの時間別平均風速

01 02 03 04 05 06 07 08 09 10 11 1200 6.22 3.79 3.27 3.20 8.37 6.98 6.93 4.28 6.10 3.69 3.96 5.90 5.2401 6.05 3.62 3.32 3.29 8.45 6.77 7.38 4.61 6.22 3.79 3.65 5.88 5.2702 5.96 3.68 3.16 3.13 8.55 6.62 6.82 4.74 6.10 3.86 4.00 5.92 5.2303 5.85 3.59 3.05 3.09 8.65 6.93 6.69 4.73 6.30 3.96 3.99 5.90 5.2504 5.79 3.62 3.06 3.21 8.83 7.21 6.63 4.77 6.28 4.25 3.79 5.93 5.3005 5.80 3.70 3.24 3.07 8.64 7.07 6.87 4.81 5.96 4.22 4.00 6.05 5.3006 5.84 3.69 3.29 3.19 8.58 7.25 6.57 4.88 5.66 3.97 3.85 6.03 5.2507 6.02 3.69 3.48 3.09 8.33 7.30 6.52 5.13 5.65 3.93 3.84 6.09 5.2708 6.23 3.92 3.58 2.93 8.29 6.99 6.41 4.87 5.55 3.84 3.94 6.04 5.2309 6.37 3.96 3.85 2.94 8.62 7.04 6.57 4.90 5.75 3.81 4.01 6.08 5.3410 6.41 4.24 4.06 3.12 8.13 6.91 6.57 4.94 6.10 4.22 4.33 6.04 5.4411 6.35 4.47 4.24 2.98 8.24 6.86 6.77 5.16 6.17 4.30 4.35 6.06 5.5112 6.27 4.69 4.37 3.18 8.82 7.06 7.00 5.52 5.76 4.25 4.41 6.42 5.6613 6.19 4.78 4.45 3.25 8.73 7.10 7.15 5.56 5.61 4.31 4.43 6.25 5.6714 6.13 4.88 4.36 3.23 8.70 7.08 7.02 5.50 5.81 4.66 4.15 6.25 5.6615 6.13 4.81 4.29 3.24 8.64 7.00 7.82 5.37 6.14 4.66 3.96 6.20 5.7016 6.22 4.59 4.11 3.40 8.82 6.96 7.77 5.55 6.07 4.75 3.99 6.22 5.7217 6.27 4.50 3.91 3.46 8.64 6.98 7.50 5.30 5.95 4.65 4.14 6.03 5.6318 6.27 4.31 4.04 3.21 8.15 6.59 7.24 5.33 5.90 4.53 4.16 6.09 5.5019 6.31 4.34 3.88 3.27 8.26 6.72 7.07 4.80 6.08 4.39 4.38 6.01 5.4720 6.39 4.40 3.74 3.46 7.93 6.76 7.02 4.87 5.66 4.21 4.24 6.33 5.4321 6.46 4.31 3.63 3.51 7.89 6.80 6.66 4.70 5.28 4.33 3.98 6.23 5.3322 6.52 4.00 3.47 3.37 7.93 6.72 6.38 4.78 5.02 4.19 3.60 6.01 5.1823 6.41 3.96 3.25 3.38 7.99 6.59 6.47 4.76 5.40 4.10 3.69 6.05 5.19

6.19 4.15 3.71 3.22 8.42 6.93 6.91 4.99 5.85 4.20 4.04 6.08 5.41

平均風速月

年間

時間

月別

Eydhafushi地上高40mの風向別風速出現率（％）

N NNE NE ENE E ESE SE SSE S SSW SW WSW W WNW NW NNW0 ≦ V ＜ 1 0.60 0.57 0.55 0.45 0.31 0.25 0.33 0.31 0.32 0.29 0.28 0.25 0.28 0.73 0.48 0.46 6.461 ≦ V ＜ 2 1.01 0.47 0.33 0.38 0.34 0.29 0.15 0.41 0.53 0.42 0.22 0.46 0.54 0.55 0.46 0.40 6.962 ≦ V ＜ 3 0.97 0.85 0.58 0.64 0.56 0.19 0.29 0.23 0.21 0.25 0.46 0.58 0.78 0.58 0.69 0.61 8.493 ≦ V ＜ 4 0.73 0.73 1.08 1.20 0.60 0.26 0.24 0.15 0.26 0.37 0.49 0.91 0.79 0.93 0.63 0.81 10.204 ≦ V ＜ 5 0.77 0.88 1.78 2.12 0.89 0.24 0.13 0.14 0.17 0.55 0.48 0.62 0.94 1.46 1.22 0.71 13.105 ≦ V ＜ 6 0.56 0.88 1.36 1.61 1.30 0.26 0.10 0.03 0.14 0.25 0.44 0.89 1.58 1.73 1.54 0.64 13.336 ≦ V ＜ 7 0.24 0.46 0.60 1.02 1.56 0.18 0.02 0.00 0.01 0.10 0.58 1.07 1.67 2.52 1.40 0.46 11.917 ≦ V ＜ 8 0.09 0.11 0.13 0.89 1.63 0.17 0.02 0.00 0.01 0.10 0.46 0.99 1.65 2.73 1.07 0.19 10.258 ≦ V ＜ 9 0.06 0.00 0.05 0.57 1.15 0.16 0.02 0.00 0.01 0.02 0.37 1.20 1.57 1.75 0.92 0.14 7.999 ≦ V ＜ 10 0.00 0.00 0.01 0.32 0.70 0.07 0.00 0.00 0.00 0.01 0.10 0.69 0.93 1.30 0.55 0.21 4.8910 ≦ V ＜ 11 0.00 0.00 0.00 0.32 0.67 0.02 0.00 0.00 0.00 0.00 0.06 0.32 0.81 0.75 0.18 0.01 3.1411 ≦ V ＜ 12 0.00 0.00 0.00 0.22 0.31 0.03 0.00 0.00 0.00 0.00 0.02 0.13 0.37 0.40 0.06 0.00 1.5412 ≦ V ＜ 13 0.00 0.00 0.00 0.06 0.22 0.00 0.00 0.00 0.00 0.00 0.00 0.06 0.50 0.14 0.03 0.00 1.0113 ≦ V ＜ 14 0.00 0.00 0.00 0.00 0.03 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.29 0.10 0.01 0.00 0.4514 ≦ V ＜ 15 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.10 0.02 0.03 0.00 0.1715 ≦ V ＜ 16 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.07 0.02 0.00 0.00 0.1016 ≦ V ＜ 17 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.0117 ≦ V ＜ 18 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.0018 ≦ V ＜ 19 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.0019 ≦ V ＜ 20 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.0020 ≦ V ＜ 21 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.0021 ≦ V ＜ 22 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.0022 ≦ V ＜ 23 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.0023 ≦ V ＜ 24 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.0024 ≦ V ＜ 25 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

3.19 3.66 4.12 5.34 6.50 4.41 2.76 2.09 2.46 3.44 5.05 6.07 6.90 6.46 5.63 4.17 100.0

風速風向

total

平均風速(m/s)

Hourly Average Wind Speed in Villingili

m/s

Month

Hou

rof

the

da

y

average

Frequency Distribution of Wind Class in Villingili at 40meter height

Wind Direction

m/s

Average m/s

year

24

1.2.2. Electricity Demand in each islands of the Maldives

To select the potential project site for the 300kWwind turbines , we have selected the islands with

larger electricity demand to avoid extra cost for battery storage system.

Table 3-2 shows the top 30 FENAKA served islandsin terms of annual electricity generation. There

are 13 islands with the daily peak demand larger than 300kW, which is the rated capacity of the

wind turbine. Among these, Kulhudhuffushi and Naifaru are selected since they located northern

part of the country where wind resource is expected to be richer.

Table 1-1 Top 30 FENAKA islands

Atoll Island Population

Min

Demand

kW()

Max

Demand

(kW)

Installed

Capacity

(kW)

Generated Units

(kWh)

CPS (S,Hithadhoo) 23844 1870 3850 6850 1941336

Hdh. Kulhudhuffushi 8947 581 1330 3040 748506

Atoll Fuvahmulah 11857 670 1330 2170 688353

G. Dh.Thinadhoo 7108 560 1051 2320 684574

Ga. Villingili 3460 210 481 1230 534116

Lh. Naifaru 5133 305 580 720 307224

B. Eydhafushi 3123 212 500 750 242149

S. HulhuMeedhoo 2800 210 420 2500 227971

Lh. Hinnavaru 4676 205 410 760 224314

Ha. Dhidhdhoo 3848 160 412 600 191365

Dh. Kudahuvadhoo 2544 163 406 942 180569

Ha. Hanimaadhoo 1885 115 315 770 156243

N. Velidhoo 2500 106 285 586 143121

L.Gan Mathimaradhoo 4385 110 200 275 142609

L. Fonadhoo 2147 360 440 640 138554

G. Dh.Gahdhoo 2953 128 230 550 137036

R. Dhuvaafaru 2520 166 295 750 136644

Ha. Hoarafushi 3277 130 275 650 131193

N. Manadhoo 1802 104 264 368 124200

B. Thulhaadhoo 2795 87 193 650 120223

Ha. Ihavandhoo 2988 100 225 570 118884

Th. Thimarafushi 2548 125 229 510 117892

N. Holhudhoo 2143 102 216 320 114478

Sh. Milandhoo 2280 86 221 862 112595

R. Alifushi 2589 42 193 418 103649

25

Table 1-2 STELCO islands1

Island Max Demand(kW) Total Capacity(kW)

Male 40,000 60,420

Hulumale 2410 4000

Vilingili 1470 2800

Thilafushi 580 1660

Kashidhoo 220 610

Gaafaru 105 390

Thulusdhoo 280 940

Himmafushi 320 1010

Gulhifalhu 32 163

Gulhi 110 360

Maafushi 520 1660

Guraidhoo 235 618

AA. Ukulhas 110 380

AA. Bodhufulhadhoo 67 320

AA. Mathiveri 102 390

AA. Feridhoo 61 224

AA. Maalhos 53 160

AA. Himandhoo 85 428

ADH. Omadhoo 84 370

ADH. Kuburudhoo 40 170

ADH. Dhigarah 65 202

ADH. Dhidhdhoo 17 107

ADH. Fenfushi 80 375

V. Fulidhoo 56 260

V. Thinadhoo 32 170

V. Keyodhoo 66 217

V. Rankeedhoo 24 94

Table 3-3 shows the STELCO served islands. Male is extremely large compare to others followed by

Villingili and Hulhumale. However, these islands are under consideration of interconnection thus,

not considered for the 300kW potential islands, as 300kW wind turbines could offer the best merit

for smaller scale islands.

1 STELCOWebsite より作成

26

1.2.3. Potentials around Male region

As described earlier, Male region has good potential for wind energy project in terms of wind

resources. In the meetings with the Ministry of Environment and Energy, they have showed a large

interest in installing wind turbines around Male, considering that that would be the first commercial

wind turbines in the Maldives, which could bring in significant meaning as a symbol.

We have originally planned to select Thilafushi for the feasibility study, however, due to the delay

in finding the space for wind mast installation, we decided to install wind mast on the adjacent

island of GulhiFalhu in cooperation with MWSC.

However, Thilafushi is still a good potential site for a wind turbine project.

1.2.4. Selected islands for Wind Monitoring

As above, three islands of Kulhudhuffushi, Naifaru, and GulhiFalhu are selected for wind

monitoroing.

27

1.3. Conditions of potential site（Kulhudhuffushi）

1.3.1. Information of the existing grid in Kulhudhuffushi

Table 2-1 Generators in Kulhudhuffushi

Gen.1 Gen.2 Gen.3 Gen.4Capacity , kW 1000 1000 1000 800Power factor 0.8 0.8 0.8 0.8frequency , Hz 50 50 50 50Type of governor Electronic Electronic Electronic ElectronicRotational speed, rpm 1500 1500 1500 1500Rated voltage , V 400 400 400 400Manufacturer and Model Cummins Cummins Cummins Cummins

Set Model X14F254705 X14F253711 C1250 D2R C1000 D5EEngine KTA50-G3 KTA50-G3 KTA50-G3 KTA50-G1

Year of manufacture 2014 2014 2010 1990Type of fuels Diesel Diesel Diesel DieselConditions of generator Normal Normal Normal NormalMaximum load/output, kW 1000 1000 1000 800Minimum load/output, kW 501 501 300 240Fuel Consumption, L/h

100% 259 259 261 23075% 200 200 199 17550% 130 130 139 12225% 70 70 76 67

Gen.1

Gen.2

Gen.3

Gen.4

28

(2) Electricity Demand

The electricity demand is increasing at the rate of 5 % a year.

Generated units

[kWh]

Fuel consumption

[L]

Monthly fuel

efficienty

[L/kWh]

Jan-12 667,731

8,766,336

183,605

2,474,269

0.275

Feb-12 657,694 185,230 0.282

Mar-12 735,183 200,369 0.273

Apr-12 760,813 208,971 0.275

May-12 802,519 227,498 0.283

Jun-12 717,964 204,569 0.285

Jul-12 752,422 204,560 0.272

Aug-12 743,906 210,143 0.282

Sep-12 742,442 208,577 0.281

Oct-12 748,506 213,726 0.286

Nov-12 726,313 215,071 0.296

Dec-12 710,843 211,950 0.298

Jan-13 742,442

9,087,079

223,410

2,682,389

0.301

Feb-13 689,249 207,960 0.302

Mar-13 818,459 244,520 0.299

Apr-13 807,638 240,390 0.298

May-13 774,345 231,380 0.299

Jun-13 691,572 206,620 0.299

Jul-13 750,964 224,590 0.299

Aug-13 762,063 225,698 0.296

Sep-13 744,476 211,108 0.284

Oct-13 811,810 232,420 0.286

Nov-13 755,253 217,811 0.288

Dec-13 738,808 216,482 0.293

Jan-14 779,562

8,436,849

222,660

2,425,895

0.286

Feb-14 730,658 206,243 0.282

Mar-14 849,375 238,592 0.281

Apr-14 870,651 245,285 0.282

May-14 909,636 254,470 0.280

Jun-14 870,299 243,445 0.280

Jul-14 912,405 259,990 0.285

Aug-14 824,781 247,055 0.300

Sep-14 828,271 248,580 0.300

Oct-14 861,211 259,575 0.301

Nov-14

Dec-14

29

(3) Load

The daily load curve of 2013. Average load is 1,224kW, Peak load is 2,044kW and the lowest

load of the year is 693kW.

Load Curve of year 2013

Monthly average load

Load Duration Curve

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec0

500

1,000

1,500

2,000

2,500

Po

wer

(kW

)

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Ann

500

1,000

1,500

2,000

Avera

ge

Valu

e(k

W)

Scaled data Monthly Averages

Month

max

daily high

mean

daily low

min

0 2,000 4,000 6,000 8,0000

500

1,000

1,500

2,000

2,500

Valu

e(k

W)

Scaled data Duration Curve

Hours Equaled or Exceeded

30

Year average hourly load curve

Monthly averge hourly load curve

1.3.2. Land use plan and the siting in Kulhudhuffushi

In Kulhudhuffushi, there is a wetland in the northern part of the island, it is a plant ecosystem

protection area. On the other hand, in the south part of the island is in the industrial area, and

FENAKA power plant, port, waste disposal facility are located. Therefore, wind power plant

installation site should be near the power plant and around the harbor district, etc.

Wind mast is installed at the location of Wind Turbine1.

0 6 12 18 240

500

1,000

1,500

2,000

Lo

ad

(kW

)

Daily Profile

Hour

0 6 12 18 240

500

1,000

1,500

2,000Jan

0 6 12 18 240

500

1,000

1,500

2,000Feb

0 6 12 18 240

500

1,000

1,500

2,000Mar

0 6 12 18 240

500

1,000

1,500

2,000Apr

0 6 12 18 240

500

1,000

1,500

2,000May

0 6 12 18 240

500

1,000

1,500

2,000Jun

0 6 12 18 240

500

1,000

1,500

2,000Jul

0 6 12 18 240

500

1,000

1,500

2,000Aug

0 6 12 18 240

500

1,000

1,500

2,000Sep

0 6 12 18 240

500

1,000

1,500

2,000Oct

0 6 12 18 240

500

1,000

1,500

2,000Nov

0 6 12 18 240

500

1,000

1,500

2,000Dec

31

Kulhudhuffushi Land Use Plan

WT1 area Port area

1.3.3. Transportation and Construction conditions in Kulhudhuffushi

In Kulhudhuffushi, there is an international port besides jetty port, which is operated by the Port

Authority. At the international port, the facilities are good enough for unloading wind turbine parts.

■Power House

Port Land

Wind Turbine 1●

Wind Mast Position

●Wind Turbine 2

Third Wind Turbine Site

（Port Premises）

Conservation Area

32

The Port authority maintains cranes of 150 ton, 30 ton, and 25 ton capacity, which could be used

for wind turbines installation.

Unloading at the port

150ton Crane

1.3.4. Wind monitoring at Kulhudhufushi

34 meter mast is installed to monitor the wind conditions.

33

Outline of wind monitoroing

Location

Coordinates

Next to power house in Kulhudhuffushi Kulhudhufushi

6°36'46.2"N 73°04'14.8"E

Duration From Dec, 1st

Monitoring items

(ten minutes average)

・average wind speed

・average wind direction

・wind speed deviation

・max wind speed

Sensors 32m： wind speed sensor 1,wind speed sensor 2

30m：wind direction sensor 1

22m：wind speed sensor 3, wind direction sensor 2

Monitoring system Manufacture: NRG

Datalogger： NRG Synphonie

Sensors： NRG

data transfer system： NRG iPack

Image

34 meter tower

Monitored at 2 levels

34

foundation installation Mast assembly

Mast erection Monitoring in progress

＜Monitored Data＞

No.3 クルドゥフシ月平均風速

＜サイト7886＞2015年 2014年 (m/s)1月 2月 3月 4月 5月 6月 7月 8月 9月 10月 11月 12月平均

CH1Avg(32m) 3.82 3.41 3.58 3.60CH2Avg(32m) 3.84 3.44 3.62 3.63CH3Avg(22m) 3.69 3.24 3.44 3.46

Monthly average wind speed at Kulhudhufushi

35

Wind speed in December

Wind speed in February

Wind speed in January

36

Wind Direction in December

Wind Direction in January

Wind Direction in February

37

1.4. Conditions of potential site（Naifaru）

1.4.1. Information of the existing grid in Naifaru

Table 2-3 Generators in Naifaru

Gen.1 Gen.2 Gen.3 Gen.4Capacity , kW 720 300 640 800Power factor 0.8 0.8 0.8 0.8frequency , Hz 50 50 50 50Type of governor Electronic Electronic Electronic ElectronicRotational speed, rpm 1500 1500 1500 1500Rated voltage , V 400 400 400 400Manufacturer and Model Cummins Cummins Cummins Cummins

Set Model C1100 D5B C500 D5B C900 D5 C1100 D5BEngine KTA38-G5 KTA19-G3 QSK23-G3 KTA38-G5

Year of manufacture 2009.01 2002.08 2008.02 2014.12Type of fuels Diesel Diesel Diesel DieselConditions of generator limited output normal normal normalMaximum load/output, kW 600 200 560 800Minimum load/output, kW 350 150 250 240Fuel Consumption, L/h

100% 209 107 161 20975% 161 82 121 16150% 113 57 85 11325% 65 30 46 65

Gen.1 Gen.2 Gen.3 Gen.4

(2) Electricity Demand

38

The demand is increasing at the rate of 5 % a year,

Generated units

[kWh]

Fuel consumption

[L]

Monthly fuel

efficienty

[L/kWh]

Jan-13 306,762

3,855,239

84,905

1,080,538

0.277

Feb-13 282,658 77,516 0.274

Mar-13 338,378 92,398 0.273

Apr-13 344,862 94,804 0.275

May-13 321,926 89,397 0.278

Jun-13 301,363 83,960 0.279

Jul-13 331,352 91,807 0.277

Aug-13 330,886 93,288 0.282

Sep-13 313,698 86,694 0.276

Oct-13 344,601 99,709 0.289

Nov-13 317,350 92,187 0.290

Dec-13 321,403 93,873 0.292

Jan-14 324,877

3,507,194

95,112

995,434

0.293

Feb-14 309,089 88,390 0.286

Mar-14 348,877 100,801 0.289

Apr-14 363,193 103,596 0.285

May-14 368,992 103,343 0.280

Jun-14 360,345 101,072 0.280

Jul-14 384,974 106,745 0.277

Aug-14 352,530 99,392 0.282

Sep-14 336,211 96,256 0.286

Oct-14 358,106 100,727 0.281

Nov-14

Dec-14

(3) Load

The daily load curve of 2013. Average load is594kW, Peak load is 875kW and the lowest load of the

year is 168kW. A few times of blackout are recorded.

39

Hourly load of the year 2013

Monthly average load of 2013

Load duration curve


200

400

600

800

1,000

Po

wer

(kW

)

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Ann0

200

400

600

800

1,000

Avera

ge

Valu

e(k

W)


Month

max

daily high

mean

daily low

min

0 2,000 4,000 6,000 8,0000

200

400

600

800

1,000

Valu

e(k

W)



40

Annual average hourly load curve

Monthly average daily load curve

1.4.2. Land use and siting in Naifaru, Installation and construction.

North of Naifaru is designated to industrial zone where FENAKA power plant, water desalination

plant, and waste management plant are located.

As for the transportation and construction, there are not harbor for large vessels, thus a verge will

be required to transport wind turbine parts for Naifarr. Similarly, there are no cranes in the islands,

thus need to be brought in from other islands.

0 6 12 18 240

200

400

600

800

1,000

Lo

ad

(kW

)

Daily Profile

Hour

0 6 12 18 240

200

400

600

800

1,000Jan

0 6 12 18 240

200

400

600

800

1,000Feb

0 6 12 18 240

200

400

600

800

1,000Mar

0 6 12 18 240

200

400

600

800

1,000Apr

0 6 12 18 240

200

400

600

800

1,000May

0 6 12 18 240

200

400

600

800

1,000Jun

0 6 12 18 240

200

400

600

800

1,000Jul

0 6 12 18 240

200

400

600

800

1,000Aug

0 6 12 18 240

200

400

600

800

1,000Sep

0 6 12 18 240

200

400

600

800

1,000Oct

0 6 12 18 240

200

400

600

800

1,000Nov

0 6 12 18 240

200

400

600

800

1,000Dec

41

Verge staying at Naifaru JettyPort

1.4.3. Wind monitoring at Naifaru

40 meter wind mast is installed for wind monitoring.

Power House

Wind Energy Site

42

Outline of wind monitoring

Location

Coordinates

Next to power house in Naifaru

5°26'57.0"N 73°21'57.2"E

Duration From Dec, 1st

Monitoring items





・max wind speed

Sensors 40m： wind speed sensor 1, wind speed sensor 2

40m： wind direction sensor 1




Sensors： NRG


Image


43

foundation installation

Mast assembly

Mast erection Monitoring in progress

＜Monitored Data＞

現在No.1 ナイファル月平均風速

＜サイト7884＞2015年 2014年 (m/s)1月 2月 3月 4月 5月 6月 7月 8月 9月 10月 11月 12月平均

CH1Avg(40m) 5.74 5.20 3.42 4.79CH2Avg(40m) 5.71 5.19 3.39 4.76CH3Avg(30m) 5.68 5.25 3.35 4.76

2015/3/1

Monthly average wind speed at Naifaru

44

Wind speed in December

Wind Direction in January

Wind Direction in Feburary

45

1.5. Conditions of potential site（GulhiFalhu）

1.5.1. Existing Grid Conditions（GulhiFalhu）

For GulhiFalhu, detailed data is not obtained. GulhiFalhu is a newly claimed artificial island

and still landfill is in progress and various development is developing stage. In GulhiFalhu, there is

a power plant of STELCO, but power demand for development is bery limited at this moment.

On the other hand, half of the island is owned by MWSC (Male Water and Sewage Company),

where pipe manufacturing plant is located. In the plant, MWSC uses its own diesel generator of

1MW capacity. Thus, 300kWwind turbines could be operated with the existing diesel generator.

1.5.2. Land Use plan（GulhiFalhu）

The development of GulhiFalhu is led by Global Projects Development Company.

Commercial, residential, industrial and logistics zones are planned but the development of

residential zone in pending due to the air pollution from the Thilafushi waste management facility.

MWSC has a plan to construct water bottling facility and water tanks as well as desalination plant

in GulhiFalhu.

The preliminary wind turbine location is set in a planned green area.

46

MWSC Land Use plan

1.5.3. Transportation and construction conditions（GulhuFalhu）

At this moment in GulhiFalhu, no cargo port is developed yet. Since there is no heavy equipment

on the island, there is a need to carry from such adjacent Male and Thilafushi. To load wind power

equipment, it is necessary to consider to transportation with barges.

Unloading of wind mast

47

1.5.4. Wind monitoring at GulhiFalhu

Originally it was scheduled to start wind monitoring at GulhiFalhu from December, however, due

to some troubles in the installation, the installation is postponed till February.

Outline of wind monitoring

Location

Coordinates

Next to power house in Naifaru

4°11'06.6"N 73°27'34.6"E

Duration From Feb 18th

Monitoring items





・max wind speed

Sensors 40m： wind speed sensor 1, wind speed sensor 2

40m： wind direction sensor 1




Sensors： NRG


Image


48

foundation installation マスト Mast assembly

マスト Mast erection Monitoring in progress

Monitored data

49

1.6. Other site conditions

（１）Noise Level

The below chart is the sound level of KWT300.

With a distance of 75m, the noise level is below 55dB, when the background noise is 50dB.

In Kulhudhuffushi and Naifaru, the planned wind turbines locations are farther than 100meter.

Wind Speed in February

Wind direction in February

50

（２）Civil Aviation restriction

Chart 3-3 is the height restriction around Male area by the Maldivian Civil Authority.

In the red area, any construction is restricted, and within the area of 4km diameter, marked as

green, the height is limited below 45meter, and within the blue area, the height limit changes along

with the 5% slope up to 6km. At the east end of GulhiFalhu, 6km away from Male international

aieport, the height limit is 145m.

Both in Kulhudhuffushi and Naifaru, the existing airport is farther enough, however the attention

should be paid to the new airport construction.

Distance at the point of

55dB

Distance at the point of

45dB

Wind turbine itself 55 m 200 m

With 40dB background noise 60 m 240 m

With 50dB background noise 75 m －

45dB

55dB

51

1.7. System Design

With the above-mentioned power supply and demand data and the wind conditions data of

52

Eydafushi, micro grid simulation was carried out.

1.7.1. Conditions for the Simulation

１）Wind condition

【Wind data used for simulation】

・Period：2004/01/01

-2004/12/31

・Location：Eydhafushi

・Height：48m

・Data frequency：Hourly

2004 48m 28m

Jan 6.229 6.059

Feb 4.097 4.135

Mar 3.713 3.774

Apr 3.217 3.307

May 8.423 8.069

Jun 6.928 6.423

Jul 6.910 6.833

Aug 4.804 5.016

Sep 5.855 5.688

Oct 4.116 4.137

Nov 4.035 4.042

Dec 6.084 5.945

Year ave 5.382 5.301

２．Characteristics of the wind

Annual average wind speed is 5.382 m/s, and max wind speed was 16.3 m/s.

Wind speed is relatively higher from May to October due to monsoons.

53

Hourly wind speed of the year

Monthly average wind speed.

Wind Speed duration curve


5

10

15

20

Win

dS

peed

(m/s

)

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Ann0

5

10

15

20

Avera

ge

Valu

e(m

/s)


Month

max

daily high

mean

daily low

min

0 2,000 4,000 6,000 8,0000

5

10

15

20

Valu

e(m

/s)



54

図 3-5 Monthly average Daily wind speed cueve

２）Conditions of wind turbines

(1) Basic specification

Rated outpu 300kW

Hub height 41.5m

Rotor diameter 33m

Rated rotation 40.5rpm

Cut-in wind speed

3.0m/s

Cutout wind speed 25m/s

Survival wind speed

70m/s

Design life

20years

0 6 12 18 240

2

4

6

8

10Jan

0 6 12 18 240

2

4

6

8

10Feb

0 6 12 18 240

2

4

6

8

10Mar

0 6 12 18 240

2

4

6

8

10Apr

0 6 12 18 240

2

4

6

8

10May

0 6 12 18 240

2

4

6

8

10Jun

0 6 12 18 240

2

4

6

8

10Jul

0 6 12 18 240

2

4

6

8

10Aug

0 6 12 18 240

2

4

6

8

10Sep

0 6 12 18 240

2

4

6

8

10Oct

0 6 12 18 240

2

4

6

8

10Nov

0 6 12 18 240

2

4

6

8

10Dec

55

(2) Power curve of KWt300

KWT300 Power curve

measured and calculated in accordance with IEC 61400-12-1 (1st, 2005-12)

Air Density: 1,225 kg/m3

Power performance measurement is defined according to IEC61400-12.

Power: Ten munities average values at the grid connection point, normalized by the air density of 1225kg/m3

Wind speed: Ten minutes average values measured at the met mast located upwind in the dominant wind direction,

normalized by the air density of 1225kg/m3.

* Values over 21 m/s are only referential values.

1.7.2. Supply Demand Balance Simulation (Long term)

1.7.2.1. Kulhudhuffushi

(1) Simulation protocol

①Operation of diesel generators

・At least one diesel generator should be operated.

・The number of generators will be decided to minimize the fuel consumption.

・The maintenance period of diesel generators are not considered.

②Load curves

Load curves are filtered for the sake of the simulation. The future increase in demand is not

considered.

・Blackout and data loss was replaced with nearby data.

・Three hour averaging was done to eliminated the irregular events.

56

［average load 1224kW, peak load 2044kW, min load 693kW］

Original Load Curve of the year

↓

［average load 1224kW, peak load 1928kW, min load 741kW］

Filtered load curve of the year


500

1,000

1,500

2,000

2,500

Po

wer

(kW

)


500

1,000

1,500

2,000

2,500

Po

wer

(kW

)

57

(2) Simulation Result in Kulhudhuffushi

Simulation result of One wind turbine, Two wind turbines and Three wind turbines

respectively.

As the number increases, the wind turbines total output and excess energy increases, but will

not exceed the total demand.

Output of the year with ONE WT

Output of the year with TWO WT


500

1,000

1,500

2,000

Po

wer

(kW

)

AC Primary LoadKWT300_Excess Electricity


500

1,000

1,500

2,000

Po

wer

(kW

)


58

Output of the year with THREE WT

The total percentage of the time when a single wind turbine reaches the 300kW output is 0.1%

of the year, more than 200kWis 4.9% , and more that 100kW is 19.2%.

[Average output 51.8kW,Max output 300kW,Annual generation 1,360,325 kWh]

Annual wind turbine output duration curve （ONE unit）

[Average output 103.6kW, Max output 600kW, Annual generation 906,888 kWh]

Annual wind turbine output duration curve （Two Units）


500

1,000

1,500

2,000P

ow

er

(kW

)AC Primary LoadKWT300_Excess Electricity

0 2,000 4,000 6,000 8,0000

200

400

600

800

1,000

Valu

e(k

W)

KWT300_ Power Output Duration Curve


0 2,000 4,000 6,000 8,0000

200

400

600

800

1,000

Valu

e(k

W)



59

[Average output155.3kW,Max output900kW,Annual generation453,444 kWh]

Annual wind turbine output duration curve （Three Units）

Excess supply from wind turbines are illustrated below charts for the cases of One units to three

units of KWT300.

The max excess supply for one unit and two units cases is 20.6kW, and that for the three unit

case is 232.4kW.

[Average output0.3kW,Max output20.6kW,Annual surplus electricity generation10,464 kWh]

Annual excess supply duration curve（ONE unit case）

0 2,000 4,000 6,000 8,0000

200

400

600

800

1,000

Valu

e(k

W)



0 2,000 4,000 6,000 8,0000

50

100

150

200

250

Valu

e(k

W)

Excess Electrical Production Duration Curve


60

[Average output0.4kW, Max output20.6kW, Annual surplus electricity generation3,156 kWh]

Annual excess supply duration curve（TWO units case）

[Average output1.2kW,Max output232.4kW,Annual surplus electricity generation2,608 kWh]

Annual excess supply duration curve（Three units case）

0 2,000 4,000 6,000 8,0000

50

100

150

200

250V

alu

e(k

W)



0 2,000 4,000 6,000 8,0000

50

100

150

200

250

Valu

e(k

W)



61

(3) Recommended System

The issue of excess supply from wind turbines can be solved by limiting wind turbine output,

battery storage or demand control of large electric consumers.

From the below analysis,①Fixed power limitation is recommended since it does not require

extra cost and the loss of energy is not significant.

①Fixed power limitation cases

For one and two units cases, wind turbine’s max output is fixed to 250kW.

For three units case, wind turbine’s max output is fixed to 200kW.

For these fixed output cases, no extra system is required.

cases

Electricity

demand

[kWh]

Wind energy

generation

[kWh]

limited units

[kWh]

Net units

from WTs

[kWh]

Wind

penetration

rate

Capacity

factor of

WTs

One unit 10,723,797 453,444 3,484 449,960 4.2% 17.1%

Two units 10,723,797 906,888 6,967 899,921 8.4% 17.1%

Three

units

10,723,797 1,360,325 52,489 1,307,836 12.2% 16.6%

（For the WT 3 units case, if total output from three units can be limited to 650k, the capacity factor

will be higher.）

②Auto power limitation cases

To have the best possible capacity factor of WTs,（17.3% if no limitation）, wind turbine output

will be controlled when there will be excess electricity.

cases

Electricity

demand

[kWh]

Wind energy

generation

[kWh]

limited units

[kWh]

Net units

from WTs

[kWh]

Wind

penetration

rate

Capacity

factor of

WTs

One unit 10,723,797 453,444 2,608 450,836 4.2% 17.2%

Two units 10,723,797 906,888 3,156 903,732 8.4% 17.2%

Three

units

10,723,797 1,360,325 10,464 1,349,861 12.6% 17.1%

③Battery storage cases

For these cases, lead battery storage system will be installed.

cases

Electricity

demand

[kWh]

Wind energy

generation

[kWh]

Loss from

storage

[kWh]

Net units

from WTs

[kWh]

Wind

penetration

rate

Capacity

factor of

WTs

One unit 10,723,797 453,444 391 453,053 4.2% 17.2%

Two units 10,723,797 906,888 473 906,415 8.5% 17.2%

62

Three

units

10,723,797 1,360,325 1,570 1,358,755 12.7% 17.2%

（ Battery capacity will be WT1unit: 50kW-150kWh, WT2units: 100kW-300kWh,WT3units

300kW-900kWh）

④Demand control of large electricity user

In Kulhudhuffushi, the water desalination plant is in operation from from 8am to 5pm, which

requires around 50kW electricity. It can be controlled to reduce the excess demand, however, the

above systems 1 -3 are enough to control the grid system, thus the use of desalination plant was

not considered.

1.7.2.2. Naifaru

(1) Simulation protocol

①Operation of diesel generators

・At least one diesel generator should be operated.

・The number of generators will be decided to minimize the fuel consumption.

・The maintenance period of diesel generators are not considered.

②Load curves

Load curves are filtered for the sake of the simulation. The future increase in demand is not

considered.

・Blackout and data loss was replaced with nearby data.

・Three hour averaging was done to eliminated the irregular events.

［Average load 594kW, Max load 875kW,Min load 168W］

Original annual load curve

↓


200

400

600

800

1,000

Po

wer

(kW

)

63

［Average load 597kW,Max load 842kW,Min load 353W］

Load curve after filtering


200

400

600

800

1,000

Po

wer

(kW

)

64

(2) Simulation result

Simulation result of One wind turbine, Two wind turbines and Three wind turbines

respectively.

As the number increases, the wind turbines total output and excess energy increases. For two

units case, there are some times wind turbine output exceeds the grid demand, and for the three

units case, the frequency of such excess is significant.

Output of the year with One WT

Output of the year with Two WT


200

400

600

800

1,000

Po

wer

(kW

)



200

400

600

800

1,000

Po

wer

(kW

)


65

Output of the year with THREE WT

Below is the output tendency of wind turbines from one units to thre units cases.

The percentage of the time when a single wind turbine reaches 300kW output is 0.1%, larger

than 200kW is 4.9%, and larger than 100kW is 19.2%.

[Average output51.8kW, Max output300kW,Annual generation1,360,325 kWh]

Annual wind turbine output duration curve （For One unit case）

[Average output103.6kW,Max output600kW,Annual generation906,888 kWh]


200

400

600

800

1,000P

ow

er

(kW

)AC Primary LoadKWT300_Excess Electricity

0 2,000 4,000 6,000 8,0000

200

400

600

800

1,000

Valu

e(k

W)



0 2,000 4,000 6,000 8,0000

200

400

600

800

1,000

Valu

e(k

W)



66

Annual wind turbine output duration curve （For two units case）

[Average output155.3kW, Max output900kW, Annual generation 453,444 kWh]

Annual wind turbine output duration curve （For three units case ）

Excess energy from wind turbines are described below, for the one WT to three WT cases.

The max excess demand for One unit case is 94.8kW, 372.6kW for Two units case and 551.0kW

for Three units case.

[Average output0.3kW,Max output94.8kW]

Annual excess supply duration curve（For One unit）

0 2,000 4,000 6,000 8,0000

200

400

600

800

1,000

Valu

e(k

W)



0 2,000 4,000 6,000 8,0000

100

200

300

400

500

Valu

e(k

W)



67


Annual excess supply duration curve（For Two units）


Annual excess supply duration curve（For Three units）

0 2,000 4,000 6,000 8,0000

100

200

300

400

500V

alu

e(k

W)



0 2,000 4,000 6,000 8,0000

100

200

300

400

500

Valu

e(k

W)



68

(3) Recommended System

The issue of excess supply from wind turbines can be solved by limiting wind turbine output,

battery storage or demand control of large electric consumers.

From the below analysis, ① Fixed power limitation or ② Auto power limitation is

recommended since it does not require extra cost and the loss of energy is not significant.

Since the energy surplus will be large for three units case, it is not recommended.

①Fixed power limitation case

Max output is limited to 200kW for One unit case, 250kW for two units case, and 350kW for

three units case.

case

Electricity

demand

[kWh]

Wind energy

generation

[kWh]

limited units

[kWh]

Net units

from WTs

[kWh]

Wind

penetration

rate

Capacity

factor of

WTs

One unit 5,233,528 453,444 17,496 435,948 8.3% 16.6%

Two units 5,233,528 906,888 149,701 757,187 14.5% 14.4%

Three

units

5,233,528 1,360,325 257,207 1,103,118 21.1% 14.0%

②Auto power limitation case

To have the best possible capacity factor of WTs,（17.3% if no limitation）, wind turbine output

will be controlled when there will be excess electricity.

case

Electricity

demand

[kWh]

Wind energy

generation

[kWh]

limited units

[kWh]

Net units

from WTs

[kWh]

Wind

penetration

rate

Capacity

factor of

WTs

One unit 5,233,528 453,444 2,508 450,936 8.6% 17.2%

Two units 5,233,528 906,888 82,542 824,346 15.8% 15.7%

Three

units

5,233,528 1,360,325 268,362 1,091,963 20.9% 13.9%

③安定化蓄電池装置の場合

For these cases, lead battery storage system will be installed.

case

Electricity

demand

[kWh]

Wind energy

generation

[kWh]

Battery loss

[kWh]

Net units

from WTs

[kWh]

Wind

penetration

rate

Capacity

factor of

WTs

One unit 5,233,528 453,444 376 453,068 8.7% 17.2%

Two units 5,233,528 906,888 12,381 894,507 17.1% 17.0%

Three

units

5,233,528 1,360,325 40,254 1,320,071 25.2% 16.7%

69

（Battery capacity should be 100kW-300kWh for WT 1 unit case, 400kW-1200kWh for WT 2 units

case and 600kW-1800kWh for WT3 units case.）

④Demand control

No facility of large enough demand to be controlled is yet to available in Nafaru.

1.7.3. Control of short term output fluctuation

The long term output fluctuation can be handled by the means described in the previous sections,

however, the short term output fluctuation over a few seconds and minuts must be considered as

well. To judge its influence, the response speed of diesel generators are inspected with the load

shut tests at power houses of Kulhudhuffushi and Naifaru.

1.7.3.1. Load dump test（Kulhudhuffushi）

(1)Outline of the test

Test schedule Diesel generators status

(2) Test result

KulhudhuffshiLoad dump test record

generator statuskW

On then off-On

On

Frequency

Frequency

70

KulhudhuffshiLoad dump test record

(3) Analysis

Frequency is changed by switched off the Gen1.

However, due to the limitation of the generators capacity, it is difficult to determine the drid

performance factor.

1.7.3.2. Load dump test（Naifaru）

(1 )Test condition

Test schedule Generators status

(2) Test record

Frequency

Frequency

generator statuskW

OnOn then off

-

-

71

Naifaru Load dump test Record

図 5-4 NaifaruLoad dump test Test

(3) Analysis

The change in frequency is recorded but it was only 0.1Hz and negligible. It is difficult to judge

the grid response factor.

Frequency

Frequency

Frequency

Frequency

72

【Result from the past study】

With the result of Load dump tests in Kulhudhuffushi and Naifaru, it is difficult to judge the

grid response factor, however, the past test result in Eydaffushi, could be a good reference to these

two islands since the diesel generators type is the same with electricity governor with 1500 rpm.

This high speed diesel generators are usually considered to have good response speed .

From the test results of Eydafshi, it was judged that the special system for short term

fluctuation is not necessary if the long term fluctuation control is taken.

If the operator decided to take measures to short term fluctuation, it is recommended to adopt

battery systems of high output and low storage capacity, such as capacitors（EDLC）,Lithium ion

capacitor（LiC）,Flywheel battery（FWG.

The capacity of these should be 1/2-2/3 of the total capacity of wind turbines.

1.7.4. Proposed System design

1.7.4.1. Kulhudhuffushi

In Kulhudhuffushi, the wind penetration rate will be 4.2%, 8.4% and 12.2% for one , two and

three wind turbines case, for the fixed power limitation system.

Even with three wind turbines, the surplus electricity amount is not significant. The fixed

limitation system with the limit of total wind power station as 650kW is the best recommendation.

To decrease the energy loss, auto power limitation could be attached. For this case, the capacity

factor will be 17.1%, compared to the 16.6% without auto system.

For a security, a capacitor of PCS500kW-EDLC/LiC25kWh is recommended to handle the short

term fluctuation.

The cost of auto power limitation shall be USD 0.4 million, and the cost of the battery system

will be USD0.6 million.

[Fixed power limitation with three wind turbines ]

windturbinesKWT300

200kWfixed

windturbinesKWT300

200kWfixed

windturbinesKWT300

200kWFixed

existingpower house

DEGGEN1-4

Demand

SCADA

Batteryfor short

term

PCS500kWEDLC/LiC25kWh

if necessary

monitoring, start, stop, output

control

extra cost：NoneCapacity factor：16.6 %

Penetration rate ：12.2 %

73

[Auto power limitation]

1.7.4.2. Naifaru

In Naifaru, Wind penetration rate will be 8.3%, 14.5% and 21.1% for one, two , three units for

the fixed power limitation system.

For the one unit case, the surplus energy amount is not significant, thus fixed system is

recommended.

For the two units case, as the capacity factor will decrease from 17.3% to 14.4% with the fixed

power limitation system, auto power limitation system is preferable which can increase the

capacity factor up to 15.7%.

To avoid further energy loss, batteries can be installed, PCS400kW lead battery with 1200kWh

capacity. Then the capacity factor increases to 17.0%. The cost for the battery system is USD 1M.

Only for the short term fluctuation purpose, PCS500kW-EDLC/LiC25kWh is recommended.

The cost of auto power limitation shall be USD 0.4 million, and the cost of the battery system

will be USD0.6 million. For the battery system for long term fluctuation, the system cost will bel

USD 1M.

windturbinesKWT300

300kW

windturbinesKWT300

300kW

windturbinesKWT300

300kW

existingpower house

DEGGEN1-4

Demand

SCADA

短周期変動対策用蓄電装置


if necessary

Controlpanel

DEG output

order

monitoring, start, stop,

output control

extra cost：USD0.4 MCapacity factor：17.1 %


74

Case１：Two units＋Auto output control

[Auto power limitation]

Case2： One unit＋Fixed output

[Fixed power limitation]

windturbinesKWT300

300kW

windturbinesKWT300

300kW

existingpower house

DEGGEN1-4

Demand

SCADA

Batteryfor short

term


if necessary

Control panel

DEG 出力

command


output control

windturbinesKWT300200kWFixed

existingpower house

DEGGEN1-4

Demand

SCADA

Batteryfor short

term


if necessary


output control

extra cost：USD0.4MCapacity factor：15.7 %


extra cost：NoneCapacity factor：16.6 %

Penetration rate ： 8.3 %

75

Case 3： Two units＋Auto limitation ＋Battery

[Auto power limitation with battery for long term]

1.7.5. Self-control system of wind turbines

In the place of auto limitation system recommended in the previous sections, it is possible to take

the advantage of the self-control system of the wind turbine. With these, the extra cost of

communication lines and the control panels for the auto limitation system, while the wind turbines

system detects the frequency change by themselves and reduce the output/

The convertor of the wind turbine has the function called, SSL control ( Phase Lock Loop) to

control the frequency and phases.

With this function, for example, when the grid power demand is small and the wind turbine power

output increases, and thus the grid frequency increases, the wind turbine convertor detects the

frequency rise and control the wind turbine output by sending a signal. Therefore, a command from

the power house is not required.

For this system, only a slight program change is needed, and no need for the without

communication lines and control equipment for automatic control, thus extra cost is practically zero.

This system is under development and will be in use in one year time.

windturbinesKWT300

300kW

windturbinesKWT300

300kW

existingpower house

DEGGEN1-4

Demand

SCADA

Batteryfor long

term

PCS400kW-Lead battery 1200kWh

Controlpanel

DEG outpu

Commandmonitoring, start, stop,

output control

extra cost：USD 1MCapacity factor：17.0 %


command

76

1.8. Evaluaton of the project economy

1.8.1. Outline of the proposed project

Island Location Unit system Annual WT generation

Penetration rate

(for average wind speed

at 5.48m/s)

Kulhudhuffushi South of island

Next to power house

and port

2 300kWwind turbines

＋ Output limitation

system

903,732kWh

8.4%

Naifaru North of island

Next to power house

2 300kWwind turbines


system

824,326kWh

15.8%

GulhiFalhu MWCS premises 1 300kWwind turbines


system

451,866kWh

―

Total Capacity ： 300kW×5 = 1500kW

1.8.2. Project cost (rough estimate)

The project cost was roughly estimated as below for FIVE unites of wind turbines installation in

island of the Maldives.

Total cost for five units 7,683 thousand USD

WT generation system 3,750 thousand USD

Grid connection facilities and works 1,000 thousand USD

Transportation and construction 1,550 thousand USD

Foundation works 750 thousand USD

Design services 90 thousand USD

Studies 20 thousand USD

Overhead fee, temporary facilities 523 thousand USD

others 0 thousand USD

Especially foundation construction cost needs more detailed analysis with soil investigation result at

each site.

77

1.8.3. Analysis of Project economy

Twenty years project economy is analyzed, for the case of annual average wind speed of 5.38m/s

and 6.0m/s, and for the case of subsidy rate of 50%, 30% and 0%, for the total of 6 cases.

As a result, even for the worst case with lower wind speed and no subsidy, the pay back years is 15

years.

＜Pre-conditions＞

item assumtions note

Project size 300kW×5 units Total of three islands

annual average wind speed case１ case2

5.38m/s 6.0m/s

case1 is the Eydafushi value

case2 is an assumption

Annual supply from WTs

Kulhudhuffushi

Naifaru

Gulhifalhu

Total：2,181,522kWh

903,732kWh

824,346kWh

453,444kWh

Surplus energy is not counted

2 units with auto control

2 units with auto control

One unit, no surplus

Total project cost USD 7,683,000

Subsidy rate caseA：50％

caseB：30%

caseC：0%

Subsidy rate for the initial

investment

Interest rate 5% Initial cost not covered by sublidy

will be covered by Borrowing.

Saved cost per unit by WT

generation

0.4USD/kWh (First year) Annual increase rate of 2%

Total saving in fuel

payment

USD872,609 First year

annual average

maintenance fee

USD132,100（first year） 10 % increase for every five years

Insurance premium USD2,000（First year） 1 % decrease for every year

Tax Not considered

＜Simulation result＞

annual

average wind

speed

Subsidy

rate

Unit cost for wind

turbine generation

Pay back years Project IRR

case１－A 5.38m/s 50% 0.227USD/kWh 8 14.6％

78

case１－B 5.38m/s 30% 0.267USD/kWh 11 9.2％

case１－C 5.38m/s 0% 0.342USD/kWh 15 4.5％

case２－A 6.0m/s 50% 0.273USD/KWh 6 21.6%

case２－B 6.0m/s 30% 0.213USD/kWh 8 14.7％

case２－C 6.0m/s 0% 0.273USD/KWh 11 8.9%

Unit cost for wind turbine generation ＝（initial investment ＋maintenance fee＋interests）÷ total generaion

1.9. Implementation Framework

1.9.1. Implementation Framework

In general, wind energy projects are managed either by utility company as one of the generation

facilities or private independent power producer as an investment. In micro-grid areas, like in the

Maldives, the existing utilities such as FENAKA, STELCO, MWSC in the Maldives, can enjoy the

most benefit from wind energy project by .

Utilities IPPs

How to use electricity Used in their own grid Sell electricity to the utility

Merit of wind turbine

generation

Wind turbine generation = fuel cost

savings

Power purchase and tariff

agreement is required

Micro-grid control To keep the grid electricity quality,

utility can control wind turbine output.

System design and operation

synchronizing diesel generator and

wind turbines is possible.

Output limitation of wind turbines

should be avoided to avoid the

revenue loss. If the utility has the

right to limit, it will be regarded as

the risk in the project.

No incentives to consider diesel

generator operation.

maintenance Engineers in power house can be

trained to maintain the wind turbines.

Prompt action is possible by inland

engineers.

Special maintenance staff should be

trained. If the maintenance staff

stays inland, the operational cost

will increase.

Finance Limitation of state owned company for

borrowings.

Freely get funds in the market.

Judging from the above comparison, it is strongly recommended for the utility company to be a own

wind energy project.

79

JCM Implementation framework

1.9.2. Financing arrangemnt

Here are possible funding resources.

（１）SREP Investment Plan budget

After getting the wind data of islands, it is required to discuss with ADB for the possible allocation

of SREP budget for wind energy project, which is included in the plan as well.

（２）JBIC finance

JBIC has a program to facilitate JCM

implementation under their export financing scheme.

State own companies such as FENAKA or STELCO

can directly borrow from JBIC or they can utilize the

credit line of JBIC and ICIC bank of India .

JBIC can finance up to 50 or 60 percent of the project

cost, thus it could be a good match up with the initial

subsidy.

1.10. Timeline for implementaion

The wind monitoring will be continued till the end of December.

After the analysis of one year wind data, the final project economy will be decided.

The operation star will be in 2016 at the earliest.

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1.11. Other potencial sites in the Maldives

Here is the list of other potential sites other than three islands mentioned above.

islands unit

FENAKA Eydafushi

Hinnavaru

One each

STELCO Maafushi

Himmafushi

Two

One

MWSC Dhuvaafaru One

Industrial islands Felivaru One or two

Resort islands 10-20 for total

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2. Policy recommendation

2.1. Setting technical requirements for wind turbines

For a JCM project, it is also one of its purpose to spread the superior technology of Japan to the

world. Although, in the market of renewable low-cost systems from the emerging countries are

increasing its share, for a wind energy project where the initial investment is large which must be

paid back by the fuel cost savings of each year, the reliability of the system, little failure as possible,

become very important to maintain the project economy.

In particular, in the small-grid system of the island, etc., the system design based on the premise of

fluctuating renewable energy output is essential. Thus, if the project owner selects a model only

considering the price, the influence of the wind turbines to the grid system will not be analyzed,

which lead to the malfunction of the wind turbines as well as causing damage to the power

generation systems and electric power system, such as existing diesel generator as a result.

It is highly recommended to set the technical requirements to wind turbines described below to be

installed in Maldives to facilitate reliable system.

・ To have International Certification： Wind turbine system must been certified by

international crediting bodies such as Germanisher Lloyd or TUV.

・ To maintain output control system： Wind turbine system must have control system to

limit the output by commands or by programming etc.

・ Remote monitoring and control ： Wind turbine system must have SCADA remote

monitoring and remote control.

Remote monitoring system portal

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2.2. FIT reflecting the real generation cost of islands

At this moment, the Maldivian government maintains the Feed In Tariff which set the tariff

according to the regions from USD 0.22/ kWh to USD 0.35/kWh regardless of the source of energy.

On the other hand, the actual cost for generation with diesel generators is higher than FIT tariff.

This lead to the situation where STELCO buys Solar generated electricity from the IPP,

Renewable Energy Maldives Co. Ltd., at the price higher than FIT price, since the actual cost of

energy generation is much higher than FIT price.

In the Maldives, FIT tariff should be set between the cost of diesel generated electricity and the

cost of wind generated electricity.

In setting the tariff, the below items should be considered, and the FIT should be different

depending on the cost of renewable sources, which varies with source of generation, project capacity,

and the location.

１）Source of energy

２）Size of project

３）Location of the project

1) Source of Energy: In general, solar generated power is more expensive than wind generated

power and the cost of biomass power generation power varies a lot among cases. There is a need to

set the price in consideration of the construction costs of each generation type in the Maldives.

2) Size of project: The power generation unit price decreases as the plant scale gets larger, and

increases as the plant scale gets smaller. In very densely inhabited places as the Maldives, the land

area available for renewable power generation is very limited, and the large-scale equipment is very

difficult to be located. Therefore, there is also a need to introduce a large number of small-scale

power generation projects , with which the unit price is higher than large scale single project..

3) Location of the project: In the Maldives, generation cost is higher in smaller islands than larger

islands. The FIT tariff should be set so as to facilitate the renewable energy production if the

generation cost is lower than the existing diesel generated electricity of the planned island. Not to be

judged by the market price.

2.3. Interconnection of islands for increasing penetration rate

All Maldivian islands except for Addu City maintain independent grid system in each island. On

the other hand, the distance between the island and the island is often less than 1km.

If the grid systems are interconnected between nearby islands, grid capacity expands, which

means that the room for installing renewable energy will also increase, also more effectively and

efficiently. Thus, as part of the infrastructure development of renewable energy introduction, the

Government should take initiatives for grid system interconnection between the islands.

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2.4. Action plan for wind power projects with mid-size wind turbines

In the mainstream wind energy market, large wind turbines (MW machine) are prevailing, while

these are unsuitable for the island of very small scales in the Maldives. Because of the fact that the

wind speed is not so high in Maldives, it seems that the Maldives government and the power

companies have not considered the wind energy project seriously until now.

However, with 300kW wind turbines proposed here, wind energy projects are viable in the Maldives

as well, compared to the very high cost of diesel power generation. The cost reduction by the

introduction of wind power generation is significant even with the lower wind speed in the Maldives.

Throughout this study, such proposals have been recognized by the Maldivian authorities.

84

3. MRV Methodology

Outline of methodology developed is presented below.

3.1. Eligibility criteria

This methodology is applicable to projects that satisfy all of the following criteria. If there is

multiple project sites included in a JCM project, all project sites need to satisfy all the criteria.

Criterion 1 The project shall be the installation of a new wind turbine generator.

Criterion 2 The electricity generated by the project replaces fossil fuel based electricity

generation in the mini-grid under 15MW or electricity generation by diesel based

captive power plant

Criterion 3 The wind turbine system shall be equipped with remote monitoring system that is

connected to a computer system of a single entity responsible for monitoring of all

systems installed by the project.

Criterion 4 The wind turbine generator system installed in the project measures net electricity

supplied.

Criterion 5 The wind turbine systems shall be equipped with an inductive generator and

AC-DC-AC link converter as well as be able to limit the output power by signals

and to control reactive power, to secure the system reliability and smooth output in

vulnerable and low capacity grid.

Criterion 6 The wind turbine generator systems should have obtained a certification of design

type issued by internationally recognized assessment body. (i.e.Germanischer

Lloyd)

3.2. GHG emission sources

In this methodology, the only GHG emission sources are CO2 emissions from electricity generation by diesel

generator system in reference emissions.

Reference emissions

Emission sources GHG types

CO2 emissions from electricity generation by diesel generator system. CO2

Project emissions


n/a n/a

85

3.3. Establishment of reference emissions

Reference scenario is displacement of diesel based electricity generation by renewable electricity generated by the

project. Reference emissions are calculated as a product of the amount of net electricity generated by the wind

turbine system installed under the project activity and CO2 emission factor of diesel electricity generation system

otherwise operated.

Emission factor is fixed ex-ante as 0.7tCO2/MWh. The detail on how 0.7tCO2/MWh has been determined is

provided in the following section.

3.4. Emissions from existing diesel generation

For two potential project sites, historical data of electricity supply (electricity generation and fuel consumption)

were obtained from respective power operating companies. Based on these data, emission factor per kWh of power

generation was calculated.

=

Fuel

consumptionx NCV / 1,000,000 x

Emission factor

of fuel/

Electricity

generated

(kg/y) (TJ/Gg) (kg/Gg) (kgCO2/TJ) (kWh)

= Emission factor

（kgCO2/kWh）

Parameter Value Unit Source

Diesel density 0.8439 kg/litre IEA

Diesel NCV 41.1 TJ/Gg IPCC (Lower value)

Diesel EF 72600 kgCO2/TJ IPCC (Lower value)

Below summarize the CO2 emission factor calculated using original historical data of electricity supply (electricity

generation and fuel consumption) from two sites.

Kulhudhuffushi Powerhouse

Electricity

generation（kWh）

Diesel consumption

（litre)

CO2 Emission factor

（kWh/CO2kg)

2012 8,766,336 2,474,269 0.7107

2013 9,087,079 2,682,389 0.7433

86

20142 9,012,363.00 2,595,371 0.7252

Naifaru Powerhouse

Electricity

generation（kWh）

Diesel consumption

（litre)

CO2 Emission factor

（kWh/CO2kg)

2013 3,855,239 1,080,538 0.7058

20143 3,743,741 1,062,997 0.7150

The CO2 emission factor calculated are lower than the default value of 0.8kgCO2-e/kWh allowed to apply in the

CDM methodology AMS I.A allows. Therefore, adopting the CO2 emission factor value calculated in this

methodology as default emission factor lead to more conservative approach for reference emissions calculation.

It is suggested to select the lowest CO2 emission factor and round down to one decimal place. Emission factor for

both Kulhudhuffushi and Naifaru will be 0.7kgCO2-e/kWh.

3.5. Calculation of reference emissions

ydieselCOyREFy EFEGRE ,,2,

Parameter Description

REy Reference emissions in year y (tCO2/year)

EGREF,y Amount of net electricity supplied by the project (MWh/y)

EFCO2,diesel,y Emission factor of the electricity displaced by the project (tCO2/MWh)

3.6. Calculation of project emissions

0yPE

There is a very small amount of electricity demand for standby electricity consumption in the wind power

generation. The same meter measures both the amount of electricity generated and electricity consumed for

standby purpose. The electricity consumed standby purpose is counted by deducting the amount of standby

electricity consumption from the about of electricity generated by the wind turbine. Therefore, separated

calculation of project emission due to consumption of standby electricity is not required and project emissions are

2 Does not include Dec 1, 2014 to December 31, 20143 Does not include Nov. 21, 2014 to Dec. 31, 2014.

87

zero (0).

3.7. Monitoring

Monitoring items, measurement method, and frequency are summarized below.

Parameter Measurement method Frequency

EGREF,y Amount of net

electricity supplied by

the project (MWh/y)

Option C Monitored by

electricity meter

Continuously monitored

and accumulated at least

monthly

4. Calculation of GHG emission reductions

Using this methodology, GHG emission reductions from the project is estimated as follows.

ERy = REy

Description of dataERy GHG emissions reduction during the year y（tCO2/year）REy Reference emissions during the year y（tCO2/year）

Below summarize the value and basis of the values applied for calculation of GHG emission reduction.

Item Value Basis Unit

Estimated annual power generation 2,1825 units of 300kW wind turbinesamong 3 islands. Total generationbased on the simulation result.

MWh/year

Emission factor of the dieselelectricity displaced by the project.

0.7 Determined in the methodology tCO2/MWh

Emission reductions will be calculated as follows.

（Reference emissions）


=2,182 (MWh/year) × 0.7 (t-CO2/MWh)

= 1,527.4≒ 1,527 (t-CO2/year)

88

（Emission reductions）

ERy = REy

= 1,527 (t-CO2/year)

Emission reduction from the project is calculated as 1,527t-CO2/year.

89

JCM Proposed Methodology Form

Cover sheet of the Proposed Methodology Form

Form for submitting the proposed methodology

Host Country Maldives

Name of the methodology proponents

submitting this form

Komai Haltec Inc.

Mitsubishi UFJ Morgan Stanley Securities,

Co., Ltd.

Sectoral scope(s) to which the Proposed

Methodology applies

1. Energy Industries

Title of the proposed methodology, and

version number

Renewable electricity generation from wind

turbine generator system in Maldives

List of documents to be attached to this

form (please check):

The attached draft JCM-PDD:

Additional information

Date of completion March 9, 2015

History of the proposed methodology

Version Date Contents revised

n/a n/a n/a

90

A. Title of the methodology

Renewable electricity generation from wind turbine generator system in Maldives

B. Terms and definitions

Terms Definitions

Remote monitoring system SCADA（Supervisory Control And Data Acquisition）

system to monitor operational condition and operating

record to operational performance of the turbine

generator. SCADA system analyzes the data and

transfers them to the main system via internet and/or

mobile networks.

C. Summary of the methodology

Items Summary

GHG emission reduction

measures

Electricity is generated by wind turbine generator system in

place of operating diesel electricity generation system.

Calculation of reference

emissions

Reference emissions are calculated as a product of the

amount of net electricity generated by the wind turbine

system installed under the project activity and

CO2emission factor of diesel electricity generation system

otherwise operated.

Calculation of project

emissions

There is no project emission. The project system requires

small amount of standby electricity requirement. However,

here is consumption of non-wind turbine generated electricity

for this purpose, it will be monitored. Project emissions are

calculated as a product of the amount of diesel electricity

consumed and CO2 emission factor of diesel electricity

generation system.

Monitoring parameters - Amount of electricity generated by wind turbine generator

system

91

D. Eligibility criteria

This methodology is applicable to projects that satisfy all of the following criteria.

Criterion 1 The project shall be the installation of a new wind turbine generator.

Criterion 2 The electricity generated by the project replaces fossil fuel based

electricity generation in the mini-grid under 15MW or electricity

generation by diesel based captive power plant

Criterion 3 The wind turbine system shall be equipped with remote monitoring

system that is connected to a computer system of a single entity

responsible for monitoring of all systems installed by the project.

Criterion 4 The wind turbine generator system installed in the project measures net

electricity supplied.

Criterion 5 The wind turbine systems shall be equipped with an inductive generator

and AC-DC-AC link converter as well as be able to limit the output power

by signals and to control reactive power, to secure the system reliability

and smooth output in vulnerable and low capacity grid.

Criterion 6 The wind turbine generator systems should have obtained a certification

of design type issued by internationally recognized assessment body.

(i.e.Germanischer Lloyd)

E. Emission Sources and GHG types

Reference emissions


CO2 emissions from electricity generation by diesel generator

system.

CO2

Project emissions


n/a n/a

92

F. Establishment and calculation of reference emissions

F.1. Establishment of reference emissions

Reference scenario is displacement of diesel based electricity generation by renewable

electricity generated by the project.

Reference emissions are calculated as a product of the amount of net electricity

generated by the wind turbine system installed under the project activity and

CO2emission factor of diesel electricity generation system otherwise operated.

Emission factor is fixed ex-ante and presented in Section I of the methodology.

F.2. Calculation of reference emissions


Parameter Description

REy Reference emissions in year y (tCO2/year)

EGREF,y Amount of net electricity supplied by the project (MWh/y)

EFCO2,diesel,y Emission factor of the electricity displaced by the project

(tCO2/MWh)

G. Calculation of project emissions

Project emission is accounted in reference emissions calculation.

H. Calculation of emissions reductions

Emissions reductions are monitored reference emission.

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ERy = REy

ERy: CO2 Emission Reduction［tCO2/y］

REy : Reference CO2 emissions［tCO2/y］

I. Data and parameters fixed ex ante

The source of each data and parameter fixed ex ante is listed as below.

Parameter Description of data Source

EFCO2,diesel,y 0.7tCO2/MWh

Emission factor of the diesel electricity

displaced by the project.

Determined and fixed

ex-ante in the methodology

based on the historical

electricity generation and

fuel consumption data

supplied by relevant

Maldivian authority.

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