HUAQIANG CHEMICAL PROFILE - Npk compound fertilizer, Npk ...
131127 ENERTEAM_cao su, phân bón NPK và sơn(ENG)
Transcript of 131127 ENERTEAM_cao su, phân bón NPK và sơn(ENG)
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CLEAN PRODUCTION AND ENERGY EFFICIENCY
IN VIETNAMMOIT GEF
GEF Trust Fund Grant No: TF099859VN
Final Report on Assessmentof Energy Saving Potential of
RUBBER - NPK FERTILIZER and
PAINT MANUFACTURING INDUSTRY
Deliverable N
o
. 7Energy Efficiency Assessment of the Chemical Industry
Consulting Firm:
ENERGY CONSERVATION RESEARCH AND DEVELOPMENT CENTER
October 2013
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ACRONYMS AND ABBREVIATIONS
ADMP : Agriculture Development Master Plan up to 2020 looking at the horizon of 2030
CIDP : Draft of Chemical Industry Development Plan up to 2020 looking at the horizon of
2030
EnMS : Energy Management System
ESCO : Energy Service Company
FDI : Foreign Direct Investment
ISIC :International Standard Industrial Classification
MoIT : Ministry of Industry and Trade
PMU : Project Management Unit
SEC : Specific Energy1Consumption
TOE : Ton of Oil Equivalent
VINACHEM : Vietnam National Chemical Group
VSIC :Viet Nam Standard Industrial Classification
1Electricity is also energy (electric energy).
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LIST OF FIGURES
Figure 1: Benchmarking boundary ................................................................................................... 27
Figure 2: Possible saving solution in primary rubber processing industry ....................................... 28
Figure 3: Possible saving solution in NPK manufacturing industry .................................................. 28
Figure 4: Possible energy saving solution (apply high efficiency motor) in paint manufacturing
industry ............................................................................................................................................ 29
Figure 5: Distribution of surveyed factories by Output (pure latex equivalent) .............................. 33
Figure 6: Distribution of surveyed factories by age ......................................................................... 34
Figure 7: Processing scheme of product group 1 and 2 (SVR) ......................................................... 36
Figure 8: Share of electricity consumption ...................................................................................... 37
Figure 9: Specific electricity consumption of audited factories ....................................................... 37Figure 10: Specific electricity consumption of main process of product group 1 ............................ 38
Figure 11: Specific final thermal energy consumption in drying process of product group 1 ......... 39
Figure 12: Share of electricity consumption of the audited factories ............................................. 40
Figure 13: Specific electricity consumption of main process of product group 2 ............................ 40
Figure 14: Specific final thermal energy consumption in drying process of product group 2 ......... 41
Figure 15: Energy management rating ............................................................................................. 42
Figure 16: Energy management rating by item ................................................................................ 42
Figure 17: Specific electricity consumption of wastewater treating system by production............ 44
Figure 18: Specific electricity of waste water system by water consumption ................................. 45
Figure 19: Possible saving potential of electric solutions ................................................................ 47
Figure 20: Possible saving potential of thermal solutions ............................................................... 47
Figure 21: Saving potential v.s Payback period of possible solutions. ............................................. 48
Figure 22: Specific primary energy consumption by group ............................................................. 49
Figure 23: Specific primary energy consumption by factory age ..................................................... 49
Figure 24: relationship between load factor and specific primary energy consumption ................ 50
Figure 25: Relationship between SEC and energy management score ........................................... 50
Figure 26: Percentile graph of primary SEC in rubber group 1 production ..................................... 51
Figure 27: Tendentious relationship between primary SEC and production of product group 1 .... 51
Figure 28: Specific purchased energy consumption of group 1 products........................................ 52
Figure 29: Percentile graph of primary SEC in rubber group 2 products ......................................... 53
Figure 30: Tendentious relationship between primary SEC and production of product group 2 .... 53
Figure 31: Specific purchased energy consumption of group 2 products........................................ 54
Figure 32: Processing scheme of product group 3 (H.A.; L.A.) ......................................................... 55Figure 33: Primary SEC of product group 3 ..................................................................................... 56
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Figure 34: Processing scheme of product group 4 (RSS) .................................................................. 56
Figure 35: Specific primary SEC of product group 4 ......................................................................... 57
Figure 36: Possible sectorial primary energy saving potential ......................................................... 58
Figure 37: Best existing practice ...................................................................................................... 58
Figure 38: Moving the quartile average baselines ........................................................................... 59
Figure 39: moving the scale group average baselines ..................................................................... 60
Figure 40: Distribution of surveyed factories by Output (monocolor) ............................................ 64
Figure 41: Distribution of surveyed factories by age ....................................................................... 64
Figure 42: Manufacturing scheme of mono-color production ........................................................ 66
Figure 43: Specific electricity consumption by main process of NPK manufacturing ...................... 67
Figure 44: Specific electricity consumption by process with normalization .................................... 68
Figure 45: Share of electricity consumption by process .................................................................. 69
Figure 46: SEC for heating (granulating and drying) ........................................................................ 69
Figure 47: Energy management rating in NPK industry ................................................................... 70
Figure 48: Recirculation ratio ........................................................................................................... 72
Figure 49: Possible energy saving due to improving recirculation rate ........................................... 72
Figure 50: Possible electricity saving by applying high efficiency electric motor ............................ 73
Figure 51: Energy management rating ............................................................................................. 75
Figure 52: Energy management rating by item ................................................................................ 76
Figure 53: Saving cost v.s electricity price ........................................................................................ 77
Figure 54: Saving potential and cost ................................................................................................ 77
Figure 55: Saving solutions vs. Payback period ................................................................................ 78
Figure 56: Percentile graph of primary SEC in mono-color NPK industry ........................................ 79
Figure 57: Distribution of primary SEC in mono-color NPK production ........................................... 80
Figure 58: Specific purchased energy consumption of mono-color NPK ......................................... 80
Figure 59: Manufacturing scheme of tricolor NPK ........................................................................... 81
Figure 60: Primary SEC of tricolor NPK ............................................................................................. 82
Figure 61: Primary SEC vs. load factor.............................................................................................. 82
Figure 62: Primary SEC vs. factory age ............................................................................................. 83
Figure 63: Possible sectorial primary energy saving potential ......................................................... 84
Figure 64: Best existing practice. ..................................................................................................... 85
Figure 65: Moving the quartile group average baseline .................................................................. 86
Figure 66: moving the scale group average baselines ..................................................................... 87
Figure 67: Distribution of factories by age ....................................................................................... 91
Figure 68: Distribution of surveyed water-based factories by production ...................................... 92Figure 69: Distribution of surveyed solvent-based factories by production.................................... 92
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LIST OF TALBES
Table 1: Difference of chemical products grouping between CIDP and VSIC ................................. 14
Table 2: Number of chemical factories during the period from 2000 to 2010 ................................ 15
Table 3: Forecasted gross value output of Chemical industry ......................................................... 15
Table 4: Production value growth rate forecasting of chemical industry ........................................ 16
Table 5: Number of fertilizer factories by product type .................................................................. 16
Table 6: Number of basic chemical factories ................................................................................... 18
Table 7: Planned production of cleaning products .......................................................................... 19
Table 8: Planned paint production ................................................................................................... 20
Table 9: Number of listed factories .................................................................................................. 23
Table 10: Chemical product group considered by bonus method ................................................... 24
Table 11: Proposed priority order of industry selection .................................................................. 25
Table 12: Sub-sectorial saving potential .......................................................................................... 29
Table 13: SEC norm of VRG .............................................................................................................. 32
Table 14: List of selected factories for preliminary auditing ............................................................ 35
Table 15: Energy saving potential due to energy management improvement ............................... 43
Table 16: Investment cost for energy saving solutions .................................................................... 46
Table 17: List audited factories ........................................................................................................ 65
Table 18: energy saving potential due to energy management improvement ............................... 70
Table 19: Saving potential of VSD solution ...................................................................................... 74
Table 20: Saving cost of VSD solution .............................................................................................. 74
Table 21: List of paint manufacturing factories sending the feedbacks .......................................... 91
Table 22: Specific purchased energy consumption by process ........................................................ 95
Table 23: Relationship between grinding technology and specific electricity consumption ........... 96
Table 24: Saving cost of high efficient motor solution ..................................................................... 98
Table 25: Energy saving potential with energy management improvement ................................. 100Table 26: Moving average baselines of every scale group ............................................................. 107
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LIST OF ANNEX
Annex 1: Energy conversion factor ................................................................................................ 111
Annex 2: VSD price ......................................................................................................................... 112
Annex 3: Cost of electric motor ..................................................................................................... 115
Annex 4: Convert to pure latex equivalent .................................................................................... 116
Annex 5: Rubber- Saving potential of purchased energy by moving the average sectorial baseline.
........................................................................................................................................................ 117
Annex 6: Drying NPK in the North and the South .......................................................................... 119
Annex 7: Comparison of energy consumption when reduce 1% NPK humidity in drying process 121
Annex 8: NPK fertilizer - Calculation or energy saving potential due to reducing recirculation ratio
........................................................................................................................................................ 130
Annex 9: NPK fertilizer industry - Energy saving due to energy management improvement ....... 132
Annex 10: NPK fertilizer industry - Calculation of Sectorial purchased energy saving potential .. 133
Annex 11: Energy saving potential assessment by moving the average baseline of water based
paint ............................................................................................................................................... 134
Annex 12: Energy saving potential assessment by moving the average baseline of solvent based
paint ............................................................................................................................................... 135
Annex 13: Converting to solvent based paint equivalent .............................................................. 136
Annex 14: Planned paint production ............................................................................................. 137
Annex 15: Paint manufacturing industry - Sub-sectorial saving potential ..................................... 138
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PART A. GENERALITY
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1. EXECUTIVE SUMMARY
The main goal of the benchmarking activities in this assignment is to provide input for the
action plan with the elaboration of the international consultant. They can also provide
information for concerning agencies in order to set up feasible target(s) of sectorial
energy efficiency.
The benchmarking calculation is done with data collection during the questionnaire
survey. Some detailed information collected from preliminary onsite audits is also taken
into account during the benchmarking analysis. The benchmarking methodology
developed by the international consultant is the basis of this assignment but it is flexibly
adapted to the actual conditions along with his close advices.
The preliminary audit is done before the benchmarking analysis. Its main purposes are:
- To identify the factors used for extrapolating in the benchmarking analysis.
- To identify possible energy saving potentials as well as the best available
technology point in the sub-sectorial assessment.
- To calculate the investment cost of energy saving solutions
Since the consistency with both the preliminary audit and benchmarking activities, they
can be compiled together in sub-sectorial reports. Therefore, this document is the
combination of deliveries 2, 3, 6 and 7. Moreover, the assignment is done for three
different industries with different technologies, and, in fact, with different official
development master plans.
This report will be submitted to the Ministry of Industry and Trade, which will prepare
legal regulations, so numbers are presented in accordance with the official Vietnamese
format.
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2. SELECTION OF INDUSTRIES FOR BENCHMARKING
Since the time and resource limitations, whereas chemical is a vast industry, the
benchmarking is carried out for only three chemical industry sub-sectors. The
consideration for subsector selection is presented in the following parts.
2.1. CLASSIFICATION
There are two different classifications of chemical sub-sectors:
- Chemical Industry Development Plan (CIDP)
- Viet Nam Standard Industrial Classification (VSIC)
Chemical Industry Development Plan (CIDP)
The chemical manufacturing activities are administratively managed by the Ministry of
Industry and Trade (MoIT). Therefore, MoIT is responsible for preparing the Chemical
Industry Development Plan up to 2020 looking at the horizon of 2030 (CIDP) in orderto
submit to the Prime Minister for the approval.
The Plan covers the following chemical groups:
- Fertilizer
- Flora protection chemicals
- Petro chemicals
- Basic chemicals
- Electro-chemicals
- Industrial gases
- Rubber processing
- Cleaning products
- Paint and printing ink
- Pharmaceutical chemicals
Viet Nam Standard Industrial Classification (VSIC)
The VSIC 2007 was approved by the Decision No 10/2007/Q-TTg, dated 23/01/2007. It
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was built based on ISIC Rev.42, passed by United Nation Statistical Division in the meeting
organized in March 2006.
Chemical industry is classified into 20 as two first digits as presented in Annex 1.
However, the classification of VSIC in this document has some difference with that of the
VSIC as presented in Table 1.
2ISIC Rev.4: International Standard Industrial Classification Revision 4
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Table 1: Difference of chemical products grouping between CIDP and VSIC
CIDP
classification
VSIC 20
(Manufacture of chemicals and chemical
products)
Remark
Item ISIC
Fertilizer Manufacture of fertilizer and
nitrogen compounds
20120
Flora
protection
chemicals
Manufacture of pesticides and
other agrochemical products
20210
Petro-
chemicals
Manufacture of coke and
refined petroleum
Products (VSIC 19)
Basicchemicals
Manufacture of basic chemicals 20110
Electro
chemicals
Manufacture of electrical
equipment (VSIC 27)
Industrial
gases
Electricity, gas, steam and
air conditioning supply (VSIC
35)
Rubber
processing
Manufacture of rubber and
plastics products (VSIC 22)
Manufacture of rubber in primary
forms
20132
Cleaning
products
Manufacture of soap and
detergents, cleaning and polishing
preparations
20232
Paint and
printing ink
Manufacture of paints, varnishes
and similar coatings and mastics
20221
Manufacture of printing ink 20222
Pharmaceuti
cal chemicals
Manufacture of
pharmaceuticals, medicinal,
chemical and botanical
products (VSIC 21)
It is noted that the rubber in primary forms is covered by the Agriculture Development
Master Plan up to 2020 looking at the horizon of 2030 but not by the CIDP.
Regarding to the international practice, only products classified in the division
Manufacture of chemicals and chemical products in the VSIC (with 20 as the two first
digits) are put into consideration in this study (see Annex 1).
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2.2. STATUS
According to the CIDP, the number of chemical enterprises has been reduced from 1947
to 671 during 10 years, from 20002010.
Table 2: Number of chemical factories during the period from 2000 to 2010
YearNumber of
enterprisesState owned Non-state FDI
2010 671 90 396 185
2000 1.947 88 1.773 86
Increment -1.276 2 -1.377 99
Growth rate -66% 2% -78% 115%
Source: CIDP
As shown in Table 2, the gross number of chemical enterprises decreased by 66%.
However, the growth rate is not similar to each type. The figure of non-state enterprises
which are mostly small scale dramatically decreased, whereas that of FDI with large scale
ones has grown significantly at 115%. This is the reason, which can explain the average
growth rate of production value (fix price of 1994) is 16,7% per year during the period
from 2000 to 2010 (Source: CIDP). Looking at the Table 2, it can be understood as the
non-state enterprises take a quite small share whereas FDI ones take the biggest share in
the gross value output.
The forecasted gross value output of chemical industry is shown inTable 3.
Table 3: Forecasted gross value output of Chemical industry
Unit: Billion VND
2005 2006 2007 2008 2009 2010 2015 2020 2030
Low case 8.984 10.716 11.623 13.453 15.367 17.211 26.676 41.821 106.669
High case 42.679 50.570 60.166 68.970 77.315 97.228 197.995 411.635 1.592.170
Source: CIDP - (fix price of 1994)
As shown inTable 4,the forecasted growth rate of production value up to 2030 is around
15% per year. This can be explained that the production is almost double after every 5
years.
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Table 4: Production value growth rate forecasting of chemical industry
Period
2011 - 2015 2016 - 2020 2021 - 2030
Growth rate (%
per year)
Low case 9,16% 9,41% 9,82%
High case 15,28 15,76 14,48
Source: CIDP - (fix price of 1994)
2.3. CHEMICAL SUB-SECTORIAL REVIEW
The review of the following chemical industries is mainly done with available document,
such as sectorial (draft Chemical and Agriculture) development master plans and results
of previous project (DANIDA). Survey and audit results are not used in this part. They are
presented in next parts.
Fertilizer (VSIC 20120)
Fertilizer includes various products, such as urea, super phosphate, melting phosphate,
DAP, NPK and bio-organic.
Table 5: Number of fertilizer factories by product type
No Product Number of factories Total capacity Remark
1 Urea 5 3.220.000 t/y Up to 20153
2 Super phosphate 3 1.200.000 t/y ,,
3 Melting phosphate 3 1.100.000 t/y ,,
4 DAP 2 660.000 t/y ,,
5 NPK Few hundred 3.820.000 t/y -
6 Bio-organic - 400.000 t/y -
Source: CIDP
As presented in Table 5, NPK takes the most important role in fertilizer manufacturing
area. However, the CIPD does not present the list or number of factories.
Most of big companies are members or Fertilizer Association of Viet Nam (FAV).
3Planned total capacity at 2015
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product types are very various, so it is difficult to do sampling for surveying.
Basic chemicals (VSIC 20110)
Basic chemicals comprise quite large product types: caustic soda, acids, alum, chloral
products, etc.
Almost all factories produce few different products, such as caustic soda and Chlorine,
DAP and H2SO4, Copper and H2SO4, H2SO4 for making alum, H2SO4 for making ammonia
sulfate, etc.
The number of basic chemical factories in Viet Nam is very few, as shown in Table 6.
Table 6: Number of basic chemical factories
No Product Number of factories Capacity Remark
1 Caustic soda (NaOH)
And Chlorine (Cl2)
4 main factories and
some small ones
NaOH: 130.000 t/y
Cl2: N.A.
2 Sulfuric acid (H2SO4) 6 895.000 t/y
Source: CIDP
Most of factories produce sulfuric acid mainly for making other products in the same
corporation. Regarding the replication, little number of factories may not be suitable to
select for this project.
Rubber (VSIC 20132)
According to other parts of the CIDP, rubber group in this document includes only final
products (tires, air tubes, gloves, etc.), which is classified as VSIC 22. According to the first
survey done by the project team, up to 2013, there are 87 listed factories satisfying the
VSIC 20, rubber in primary forms. Therefore, surveys in this project will focus only on the
of rubber manufacturing chain.
Most of primary rubber factories are members of the Viet Nam Rubber Group. They are
also members of Viet Nam Rubber Association. Since the climate conditions, most of
rubber plantations are located in the South of Viet Nam. Primary rubber processing
factories are component of these plantations, so most of them are also located in the
South.
According to the ADMP, the total capacity of primary rubber plant up to 2020 will reach
to 1,2 million ton/year. Referring the norm of the Vietnam Rubber Group concerning
energy consumption for primary rubber processing:
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Decision no1294/Q-TTg
The selection consideration refers to the list of energy intensive enterprise as prescribed
in the Decision no 1294/Q-TTg6 . However, it is not very informative. It lists only nine
chemical concerning factories with different products:
- Van Dien: melting phosphate
- Son Viet Anh: various businesses, in which water based paint is the one of its
business.
- Minh Duc: chemical and food processing machines
- Lam Thao: super phosphate
- Chemical enterprise No21 of Ministry of Defense: explosive and fireworks
- Surint Omya Viet Nam: calcium carbonate and dolomite
- Construction Investment Join Stock Company No5: calcium carbide and ethylene
- Baconco: various crop care products
- Phuoc Hoa Rubber JSC: primary rubber product (SVR, etc.)
Thus, it is difficult to extract information from this Decision.
6
Decision no
1294/Q-TTg, dated 01/08/2011 of the Prime Minister: List of energy intensive enterprises of2011.
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2.4. SELECTION PROCESS FOR THE BENCHMARKING EXERCISE
Among six industries mentioned above, only 3 of them are selected to put into survey.
The selection is considered through the bonus method with the following criteria:
1) Covered by the Manufacture of chemicals and chemical products of VSIC as
symbolized by the Division 20 (two first digits):
o Yes : 1
o No : 0
2) Number of factories (at least, more than 10): the number of factories is taken into
account regarding the sample comparison. Moreover, this factor can show the
replicability of energy efficiency actions, therefore, it is weighted as 2, with theclassification is presented as follows:
o Less than 10 factories : 0
o 1015 factories : 1
o 1620 factories : 2
o 2125 factories : 3
o 2630 factories : 4
o More than 30 factories : 5
The CIDP presents several factories without listing. Regarding the reliability information
for carrying out surveys, the list of factories collected by the project team is put into
consideration.
The CIDP does not show the number of factories or companies, during the desk study,
through various sources, such as associations, corporations, previous projects, etc. The
number of listed factories is presented in Table 9.
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Table 9: Number of listed factories
No Group Number of factories Remark
1 NPK fertilizer 40
2 Rubber 87
3 Paint 88
4 Cleaning products 13 (Detergent)
5 Agro-chemical 17 Pesticide
6 Basic chemicals 15 Different products
7 Printing ink 17
3) Homogeny of product types (of sector): The more product types, the more
complicated in survey and less accuracy through theoretical calculations. It is
classified as follows:
o 1 main product type : 4
o 23 main product types : 3
o 4 - 5 main product types : 2
o More than 5 main product types : 1
4) Process complexity (in term of energy consumption) (accumulating): The complexity
of process can show the energy consumption level.
o Only mixing and packaging : 1
o Grinding : 1
o Granulating : 1
o Drying : 1
o More complex : 4
5) Have professional Association/corporation or equivalent: the energy action can bebetter replicated through these organizations.
o Yes : 1
o No : 0
Since the lack of energy information of some industries mentioned above, in order to
avoid the disadvantage of less energy information of industries (sub-sector) during the
consideration, this factor is not taken into account, but it is presented in part 3.
The selection consideration is presented inTable 10.
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Table 10: Chemical product group considered by bonus method
No Group
Criteria No
Sum1 2 3 4 5
Weight
1 2 1 1 1
1 Fertilizer
1.1 NPK 1 5 3 4 1 19
1.2 Super Phosphate 1 0 4 4 1 10
1.3 Melting phosphate 1 0 4 4 1 10
1.4 Urea 1 0 4 4 1 10
2 Rubber 1 5 4 3 1 19
3 Paint 1 5 3 1 15
4 Cleaning products 1 3 3 2 0 12
5 Agro-chemical 1 3 1 1 1 10
6 Printing ink 1 2 4 1 1 11
7 Basic chemical 1 1 1 4 1 9
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3. DATA PROCESSING
The benchmarking methodology is developed by the international consultant. After the
site visit in several selected factories and the discussion with the local consultants, the
international consultant has developed the draft benchmarking methodology, which is
well fitted in the actual conditions. Moreover, during the benchmarking exercise, the
close interaction between the international and local consultants has been done for
adapting to the unpredicted problems arising from the real situations.
Almost all factories are familiar with the purchased energy. However, the existing legal
document, such as the Decree no 21/2011/N-CP, Decision no 1294/Q-TTg and the
Guidance no3505/BCT-KHCN are prescribed in TOE. In order to maintain the coherence
between the benchmarking analysis and mentioned concerning legal document as well as
according the communication with the PMU, the benchmarking calculations are done
with primary energy. The primary energy unit is in TOE and its derivative, the kOE.
However, in order to make industries easier to understand, some results are presented in
purchased energy.
The purchased energies are energy types delivered at the hedge of factory, such as
electricity, oil, LPG, etc.
Gross heating values use in this report are taken from fuel specifications provided by the
PETROLIMEX7 for petroleum products (LPG, D.O., F.O.) and the Vietnamese standard
TCVN 1790 : 1999 for coal.
The conversion from purchased energy to primary energy follows the Guidance no
3505/BCT-KHCN of the Ministry of Industry and Trade, dated 19/April/2011.
Information, which lead to unreasonable of SEC (abnormally low or high), provided by
factories, is excluded from data processing.
Since the report is submitted to the Ministry of Industry and Trade of Viet Nam, the digits
are presented in Vietnamese format (xxx.xxx,xx).
7http://www.cng-vietnam.com/vi/san-pham/cng/bang-quy-doi.html
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Figure 2: Possible saving solution in primary rubber processing industry
Figure 3: Possible saving solution in NPK manufacturing industry
0
5
10
15
20
25
30
Firewood gasif. Replace surface aeration
by fine pore one
High eff. motor
Biogas recovery Apply VSD
Averagepayba
ckperiod
(Mon
th)
27 month
21 month
18 month15 month
13month
Saving potential
0
2
4
6
8
10
12
14
0% 2% 4% 6% 8% 10% 12% 14% 16% 18% 20% 22% 24% 26%
Improv. the recirc. ratio Recover heat from boiler for drying
Apply high effic. motor Apply VSD
Paybackperiod(Month
)
Saving potential (%)
Immediatly
11 months
11 months
12,5 months
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Figure 4: Possible energy saving solution (apply high efficiency motor) in paintmanufacturing industry
6. SUMMARY OF SUB-SECTORIAL SAVING
POTENTIAL
The saving potentials are presented in detail in every sub-sector report (annexes). Thissummary presents only results calculated by average baseline moving approach, which is
often considered and short term targets. Other assessment results done by different
approaches are presented in the detailed benchmarking parts.
Table 12: Sub-sectorial saving potential
Industry Saving potential
Primary Rubber industry 17%
NPK industry 15%
Paint manufacturing 31%
0
2
4
6
8
10
12
0.0% 0.5% 1.0% 1.5% 2.0% 2.5% 3.0%
Paybackperiod(month)
Saving potential (%)
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7. GENERAL CONCLUSION
As mentioned above, the three studied sub-sectors are the three different industries with
different technologies. This is the reason that the Government must issue different
development master plans:
Primary rubber Agriculture Development Master Plan up to 2020 looking at the
horizon of 2030 (ADMP) (Decision 124/QD0-TTg, 2/2/2012, of the
Prime Minister)
NPK industry Master plan of fertilizer production and distribution of the period
20112020, looking at the horizon of 2025 (Decision 6868/Q-BCT,
27/12/2010, Ministry of Industry and Trade)
Paint
manufacturing
Included in the Draft of Chemical Industry Development Plan up to
2020 looking at the horizon of 2030 (CIDP)
However, there are some common conclusions and recommendations:
- Since the difference in the three studied industries, it should be necessary to have
different action plans.
- Moving sub-sectorial average baseline should be used for short term targeting.
The application of the best practice and technology should be regarded as targetsfor factories which are already below the existing average baseline.
- The benchmarking results with baselines presented in this report are the baselines
of the studied industries. If necessary, concerning professional associations may
conduct the baselines for every group (small, medium and large scale) or sub-
group, depending on their purposes.
- The production technical secret is a major obstacle in the energy saving activities:
it may exterminate the experience and good practice sharing.
- In order to achieve the sub-sectorial energy saving target, the professional
associations can take an active role instead of waiting for instructions from the
Government.
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PART B. PRIMARY RUBBER INDUSTRY
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1. PRODUCTS CLASSIFICATION
Most of factories, which are member of the Viet Nam Rubber Group, have integrated the
Quality Management System according to ISO 9001, so their operation data, including
production and energy consumption, are well recorded. Some of them have also
integrated Environmental Management System according to ISO 14001 standard.
The project team has received 51 filled questionnaires, 49 of which are usable.
The products of this industry is quite various with 19 different types. However, according
to the norm, issued by the Viet Nam Rubber Group, all of them are classified into four
groups:
Table 13: SEC norm of VRG
Group Product categoriesElectricity
(kWh/ton)
D.O.
(liter/ton)
Water
(m3/ton)
Firewood
(Ster/ton)
1 SVR83L, L, 5110-120 2632 1215 -
SVR CV50, CV 60
2 SVR 10, 20210220 3642 2225 -
SVR 10CV, 20 CV
3 HA9, LA10 100105 - 810 -
4 RSS11
- - 68 1,82
Source: Viet Nam Rubber Group
Referring the classification as presentedTable 13,the data processing will be done with
four groups, instead of every product category.
All factories considered groups 1 (pure latex) is their main product. Group 2 (impure latex)
is their important product. However, the processes of groups 1 and 2 are similar. The
main different between both groups is the impurities content in the first material (natural
latex). Very few factories produce products in groups 3 and 4. In H.A, L.A product
processing, there is a by-product, the SKIM latex. It continues to be sent to coagulating
operation and becomes a lower grade product.
8SVR: Standard Vietnam Rubber
9HA: High ammonia
10
LA: Low Ammonia11
RSS: Ribbed Smoke Sheet
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The main energy used in primary rubber processing is electricity and heat. Heat is used for
drying process. Most of fuel used is Diesel oil. LPG and coal are also used in some
factories.
2. DISTRIBUTION OF SURVEY FACTORIES
Up to now, there is not any document or data source presenting the requested
information for choosing site for benchmarking. The selection of factories could not be
done before the survey because of the no-information. It depends on the willingness of
information sharing from contacted factories. The distribution of factories referring the
selecting criteria for benchmarking proposed by the international consultant can be
observed as inFigure 5.
Source: quoted fromAnnex 4
Figure 5: Distribution of surveyed factories by Output (pure latex equivalent)
In order to observe the distribution of factories, impure latex is converted into pure latexequivalent (Annex 4). Therefore, the Figure 5 presents only seven factories selected for
preliminary audit. The eighth one produces only impure latex (product group 2). Other
products (RSS, L.A., H.A.) takes a very small portion, so it can be ignored. However, some
factories, including ones audited, are not presented inFigure 5 since they produce only
impure latex.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 5000 10000 15000 20000
Big scale
Medium scale
Small scale
Ton/year
Percentile
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Source: survey results
Figure 6: Distribution of surveyed factories by age
2.1. Boundary
Regarding the boundary proposed by international consultant, the waste water treating
system is an auxiliary as it not directly affect to the primary rubber processing. In this
report, since some factories have not monitored the energy for waste treating system or
it is done by a third party, it is not included in SEC analysis. However, regarding feedback
from some factories, this is an important energy consuming system in this industry;
possible solutions will be also proposed in the preliminary audit part.
2.2. Normalization
As mentioned before, almost all primary rubber factories are located in the South, in
addition, there are not space cooling or heating. In drying process, the product humidity
of all factories is exactly similar. Therefore, the normalization of influence of climate
conditions is not necessary.
0
5
10
15
20
25
30
35
40
Age(year)
Factories
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3. PRELIMINARY AUDIT
3.1. Selection for preliminary audit
Factories selected for preliminary auditing are highlighted in red color in Figure 5 and
Figure 6.
As presented inFigure 6,sometimes, difficult to satisfy the two criteria at the same time
for preliminary auditing because of the information sharing willingness of contacted
factories. Therefore, the output of factory is considered as the first criterion. However,
regarding to the two criteria proposed by international consultant, every group has
representative(s) in the selection for preliminary audit.
After the factories identification referring criteria proposed by international consultant,
the selection is done in accordance to the following criteria, based on the real conditions:
- Fulfilling survey questionnaires: this criterion can show the information sharing
willingness of factories.
- Willing to accepting the preliminary audit: it can show the collaboration of
factories with audit team. Of course, the audit team cannot pass through the
factory entry without their acceptance.
Table 14: List of selected factories for preliminary auditing
No Factory Age Production
(ton/year)
Electricity
consumption
(kWh/year)
Power to heat
ratio
1 R52 10 5.049 302.671 27%
2 R41 1 2.886 415.200 42%
3 R08 13 20.169 569.216 41%
4 R09 17 12.091 718.227 29%5 R53 16 11.071 663.326 32%
6 R24 37 15.410 1.527.004 36%
7 R38 33 13.224 1.652.046 46%
8 R54 6 2.500 760.570 68%
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Group 1 - Pure latex
The processing scheme of this product group is presented inFigure 7.
Figure 7: Processing scheme of product group 1 and 2 (SVR)
Electricity used in almost all operation of pure latex processing process, whereas fuel is
used only for drying.
TheFigure 8 presents the electricity used of the 6 audited pure latex factories. As shown
in this figure, mechanical processing tak.v9bes the biggest share.
Latex bulking tank
Coagulating
Crushing
Creeping
Screening, washing
Drying
Packaging
Washing
Cooling
Shredding
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Source: compiled from preliminary audit results.
Figure 8: Share of electricity consumption
In product group 1 (see Figure 9), the factories, R08 and R41, have very high specific
electricity. These values seem to be abnormal. Therefore, it is removed from the
(arithmetic) average value calculation.
The specific electricity consumption of the audited factories is shown inFigure 9.
Figure 9: Specific electricity consumption of audited factories
The specific electricity consumption difference is mainly cause by the technical processing
operations. The drums of technical processing machines are worn out with the time. They
are repaired by reducing the diameter on lathe machine and some other machining
operation, their specifications are change (the case of R08), and they need to have an
adjusting period (with low productivity) in order to ensure the product quality. Besides,
48%45%
7%
Mechanical processing Drying Packaging
41
86 9097
156165
0
20
40
60
80
100
120
140
160
180
R09 R52 R53 R24 R41 R08
kWh/ton
Factory
Average: 79 kWh/ton
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the action of workers is also important: the specific electricity consumption increases
along with the free time of material feeding to the machines.
The R41 has high electricity consumption since its drying process (Figure 10). This is a
small private factory without professional technician, its process and technicalmanagement is poor with lower productivity, which leads to the high electricity
consumption. It has not any management certification (such as ISO 9001 or similar).
Figure 10: Specific electricity consumption of main process of product group 1
It specific drying electricity is abnormally high, so not is not put into average calculation.
In this process, electricity is used for auxiliaries of the dryers, such as fan, fuel supply,
conveyors, etc.
Go into process level, the factory R08 is a member of Du ing Corporaon. It main
assigned job is impure latex. It can process pure latex when other members have enough
first material (it often produces pure latex few months after the crop beginning).
Therefore, during the preliminary audit period, only impure latex processing is audited.
Thus, it is not presented in this section (group 1pure latex section).
For drying, some different types of fuel are used, such as diesel oil (D.O.), LPG (R08, R09,
R38, R24) and coal (R54), so fuels are converted into MJ for comparison.
0
10
20
30
40
50
60
70
80
90
100
R09 R24 R38 R41 R52 R53
Mech. Proc. Drying Packaging
k
Wh/ton
Factory
Aver. 5 kWh/tonAver. 41 kWh/ton
Aver. 38 kWh/ton
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Figure 12: Share of electricity consumption of the audited factories
In impure latex processing, mechanic processes take the biggest share. It is much higher
than that of drying process.
Figure 13: Specific electricity consumption of main process of product group 2
Since group 1 and 2 are produced in the same factories, so they use the same purchased
energy types for drying.
68%
25%
7%
Mech. Proc. Drying Packaging
0
50
100
150
200
250
R38 R52 R53 R54 R08
Mechanical
processing
Drying Packaging
kWh/ton
Factory
Aver. 129 kWh/ton
Aver. 37 kWh/tonAver. 7 kWh/ton
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Figure 14: Specific final thermal energy consumption in drying process of product group 2
As shown inFigure 14,the two LPG use factories, R38 and R08 has smaller specific energy
consumption whereas the coal use one has the highest specific energy consumption.
Therefore, the LPG fire drying kilns has the best efficiency and the coal fire is the worse
one (R54).
Other product groups
Among audited factories, only one of them produces H.A and L.A latex and other one
produces RSS product and SKIM. Therefore, the comparison is not done.
Energy management
The energy consumption does not only depend on technical issues, but also on
management. However, it is difficult to quantitatively evaluate this potential.
In general most of factories are not adequately pay attention on energy management.
The sub-sectorial average of energy management score is less than 50% of the maximum.
0
200
400
600
800
1000
1200
1400
1600
1800
R52 R53 R38 R08 R54
MJ/ton
Factory
Aver. 1407 MJ/ton
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Figure 15: Energy management rating
The factory R41 is a small scale private. Its energy management rating is the poorest. The
others are state owned. The energy management rating of factories R 53 and R52 are also
poor. Both of them is located in central highland region, far from the Viet Nam Rubber
Group headquarter.
Figure 16: Energy management rating by item
The paying attention of every factories on energy management item is quite different.
Most of them do not clear commitment on energy improvement of top manager(s),
reflected through the energy policy.
2.1
1.1
1.4
2.4
2.4
1.8
1.4
0.8
0
1
1
2
23
3
4
4
5
R24 R53 R54 R09 R08 R38 R52 R41
Fact. Aver. Sect. aver. Max
Aver. 1,7
Max. 4
0
5
10
15
20
25
30
35
R24 R53 R54 R09 R08 R38 R52 R41
Energ. Policy Manag. Motivation InformationTraining Energy audit Technology InvestmentMax Aver.
Score
Factory
Max. 32
Aver. 13
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RegardingFigure 15 andFigure 16,the average energy management rating of the audited
factories is very poor, lower than 50% of the maximum. Qualitatively, this is an important
energy saving potential.
According the trainers of the most recent training course set up by UNIDO on EnMS, thesetting up this system can bring a saving from 10% - 15%. In this report only the energy
saving potential due to energy management improvement (but not the EnMS setting up)
is calculated based on the uniformity of SEC of every audited factory.
Table 15: Energy saving potential due to energy management improvement
Factory Saving potential
R24 6%
R53 2%
R54 1%
R09 2%
R08 2%
R38 5%
R52 10%
R41 3%
Average 4%
Waste water treating system
he water treang system is an auiliary one owever as reuested by few surveyed
factories (Du ing corporaon) during the workshop 1, therefore, it is put into analysis.
Most of audited factories are not interesting on energy for water treating system, so most
of them are not interesting on monitoring it. Therefore, the analysis is quite different
since the lack of past data. One audited factory has not wastewater treatment system. Its
wastewater is treated by a contractor with a cost of 0,66 $US/m3.
Not all factories monitor the wastewater quantity, so the analysis is initiated based on the
water consumption and product production.
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-
Figure 18: Specific electricity of waste water system by water consumption
The factory R08 has not monitor water consumption (well water), so it is not put into
analysis.
As the factory R09 produce also the H.A and L.A latex, with different contaminant, and
R24 has abnormal value as discussed above, so the average should be taken from
factories R41 and R54.
3.2. Possible energy saving solutions
The possible energy saving solutions are identified directly during the preliminary audits.
Almost all energy saving measures, which are introduced in Table 16 are not yet
implemented in audited factories. They are proposed measures.
The life cycle saving cost is calculated as follows:
LFSC= INVEST/(E annualsavingx LF)
INVEST : Investment cost
E annualsaving : Annual energy saving
LF : Life cycle
Life cycle saving costs are calculated based on the following assumption: Live cycle:
o VSD, high efficiency motor: 5 year (depreciation period)
o Gasification system, Biogas recycling, waste water treating system: 10 year
0.2
1.01.3
2.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
R24 R41 R54 R09
kWh
/m3
Factory
1,6 kWh/m3
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Investment cost is based on market research and estimated from previous projects done
by ENERTEAM as presented inTable 16
Table 16: Investment cost for energy saving solutions
N
o
Item Standard scale Price
1 Fine pore aeration system 1000m3
waste water/day 900 M. VND
2 Biogas digester 47 M.VND/m3
3 High efficiency electric motor 1.954.314 VND/kW
4 Standard electric motor 1.585.367 VND/kW
5 Biomass gasification 300 kg firewood/hour 3,4 B. VND
The price of standard scale is used for extrapolating for other scales.
The calculation on biomass gasification is based on assumption that all factories is very
near (their own) rubber plantations, so they could use rubber tree branches and cover
enough their thermal energy demand and avoid to use fossil fuels.
Biogas recovery and wastewater treating system are calculated based on the assumption
of 80% the water consumption is rejected as wastewater 12. In practice, biogas recovery
could reduce the size of biomass gasification system. However, to make calculation for
the whole industry, it is difficult to go into very detail.
The high efficiency replacing is calculated based on the assumption of 80% electricity
consumption is used for electric motors, which may be changed to high efficiency motor.
The energy management does not technical investment cost as it need only human
resource. According to the calculation for every individual audited factory, the average
saving potential by improving the existing energy management can contribute to reduce
4% of the existing energy consumption.
The cost of possible technical saving potential can be graphically presented inFigure 19and Figure 20. It can be used for estimation the possible sectorial energy efficiency
investment cost.
12All audited factories do not monitor the waste water quantity
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Figure 19: Possible saving potential of electric solutions
Figure 20: Possible saving potential of thermal solutions
27 VND/MJ
237 VND/MJ
346 VND/MJ
391 VND/MJ
0
50
100
150
200
250
300
350
400
450
1% 2% 3% 4% 5% 6% 7% 8% 9%
Apply high eff. Motor Apply VSD
Replace surface aeration by fine pore one Electricity price
VND/MJpurchased
Saving potential
0
100
200
300
400
500
600
55
Biogas recovery Firewood gasification Coal price LPG price D.O. Price
Saving potential
VND/MJpurchased
21 VND/MJ
64 VND/MJ
550 VND/MJ
605 VND/MJ
2 VND MJ
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However, the simple payback period is quite familiar with the majority of factory
managers and readers. Therefore, it is graphically presented inFigure 21.
Figure 21: Saving potential v.s Payback period of possible solutions.
4. BENCHMARKING
Since the feedback from factories and commented by international consultant, the
average specific primary energy consumptions of every group (small, medium and big
scale factories) are calculated and shown inFigure 22.The grouping is presented inFigure
5.
As shown inFigure 22,generally, bigger factories have the lower primary specific energy
consumption. The average primary specific energy consumption of the small and medium
group is not very different whereas that of the big factory group is much lower.
0
5
10
15
20
25
30
Firewood gasif. Replace surface aeration
by fine pore one
High eff. motor
Biogas recovery Apply VSD
Averagepaybackperiod
(Month)
27
21
1815
13
Saving potential
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Figure 22: Specific primary energy consumption by group
As shown inFigure 23,the relationship between the factory age and specific consumption
is not clear (R2 is quite small). The reason is aged factories regularly upgrade their
equipment and the overhaul maintenance are done periodically. In principle, the purpose
the overhaul maintenance is to recover equipment working characteristics. Younger
factories may need adjusting operations, which also consume energy.
According to the on-site survey during the preliminary audit, the equipment and
technology of this industry is quite simple and similar among factories. Thus, the
dispersion of specific consumption can be also understood as caused by the difference in
operation and management of different factories.
Figure 23: Specific primary energy consumption by factory age
As shown in Figure 24, the load factor does not clearly affect to the specific primary
energy consumption (R2is very small), this mean it is very scattered. It can be understood
0
10
20
30
40
50
60
70
0 5000 10000 15000 20000 25000
Small factories Medium factories Big factories Prim spec. cons.
28 kOE/ton
kOE/ton
Ton pure latex equivalent/year
36 kOE/ton
44 kOE/ton
0
10
20
30
40
50
60
70
0 5 10 15 20 25 30 35 40
kOE/tonpurelatecequivalent
Age (Year)
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that there are problems in the production management, which affects to the energy
consumption in this industry.
Figure 24: relationship between load factor and specific primary energy consumption
The energy management scoring is implemented by audit team during the on-site
preliminary auditing. It is done based on the energy management matrix.
Figure 25: Relationship between SEC and energy management score
As shown inFigure 25,there is the tendency of SEC reduction by increasing the energy
management score. However, it is not clear, as the R2value is very low.
4.1. Group 1 - Pure latex
The distribution of primary SEC for this product group shows that the sectorial average
primary SEC is fallen in the good practice area (Figure 26). This means that most of
factories (62% surveyed factories) still have the primary SEC higher than the sectorialaverage.
0
10
20
30
40
50
60
70
30% 50% 70% 90% 110% 130% 150%
kOE/tonpurelatex
Load factor
1000
1200
1400
1600
1800
2000
2200
5 10 15 20
MJ/ton
Energy management score
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As presented inFigure 26,the sectorial energy efficiency targeting may be done with two
options:
- Select the average primary SEC value (37 kOE/ton - Figure 26) as the target in
order to push factories to make a lot efforts, particularly small factories.
- Select the SEC value of the 50% percentile (41 kOE/ton). It is higher than the
average, so factories will make efforts but not very intensive.
Most of factories are well familiarized with purchased energy. Therefore, the purchased
SEC can be shown inFigure 28.However, since some factories use LPG as fuel for drying
whereas the rests use diesel oil, so the purchased SEC for thermal application is
presented in MJ/ton.
Figure 28: Specific purchased energy consumption of group 1 products.
As shown in Figure 28, the actual average purchased SECs are lower than those in the
norm of VRG.
4.2. Group 2 - Impure latex
Most of big factories have process for producing group 2 products as their by-product in
their whole from-plantation-to-factory production chain. Few small factories produce
only this product group, most of which are private.
0
200
400
600
800
1000
1200
1400
1600
1800
0
50
100
150
200
250
0 5000 10000 15000 20000
Spec. Elec. Consumption Spec. ther. Energ. Consumption
VRG Norm: 1248 MJ/ton
Aver. 1057 MJ/ton
VRG Norm: 120 kWh/ton
Avr. 108 kWh/ton
Ton/year
MJtherm./
ton
kWhelec.
/ton
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manage their energy performance quite well, since they are controlled by the norm
issued by their mother company.
Like product in group 1, there is the tendency of primary SEC reduction along with the
production augmentation. However, this tendency is not strong as the R2is quite small.
Figure 31: Specific purchased energy consumption of group 2 products.
It is noted that there is one factory uses coal for drying. Its specific thermal energy is
much higher than others. As a particular case, so it is not put intoFigure 31.However, it
can show that the energy efficiency of coal fire dryer is low.
0
500
1000
1500
2000
2500
0
50
100
150
200
250
300
350
0 2000 4000 6000 8000 10000 12000
VRG norm: 220 kWh/ton
Elec. aver. 174 kWh/ton
VRG norm: 1639 MJ/ton
Ther. aver. 1392 MJ/ton
MJtherm
/ton
kWhelec.
/ton
Ton/year
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4.3. Group 3 - H.A, L.A. latex
The processing scheme of product group 3 is presented following.
Figure 32: Processing scheme of product group 3 (H.A.; L.A.)
Very few factories produce group 3 products. The only energy usage in processes for this
product group is electricity. However, as in Figure 33, it shows the tendency of SEC
reduction along with the production augmentation.
Latex bulking tank
tank
Centrifuge
Packaging
L.A, H.A products Skim
Crushing, washing
Coagulating
Drying
Packaging
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As presented inFigure 35,since it is a sub-product of factories, no tendency of primary
SEC reduction is found out by analyzing only this product.
Figure 35: Specific primary SEC of product group 4
5. SECTORIAL SAVING POTENTIAL
The sectorial saving potential can be done by moving the average baseline. Other
approaches are to identify the best practice land best available technologies. Other
approaches are presented as follows.
5.1. Moving the average baseline
In this approach, all factories those have SEC higher than the sectorial average will try tobring it to the sectorial average value. The new expected SEC of factories will set a new
(expected) average value. The difference between the two average values can be
considered as the sectorial potential. In this approach, this potential value can be seen as
the target of the energy efficiency strategy/program.
0
2
4
6
8
10
12
14
16
18
R15:
441 ton/y.
R13:
4828 ton/y.
R27:
500 ton/y.
R45:
2382 ton/y.
R28:
500 ton/y.
kOE/ton
Factory
Aver. 9 kOE/ton
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5.3. Moving the quartile average
In this approach, enterprises have SEC higher than the average baseline of its quartile
group, they are supposed to translate into such baseline. If they are lower than the
quartile baseline, they are supposed to translate into the average baseline of the nextquartile. In case of enterprises have SEC lower than the 25% quartile baseline; they are
supposed to translate into the best available technology point as presented inFigure 37
(seeFigure 38).
The sub-sectorial energy saving potential estimated by this approach is 21,5%.
This approach is done as commented by experts invited in the workshop No 3. However
the improving possibility of every quartile group is quite different. The SEC of enterprises
in the 75% quartile group is very poor, so their improving opportunities are quite high,whereas the SEC of enterprises in the 25% quartile group is already very good, so it is
quite difficult to improve. Moreover, the gap between the average baselines of best and
good practice groups is quite big. Therefore, in order to promote them to go to the best
available technology point (as presented in Figure 37)will take time along with effective
incentive policies but not make market distortion. Therefore, this approach may not
feasible in practice.
Figure 38: Moving the quartile average baselines
0
10
20
30
40
50
60
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
kOE/ton Best Good Medium Poor Expected
13
35
44
53
SEC
kOE/tonpurelatexequivalent
Percentile
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5.4. Moving the average baseline of scale groups
Figure 39: moving the scale group average baselines
As presented inFigure 5 andFigure 22,the factories can be classified into three groups
with different SEC. It is noted that small factories are full private ownership and not
controlled by the VRG norm. In these factories, the maintenance is not paid attention,particularly, their thermal uses (dryers). The result is the low energy efficiency.
Regarding to the similarity in technology, equipment and management of factories in
every group (small, medium, big scales), the energy saving potential assessment is done
for every scale group with the same approach as shown in section5.1 andFigure 36 (see
Figure 39.
With this approach, the calculated sub-sectorial energy saving potential is 20%.
0
10
20
30
40
50
60
70
0 5000 10000 15000 20000
Small scale aver. Medium scale aver. Large scale aver.
Exp. small scale Exp. medium scale Exp. large scale
SEC Exp. SEC
kOE/tonpurelatexequivalent
Ton pure latex equivalent/year
40
31
21
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6. CONCLUSION
The climate conditions does not affect to the SEC. The product humidity, according to the
national standard, is similar for all factories, so it is not affect to the sectorial SEC.
Most of primary rubber factories have their purchased SEC lower than the norm issued by
VRG. However, there are few small private factories still have purchased SEC higher than
the mentioned norm.
Almost all factories, which are member of VRG have quite good SEC. Therefore, it is
recommended that VRG should play a certain role in supporting the private sector.
The sectorial energy performance targeting should be carried out carefully with the
product group 1 as it has the sectorial average values and the 50% percentile value.
The primary SEC is not depending to the factory age and load factor.
Energy efficiency of drying process with coal as fuel is lower than that with oil or LPG.
Since primary rubber factories are component of rubber tree plantation, so firewood
gasification should be thought of.
All life cycle energy saving costs are lower than most of energy prices. This is an excellent
signal to promote the energy efficiency actions.
Regarding the targeting, the moving average baseline should be firstly considered since its
simplification.
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PART C. NPK FERTILIZER INDUSTRY
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1. PRODUCT AND FACTORY SELECTION
1.1. Selection and distribution
The survey team sent 45 questionnaires to factories, and then received 22 feedbacks.
However, only 11 of them are usable for putting into analysis. The main reason for no
feedback is these factories are afraid of secret technology leakage even if the team has
always been committing to maintaining the survey information confidentiality. Other
reason is that most of small and medium factories do not well manage information, so
they could not fill up the questionnaire.
For few factories, NPK is one of their products and produced in only one small production
line. Therefore, the NPK production is very small.
One of them outsources the drying process (which uses biomass as fuel) and the survey
team could not get the permission for auditing it (a contractor of the drying process);
consequently, this case is not included in primary energy analysis but in specific electricity
consumption analysis.
Electricity and heat are consumed NPK manufacturing as main energy sources. Heat, for
example, is for granulating and drying process. Most of factories use coal as fuel for
heating purpose (drying, steam for granulating); meanwhile, some factories in the South
use oil for providing steam in granulating process.
The NPK fertilizer products are classified based on their composition. There are normally
two main groups: tricolor and mono-color NPK, the processing scheme of which is
mentioned in part 5. Since the tricolor manufacturing processes (only mixing and
packaging) are almost similar to some mono-color processes, the benchmarking and
preliminary audits are mainly focus on the mono-color.
Due to the limited number of usable feedbacks, the selection of factories for preliminary
audits depends mainly on the information sharing willingness of contacted factories.
However, the survey team tries to have a representative sample in every group regarding
the criteria proposed by international consultant.
Because the distribution calculation is used for selecting factories to audit (before the
audit), it is based on the survey and the mono-color as the main product.
Figure 40 shows the distribution of factories by scale. The factories accept to get
preliminary audit are highlighted in redcolor.
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Table 17: List audited factories
Factory1 color
Ton/year
3 color
Ton/year
Power to heat
ratioAge Remark
F76 11.474 - 18% 38 Monocolor
F91 144.439 31.687 24% 6 Monocolor and tricolor
F93 70.467 30.200 26% 7 Monocolor and tricolor
F31 189.610 330.390 14% 7 Monocolor and tricolor
F48 398.617 -Drying:
outsourcing 51 Monocolor
F17 234.511 - 19% 16 Monocolor
F04 - 57.840 2% 53 tricolor
1.2. Normalization
The influence of different climate conditions between the North and the South on the
energy consumption is quite small (less than 1%). Moreover, there is not space for cooling
or heating in NPK industry, so the normalization of climate conditions can be omitted.
In reality, there are many mono-color NPK products and the main differences of them are
their composition and humidity. The composition does not affect significantly the energy
consumption, but the humidity can clearly do that. According to the theoretical
calculations, SEC may increase by 1,2% in order to reduce 1% of product humidity. As a
consequence of this, the normalization factor of product humidity can be taken as 1,2%
per 1% humidity. The analysis presented in this report includes different mono-color NPK
products from various factories. Hence, it is considered as the reference. The
normalization factor should be taken into account when applying for comparison of a
concrete product.
Since the tricolor manufacturing process without granulating and drying is so simple that
the normalization could not be necessary.
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2. PRELIMINARY ENERGY AUDIT
2.1. Process scheme
The manufacturing scheme of mono-color NPK is presented in
Figure 42.
Figure 42: Manufacturing scheme of mono-color production
In the mono-color production, after the screening:
- If the grain is satisfied with the requested size, it then goes to the packaging.
First material: Ure, SA, DAP,
KCl, additive
Mixing
Granulating
Drying
Screening
Cooling
Packaging
Grinding
Un
er-sze
Over
-sze
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- If the grain is over-size, it turns back the grinding process.
- If the grain is under-size, it comes back the mixing process.
he sending materials back a previous process is called recirculation.
2.2. Preliminary audit
As presented inFigure 43,F17 is a factory with main products such as super phosphate
and Sulfuric acid. NPK is its sub-product. Its specific electricity consumption for grinding
process is much lower than other factories as the result of the fact that most of its
primary materials are prepared from the main product facility. Finally, it is excluded from
the average calculation.
The calculation shows that the specific electricity consumption for grinding of F17 is much
higher than that of others. The main reason is the operation issue like the recirculation
rate (caused by the grain size) as explained above. Actually, this rate is manually
controlled based on the seeing of operators. Therefore, the concentration on the work of
operators is very necessary for the energy consumption in the production.
In factories F91 and F31, since most of the first materials are in powder form, their
specific electricity consumption is lower than that of other. It can be concluded that the
first material preparation can effectively contribute to the energy saving.
Figure 43: Specific electricity consumption by main process of NPK manufacturing
As shown in Figure 43, since the difference in the installation of power control system
among audited factories, the specific purchased energy consumption on the packagingprocess and auxiliaries (conveyor, fans, etc.) are not presented.
0
5
10
15
20
25
30
F76 F17 F93 F31 F91 F48
Grinding + mixing Granulating Drying + cooling Screening
Aver 15,5 kWh/ton
Aver. 9,4 kWh/ton
Aver. 4.6 kWh/ton
Aver. 1,4 kWh/ton
kWh
elect./
ton
Factory
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Based on the onsite and data processing observations, the normalization is done and
presented inFigure 44:
- The packaging ranges from 3% to 8%, the average value of 5,5% is taken
- Technical auxiliaries are estimated as 6% regarding the data available in fewfactories (during the preliminary audit).
Figure 44: Specific electricity consumption by process with normalization
In order to have an image about the importance of every main process in term of
electricity consumption, the share of electricity consumption of the whole audited
factories is displayed inFigure 45.
As shown inFigure 45,the drying process take the biggest share as it is drum dryer with
big electric motors. The grinders also have big motors.
1.53
41.15
1
9.00
1.63 4
.32
14.08
1.53
1.07
6.33
13.59
1.86
3.28
3.56
1.07
7.13
23.21
8.39
7.92
24.56
22.79
7.13
0.01
0.58
1.85
1.73
1.93
3.56
0.07
0.59
1
8.99
17
.66
2.59
2.25
2.64
0.59
0.00
5.00
10.00
15.00
20.00
25.00
30.00
35.00
40.00
45.00
F48 F76 F17 F93 F31 F91 F48
Grinding Mixing & granulating Drying & cooling Packaging Auxiliaries
kWhelect./
ton
Factory
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Figure 45: Share of electricity consumption by process
In some factories, which use steam for drying, the energy (fuel) consumption for
granulating and drying processes is not monitored separately. Some other factories use
oil for producing steam for granulating process and coal for drying, so they can account
separately energy consumption for these processes. According to the onsite survey during
the preliminary audits, the purchased energy, in term of MJ/ton, of granulating process
takes a share in the range from 13% to 17% of the total energy for heating purpose
(granulating+ drying).
Figure 46: SEC for heating (granulating and drying)
In factory F48, the (sawdust fueled) drying kiln is owned and operated by an external
contractor, but the cooling fan (for cooling process) is owned and operated by the
factory, so it has electricity consumption but not thermal energy for drying.
In order to have the consistency in the presentation and comparison, the energy for
31%
11%37%
4%
17%
Grinding
Mixing & granulating
Drying & cooling
Packaging
Auxiliaries
0
200
400
600
800
1000
1200
F76 F17 F92 F31 F91
Aver. 2695 MJ therm/ton
MJtherm
/ton
Factory
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granulating and drying is presented together as heating (Figure 46).
The audit team directly rates the energy management rating by interviewing managers
and observing on the field.
The energy consumption does not only depend on technical issues, but also on
management. Some factories have good energy policy in paper, but it is not well put into
practice (F92). Most of factories do not yet consider energy efficiency in their investment
policy.
Figure 47: Energy management rating in NPK industry
Like in primary rubber industry, the energy saving potential due to energy management
improvement is calculated by the same way.
Table 18: energy saving potential due to energy management improvement
Factory Saving potential
F93 4%
F91 2%
F17 3%
F48 3%
F76 5%
F04 2%
Average 2%
Source: Compile from individual preliminary audit report
0
1
2
3
4
5
F76 F17 F93 F31 F91 F48 F04 F92
Energy Policy Management MotivationInformation Training Investment policy
Ra
ting
Factory
Average: 2
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2.3. Possible energy saving solutions
During the preliminary energy audit, some popular solutions (such as replacing magnetic
ballasts with electronic ones, applying day lighting) were directly suggested to the
factories. Because their contribution in the saving potential is very small (less than 1%), itis not presented in this report.
Since most of factories are not located in biomass prosperous areas, regarding the high
biomass transport cost, the biomass gasification is not taken into consideration.
Individual preliminary audit reports exclude some possible solutions caused by the
hesitation of factories. However, they are included into calculation regarding the long
term view point.
The saving cost is calculated as follows:
LFSC= INVEST/(E annualsavingx LF)
INVEST : Investment cost
E annualsaving : Annual energy saving
LF : Life cycle
Reduce recirculation ratio
Almost all factories have high recirculation ratio (22% to 55%). The recirculated products
quantity consumes almost double energy. Therefore, reduce recirculation ratio can save a
lot of energy. As shown in
Figure 42,the recirculation starts just after the screening process. Actually, the screening
is controlled by seeing instead of supervision device.
The recirculation ratio can be improved by better control the humidity in granulating
process, the fineness of first material. Therefore, this solution does not need new
investment.
According to the preliminary audit, the best recirculation rate is 5% (see Annex 8) (Factory
F93). Therefore, the rate of 5% is selected as the target for calculation.
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Figure 48: Recirculation ratio
The energy saving potential by improving the recirculation ratio of audited factories is
shown inFigure 49.
Figure 49: Possible energy saving due to improving recirculation rate
The average potential energy saving due to this solution can be estimated as 24% (see
Annex 8).
Use high efficiency electric motor
Similar to the primary rubber industry, electricity consumption could not directly measureduring the preliminary audit due to the complexity of the power distribution system. It is
55%
23%
28% 30% 30% 30%
0%
10%
20%
30%
40%
50%
60%
F17 F93 F91 F31 F48 F76
Average factory ratio Average Target
33%
Factory
Recirculationratio
7,539
12,785 38,342
93,704
171,252182,217
1,246
1,652
3,445
11,599
53,524
48,682
-
20,000
40,000
60,000
80,000
100,000
120,000
140,000
160,000
180,000
200,000
F76 F48 F93 F91 F17 F31
Energy Cons Saving
TJenergy/y
ear
Factory
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estimated as 15% used for non-process uses, such as office, security lighting, well
pumping, etc. The rest is considered as mainly consumed by electric motor.
Standard electric motor can be replaced when they are over their life cycle. In this case,
high efficient motor can be applied. The cost used in the calculation is difference between
the high efficient motor and the standard one (extra cost).
With the average 3% of higher efficiency, the electricity consumption is expected to
decrease around 3% or 0,1% purchased energy.
Figure 50: Possible electricity saving by applying high efficiency electric motor
The factories F76 and F04 produce only tri-color NPK, so their electricity consumption is
the lowest.
The saving cost is calculated based ong the following estimation:
- Life cycle : 5 year
- Working day : 300 day/year
- Daily working period : 12 hour/day (some period: one shift/day; some other
period: two shifts/day)
- Price difference between standard and high efficiency motors: 387.000 VND
- Exchange rate : 21.000 VND/$
366 1
290 2
459 3
862 57
30 7
389
10026
12209
11
39
74
116
172
222
301
366
0
2000
4000
6000
8000
10000
12000
14000
F76 F04 F93 F48 F91 F31 F17 F04
Process elect. Cons. Possible Saving
Thous.kWh
elect./
year
Factory
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Standard
motor
(VND/kW)
High eff.
Motor
(VND/kWh)
Extra cost
(VND/kW)Efficiency
differenceSaving
per KW
inst.
Life cycle
saving
(kWh)
Saving cost
(VND/kWh)
1.585.367 1.954.314 368.947 3% 0,03 536 688
Source: Calculated fromAnnex 3: Cost of electric motor
VSD
In NPK factories, the VSD can be appli