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CO2 mitigation and power generation implications of clean supply-side and demand-side technologies in Thailand
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Energy Policy 32 (2004) 83–90
CO2 mitigation and power generation implications of clean supplyside and demand-side technologies in Thailand Somporn Tanatvanita, Bundit Limmeechokchaia,*, Ram M. Shresthab a
Sirindhorn International Institute of Technology, Thammasat University, P.O. Box 22 Thammasat Rangsit Post Office, Pathumthani 12121, Thailand b Energy Program, Asian Institute of Technology, P.O. Box 4, Klong Luang, Pathumthani 12120, Thailand
Abstract The CO2 mitigation from the power sector in Thailand can be accomplished through both the technological substitutions in supply-side options, and the reduction of power generation through adoption of demand-side-management options. The traditional power generation expansion planning has focused only on supply-side options. However, in this study both supply-side and demand-side options are simultaneously considered in a long-term integrated resource planning model, to determine the least-cost options. Results of the analyses show that during 2003–2017 the use of efficient demand-side technologies and the efficient power generation technologies would reduce CO2 emission by 8.4% compared to the base case. When CO2 reduction targets are introduced, the installed capacity of and generation from clean supply-side technologies are found to increase. The long run average cost in the base case is found to increase from 3.10 to 3.22 US cents/kWh if the target of CO2 emission reduction by 30% is to be achieved. In addition, the sensitivity analyses are carried out to determine the effect of some parameters on the generation plan. r 2002 Elsevier Science Ltd. All rights reserved. Keywords: Clean supply-side option; Demand-side management; Integrated resource planning
1. Introduction In 1999, the power sector accounted for 33% of the total primary energy consumption in Thailand. It is also the largest contributor of CO2 emission (DEDP, 1999). In Thailand the rapid growth in electricity requirements has had a significant impact not only on the electric utility in terms of electricity generation expansion planning but also on related environmental emissions. Because of the limitation of fossil fuel resources and the problems of air pollution, the utilities need a sustainable expansion plan to provide adequate electricity supply capacity in the future and mitigate environmental emissions, particularly the CO2 emissions. To achieve a sustainable expansion plan, energy management programs such as demand-side management (DSM), energy conservation, and fuel switching have been implemented in Thailand (OEPP, 2000; NEPO, 1997).
*Corresponding author. Tel.: +662-986-9009x2206; fax: +662-9869113. E-mail addresses: [email protected] (B. Limmeechokchai), [email protected] (R.M. Shrestha).
In the context of power generation, the supply-side options and DSM programs are considered as the viable options to mitigate CO2 emission. CO2 emission could be mitigated through technological substitutions towards cleaner and more efficient supply-side options in power generation while it could also be mitigated through DSM options that reduce electricity demand (Shrestha et al., 1999). Traditionally, the electricity generation expansion planning process in Thailand is to identify the sequence of generation additions resulting in meeting the forecasted demand at a minimum total system cost. While the traditional resource planning (TRP) process focuses only on the supply-side options, the integrated resource planning (IRP) process includes both the supply-side and the demand-side options to meet the forecasted demand in a least-cost manner. Therefore, both the TRP and IRP plans are investigated in this study to find out the least-cost electricity generation expansion plans and to identify the options for mitigating CO2 emission. The sensitivity analyses of the uncertainties in parameters such as fuel price, peak demand, and capital cost are also presented. In addition, the variations in expansion plans in terms of generationmix, total cost, and CO2 emission are analyzed for four different levels of CO2 emission reduction targets.
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2. Electricity sector in Thailand The existing power plants in 1998 consisted of 161 units of various generating stations with total capacity of 18,174.5 MW (excluding 0.53 MW of renewable energy). The total capacity consisted of 2874 MW (15.8%) of hydro, 6517 MW (35.9%) of conventional oil/gas and lignite-fired plants, 5074 MW (27.9%) of combined-cycle plants, 892 MW (4.9%) of gas turbine and diesel plants, and 2818 MW (15.5%) of capacity purchased from other power suppliers (EGAT, 1999a). 2.1. DSM in Thailand Thailand became the first country in Asia to formally adopt a nationwide DSM master plan. In 1992, the Royal Thai Government approved the program budget of US$ 189 million to implement DSM programs in the country. The World Bank, under the auspices of the Global Environment Facility (GEF), has also supported the project with a grant funding of US$ 15.5 million. For over 8 years, after EGAT had launched the DSM program in 1992, various DSM programs had been implemented with aims to promote the use of energy efficient appliances, to create the attitude of energy conservation, and to support and pursue energy efficiency and load management technologies. EGAT has implemented DSM programs in three main sectors: residential, commercial, and industrial sectors. The DSM programs included the following: *
* * * * *
energy efficient fluorescent lamp program, known as thin tube program, refrigerator efficiency labeling program, air conditioner efficiency labeling program, high efficiency motor program, compact fluorescent lamp program, and cool storage program.
For the thin tube program, EGAT engaged in direct negotiations with Thai lamp manufacturers to voluntarily agree to ban the production of low-efficiency lamps and only produce high-efficiency lamps, which emit the equipment lumen output. By mid-1995, all lamp manufacturers and importers complied with the agreement. So, the impact of this program has been substantial, because the efficiency of all lamps sold in Thailand was improved at up-stream. For refrigerators and air conditioners, EGAT adopted a product efficiency labeling approach, where all participating brands of refrigerators and air conditioners would carry a label, which indicates the efficiency label, annual kWh consumption and the energy saving estimates. (Ratanopas, 1997). To date, the successful campaigns of DSM programs in Thailand are the labeling campaign for efficient
refrigerators and air-conditioners, which has now become a symbol of efficiency and energy saving. The major DSM campaigns are composed of the energyefficient thin tube program, refrigerator labeling program, and air conditioner labeling program. These programs have resulted in the total saving of 566 MW of peak demand, 3140 GWh of energy and the reduction of 2.32 million tonnes of carbon dioxide emissions (EGAT, 2000). Therefore, these major DSM programs will be continuously implemented well into the future to achieve the perpetual energy efficiency. Moreover, the electricity efficient ballasts and the high efficiency electric motors could be included in the campaign soon.
3. Data and assumptions in electricity generation expansion planning In this study, the analytical tool used to find out the least-cost power generation expansion plans is the IRP model, developed by Shrestha et al. (2001). The IRP model considers both demand- and supply-side options to meet the electricity demand in a least-cost manner, subject to a given emission reduction target. The leastcost plans are divided into two main categories: the TRP plan and the IRP plan. In the TRP plan, only supplyside options are considered. In the IRP plan, five DSM options are included in the analyses to simultaneously compete with the supply-side options. The CO2 reduction targets of 5%, 10%, 20% and 30% in the context of mitigation of greenhouse gas emissions from the power sector are introduced to both the TRP and the IRP plans. The emissions of CO2 SO2 and NOx are calculated based on emission factors provided by the Intergovernmental Panel on Climate Change (IPCC, 1996). The important assumptions and constraints used in the analyses are as follows: *
*
*
A planning horizon of 15 years (i.e., 2003–2017) with the base year in 1998 is considered. The minimum and maximum reserve margins of 15% and 25% are adopted (EGAT, 1999a). The natural gas imported from neighboring countries is considered to be enough for approximately 11,650 MW of additional capacity (EGAT, 1999a).
3.1. Load forecast data The annual peak loads figures used in the study correspond to the load forecast for the period 2003–2011 under the moderate economic recovery scenario of the Electricity Generating Authority of Thailand (EGAT, 1999a). The growth rate of peak demand during 2003– 2011 is assumed to continue during 2012–2017 in deriving the load forecast at a constant system load
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factor of 0.73. The peak load is expected to increase from 18,399 MW in 2003 to 39,490 MW in 2017. The load data used in the model are the average chronological load curves (CLCs) which are divided into three seasons; winter, summer, and rainy seasons. Each season is represented by one CLC of the peak day in that season.
commercial sector is not considered as an option in this study. The data on the projected stock of electric appliances, and their annual energy saving are obtained from the DSM office of EGAT. The technical details and costs of existing and efficient appliances are based on Shrestha et al. (1998) and market surveys.
3.2. Supply-side options
3.4. Cases considered in this study
3.2.1. Candidate power plants The candidate plants used in the IRP model are divided into two groups: conventional power plant options, and clean and efficient technology options (see Table 1). In Thailand, renewable energy such as biomass energy, hydro and solar-power, has been an important source of energy. These energy resources are the important options to mitigate greenhouse gases emission. Additionally the EGAT has been interested in the research and development of clean coal technology, such as integrated gasification combined cycle (IGCC) (EGAT, 1999b). The data on conventional thermal and hydropower plants are based on EGAT (1999a). While the data on clean technologies are obtained from TEI (1990) and Limmeechokchai and Chungpaibulpatana (1999).
The case studies are divided into two baseline cases: the traditional electricity planning or the TEP case and the IRP with clean supply-side options or the IRC case. The TEP case is used as a reference case for the comparison of the other cases. In the TEP case, only the clean supply-side options are considered to meet the projected demand. Whereas in the IRC case both supply- and demand-side options are considered. The clean supply-side options are also included in both the TEP case and the IRC case. In addition, four levels of CO2 limitation, 5%, 10%, 20%, and 30% are applied to the TEP case called the TEP05, TEP10, TEP20, and
3.3. DSM options Five DSM options are considered in this study, which included efficient lightings, efficient refrigerators, and efficient air-conditioner in the residential sector, efficient air-conditioner in the commercial sector, and efficient electric motors in the industrial sector. (see details in Table 2). The efficient fluorescent tubes are considered to have completely replaced the use of conventional fluorescent tubes in the commercial sector. Since no manufacturers produced the conventional tubes after the year 1995. Thus, the efficient lighting program in the
Table 2 Demand-side-management options considered in the IRP model Sector
DSM options
Residential
DSM1: replacement of 20 and 40-W fluorescent lamps with 18 and 36-W fluorescent lamps DSM2: replacement of conventional refrigerator with the most energy efficient Refrigerator DSM3: replacement of conventional airconditioner with the most energy efficient airconditioner DSM4: replacement of conventional airconditioner with the most energy efficient airconditioner DSM5: replacement of 5–500 hp conventional motors with the energy efficient motors
Commercial
Industrial
Table 1 Candidate plants in the IRP model Plant type
Fuel type
Capacity (MW)
Heat rate (kcal/kwh)
CO2 emission factor (g/kwh)
Traditional plants Coal based Coal based Oil based Gas turbine Combined cycle
Imported coal Imported coal Fuel oil Diesel Natural gas
700 1000 1000 200 600
2391 2321 2340 2742 1859
947 919 636 860 473
Clean supply side plants IGCC PFBC Biomass Solar power Mini-hydro power
Imported coal Imported coal Biomass — —
500 500 100 1 10
2200 2195 2378 — —
821 903 0 0 0
Notes: IGCC stands for integrated gasification combined cycle; PFBC stands for pressurized fluidized bed combustion.
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TEP30 cases, respectively, and the IRC case called the IRC05, IRC10, IRC20 and IRC30, respectively.
the total capacity of coal-based plants in all cases, presented in Table 4. Substitutions for coal-based plants are gas-based and biomass-based plants in both the TEP case and the IRC case with CO2 limitations. Although the CO2 emission constraints are applied in the TEP and IRC cases, the solar power, IGCC and PFBC plants are not selected due to their high total system costs compared to other clean supply-side options. In the IRC case, the additional capacity in the planning horizon is less than the TEP case due to end use energy savings with the use of DSM options. In the IRC case, and the 1IRC case with CO2 limitations, the cumulative generation is decreased by an average of 6.5% compared to the TEP case, as shown in Table 5. The peak load avoided due to the use of efficient air conditioners in both residential and commercial sectors account for approximately 79% of the total peak load avoided. The corresponding figures for efficient refrigerators, motors and lamps are about 10%, 8% and 3%, respectively.
4. Results of the least-cost analyses 4.1. Utility planning implications The results of the least-cost plans from the IRP model reveal that the coal-based power plants take the largest share in the total additional capacity in the TBP case and also in the IRC case, presented in Table 3. In the TEP case, 5 units of 100-MW biomass-based plants and 10 units of 10-MW hydro power plants are committed, while in the IRC case, 6 units of 100-MW biomass-based plants and 10 units of 10-MW hydro power plants are committed. The introduction of CO2 limitation shifts the power plant types from high-carbon-content fuelbased plants to low-carbon-content fuel-based plants. The higher the percentage of CO2 limitation, the lower is
Table 3 Number of committed plants in all cases Case study
TEP TEP05 TEP10 TEP20 TEP30 IRC IRC05 IRC10 IRC20 IRC30
Total number of committed power plants (2003–2017) 1000-MW coal
700-MW coal
600-MW CC
100-MW biomass
10-MW hydro
20 20 16 14 11 20 20 19 15 12
6 — 3 1 1 — 1 — 1 1
15 19 19 19 19 19 19 19 19 19
5 20 39 73 103 6 — 17 49 78
10 10 10 10 10 10 10 9 10 10
Additional capacity (MW)
Cumulative generation (TWh)
33,800 33,500 33,500 33,500 33,500 32,100 32,200 32,190 32,100 32,000
3096 3096 3096 3096 3096 2894 2894 2894 2894 2894
Notes: CC stands for combined-cycle power plant.
Table 4 Capacity-mix by plant types in 2017 Case study
TEP TEP05 TEP10 TEP20 TEP30 IRC IRC05 IRC10 IRC20 IRC30
Total capacity requirement (MW)
49,706 49,406 49,806 49,406 49,406 48,006 48,106 48,096 48,006 47,906
Capacity-mix (%) Coal-fired
Oil-fired
CC
GT
IPP
Hydro
Biomass
52.31 44.12 40.28 33.40 27.32 45.41 46.77 46.25 36.45 30.27
5.98 6.01 6.01 6.01 6.01 6.19 6.17 6.18 6.19 6.20
26.55 31.57 31.57 31.57 31.57 32.49 32.43 32.43 32.49 32.56
0.31 0.31 0.31 0.31 0.31 0.32 0.32 0.32 0.32 0.32
7.84 7.89 7.89 7.89 7.89 8.12 8.10 8.10 8.12 8.13
6.01 6.04 6.04 6.04 6.04 6.22 6.21 6.19 6.22 6.23
1.01 4.05 7.89 14.78 20.85 1.25 0.00 3.53 10.21 16.28
Notes: CC stands for combined-cycle power plant; GT stands for gas turbine power plant; IPP stands for independent power producer.
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4.2. Environmental implications Energy savings through DSM options and the substitution of generation technologies from high carbon intensive fuel-based plant to low carbon intensive fuel- based plants directly affect environmental emissions especially the CO2 emission. The CO2 mitigations in all cases are compared to the TEP case. In the IRC case, 8.4% of CO2 emission are decreased by the reduction of electricity generation (see Fig. 1). When the CO2 limitations are introduced, the CO2 emissions decrease by 9.0%, 14.2%, 24.6% and 34.1% in the TEP05, TEP10, TEP20 and TEP30 cases, respectively. In the IRC case with CO2 limitations, the CO2 emissions are decreased by 9.3%, 14.4%, 24.2% and 34.1% in the IRC05, IRC10, IRC20 and IRC30 cases, respectively. In addition to the CO2 mitigation, other harmful emissions such as SO2 and NOx are also mitigated (see Fig. 2). The Table 5 Cumulative generation avoided and peak load avoided in 2017 DSM options
Peak load avoided (MW) in 2017 IRC
DSM1 DSM2 DSM3 DSM4 DSM5 Total peak load avoided in 2017 Cumulative generation avoided during 2003– 2017 (GWh)
36.4 129.2 233.7 764.4 99.1 1262.8
201,742
IRCO5 36.4 129.2 233.7 764.4 99.1 1262.8
201,742
IRC1O 36.4 129.2 233.7 764.4 99.1 1262.8
201,742
IRC2O 36.4 129.2 233.7 764.4 99.1 1262.8
201,742
IRC3O 36.4 129.2 233.7 764.4 99.1 1262.8
201,742
87
SO2 and NOx mitigations correspond to the CO2 mitigations in all cases. However, the shift of power generation technologies from conventional technologies to clean technologies results in an increase in total system costs because the total system costs of clean technologies are higher than the conventional technologies. 4.3. Economic implications In the economic perspective, the total expenditure including DSM costs in the IRC case in the planning horizon are less than those in the TEP case by US$ 1592 million due to the reduction of electricity requirement, see Table 6. When different levels of CO2 limitation are introduced, the total costs in all cases increase owing to the increase of capital cost of power plants. The total costs increase by 0.7, 1.2%, 2.4% and 3.9% in the TEPO5, TBP10, TBP20 and TBP30 cases, respectively, compared to the TEP case. Although the total costs in the IRC with CO2 limitation cases increase, the total cost in those cases are still lower than that in the TEP case. The major reason is the less electricity generation. The results of those costs and the quantity of electricity generation directly effect the long run average cost (LRAC). The LRACs in all cases are higher than that in the TEP case. In both the TEP30 and the IRC30 cases, the LARCs increase approximately 4.0% compared to the TEP case. In the IRC case, however, the LRACs increase only 0.6% compared to the TEP case. 4.4. Marginal abatement cost (MAC) of CO2 As the previous mentioned, the introduction of CO2 limitation results in an increase in total system cost in all
Fig. 1. Cumulative CO2 mitigation in all cases during 2003–2017 compared to the base case.
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Fig. 2. Cumulative SO2 and NOx mitigation in all cases during 2003–2017 compared to the base case.
Table 6 Cumulative costs in all cases during 2003–2017 Case study
TEP TEP05 TEP10 TEP20 TEP30 IRC IRC05 IRC10 IRC20 IRC30
5. Sensitivity analyses
Coat components
Capital cost (106 US$)
Fuel and O&M (106 US$)
DSM cost (106 US$)
Total cost (106 US$)
5075 5331 5698 6357 7235 4602 4509 4756 5402 6259
25,092 25,032 24,829 24,535 24,119 23,795 23,897 23,785 23,494 23,101
— — — — — 178 178 178 178 178
30,167 30,363 30,527 30,892 31,354 28,574 28,584 28,719 29,074 29,538
LRAC (cents/ kWh)
In this study the sensitivity analysis is performed to examine the effect of variations in major parameters on utility planning, environmental, and economic implications. Sensitivity analyses are conducted for the TEP case and the IRC case. The five major parameters considered in sensitivity analyses are as follows:
3.10 3.12 3.14 3.17 3.22 3.12 3.12 3.13 3.17 3.22
*
Note: LRAC stands for long run average cost.
cases. The MAC in dollars per ton of carbon ($/ton C) is vary with the levels of CO2 limitation. In this study, the considered MAC is based on the TEP case. In the TEP case with CO2 limitation, the MACs range from 8.69 $/ton C at 5% CO2 limitation to 13.26 $/ton C at 30% CO2 limitation. Although the total system costs in the IRC baseline case are increased, these costs are less than that in the TEP case. Therefore, the MACs show negative values in all cases under the IRC baseline case. The MACs vary from 67.02 $/ton C in the IRC05 case to 7.01 $/ton C in the IRC30 case. The lowest MAC of 74.96 $/ton C is found in the IRC case.
*
*
*
*
change in gas price (725% in gas price in the TEP case), change in oil price (725% and 750% in oil price in the TEP case), change in coal price (710% in coal price in the TEP case), change in peak demand (720% in peak demand in the TEP case), and change in capacity costs of power plants that are not chosen by the IRP model.
The results of sensitivity analyses show that the variations of the peak demand directly affect the cumulative generation, CO2 emissions, and total system costs (see Table 7). As a result of the variation of peak demand from 20% to 20%, cumulative generation, cumulative CO2 emission, and total system costs would change in the range of 21% to 21%, 25% to 13%, and 22% to 25%, respectively. The variation of fuel prices likes gas, oil and coal prices has less impact on the system generation plan. The analyses of the change in capacity cost of power plants which are not chosen by the IRP model reveal that in the TEP case, the IGCC, PFBC and solar power plants are introduced in the plan if their capacity costs would be reduced by
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Table 7 Results of sensitivity analysis Parameters
Cumulative generation (% change)
Cumulative CO2 (% change)
Cumulative costs (% change)
TEP
TEP
TEP
IRC
IRC
IRC
Gas price +25% 25%
0.00 0.00
0.00 0.00
4.26 15.10
5.21 13.25
4.73 8.59
4.74 8.66
Oil price +25% 25% +50% 50%
0.00 0.00 0.00 0.00
0.00 0.00 0.00 0.00
1.28 9.70 0.66 8.34
0.18 10.64 1.24
5.69 5.03 5.48 13.49
5.67 5.03 5.48
Coal price +10% 10%
0.00 0.00
0.00 0.00
12.05 3.11
9.11 4.04
1.82 2.08
1.58 1.93
19.99 20.00
21.40 21.39
13.11 23.09
17.89 25.36
23.74 21.45
24.77 22.32
0.00 0.00 0.00
0.00 0.00 0.00
0.89 0.01 0.02
0.43 0.19 0.06
0.26 0.02 0.02
0.00 0.01 0.03
Peak demand +20% 20% Capital cost Reduction of IGCCa Reduction of PFBCb Reduction of Solarc
Notes: + stands for an increment; stands for a decrement. a 50% of capital cost is reduced in both the TEP case and the IRC case. b 50% of capital cost is reduced in both the TEP case and the IRC case. c 50% of capital cost is reduced in the TEP case while 20% of capital cost is reduced in the IRC case.
approximately 50%. In the IRC case, the IGCC and PFBC options are selected when their capacity costs are reduced by approximately 50% except the solar power plant which is decreased only 20%.
6. Conclusions The results of least-cost expansion plan reveal that the CO2 emission and the other harmful emissions could be avoided through both clean supply-side and DSM options. In the planning horizon the cumulative generation in the IRC case is less than the TEP case by 6.5%. As a result, the cumulative CO2 emission could be decreased by 8.4% through the combination of DSM and clean supply-side options in the IRC case compared to the TEP case. In addition, SO2 and NOx emissions are also mitigated. When the CO2 limitation is introduced along with clean supply-side options, the number of committed biomass-based plants is increased in order to meet the CO2 reduction targets. The results of the cases with CO2 limitations indicate that the biomass-based plant has high potential to mitigate CO2 from the power sector in Thailand but its high capacity cost results in high total system and long run average
costs. Moreover, the feasibility of biomass supply in Thailand should be taken into consideration. In addition, The solar power and clean-coal technologies (IGCC and PFBC) which have high potential to reduce CO2 emissions are not selected in all cases due to their high total system costs. However, in the sensitivity analyses those plants would be introduced in the plan if their capacity cost are decreased by approximately 50% of their current cost. The results of the total system cost and marginal abatement cost of CO2 emission show that these costs in the IRC baseline cases are lower than that in the TEP baseline cases especially in the IRC case (without CO2 limitation). As a result of this study, it reveals that the IRC case is the most appropriate plan to CO2 mitigation in Thailand.
Acknowledgements This work is in the framework of the Asian Regional Research Program in Energy, Environment and Climate (ARRPEEC) funded by the Swedish International Development Co-operation Agency (Sida). However, only the authors are responsible for the views expressed in the paper and for any errors.
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Energy Policy 32 (2004) 83–90
CO2 mitigation and power generation implications of clean supplyside and demand-side technologies in Thailand Somporn Tanatvanita, Bundit Limmeechokchaia,*, Ram M. Shresthab a
Sirindhorn International Institute of Technology, Thammasat University, P.O. Box 22 Thammasat Rangsit Post Office, Pathumthani 12121, Thailand b Energy Program, Asian Institute of Technology, P.O. Box 4, Klong Luang, Pathumthani 12120, Thailand
Abstract The CO2 mitigation from the power sector in Thailand can be accomplished through both the technological substitutions in supply-side options, and the reduction of power generation through adoption of demand-side-management options. The traditional power generation expansion planning has focused only on supply-side options. However, in this study both supply-side and demand-side options are simultaneously considered in a long-term integrated resource planning model, to determine the least-cost options. Results of the analyses show that during 2003–2017 the use of efficient demand-side technologies and the efficient power generation technologies would reduce CO2 emission by 8.4% compared to the base case. When CO2 reduction targets are introduced, the installed capacity of and generation from clean supply-side technologies are found to increase. The long run average cost in the base case is found to increase from 3.10 to 3.22 US cents/kWh if the target of CO2 emission reduction by 30% is to be achieved. In addition, the sensitivity analyses are carried out to determine the effect of some parameters on the generation plan. r 2002 Elsevier Science Ltd. All rights reserved. Keywords: Clean supply-side option; Demand-side management; Integrated resource planning
1. Introduction In 1999, the power sector accounted for 33% of the total primary energy consumption in Thailand. It is also the largest contributor of CO2 emission (DEDP, 1999). In Thailand the rapid growth in electricity requirements has had a significant impact not only on the electric utility in terms of electricity generation expansion planning but also on related environmental emissions. Because of the limitation of fossil fuel resources and the problems of air pollution, the utilities need a sustainable expansion plan to provide adequate electricity supply capacity in the future and mitigate environmental emissions, particularly the CO2 emissions. To achieve a sustainable expansion plan, energy management programs such as demand-side management (DSM), energy conservation, and fuel switching have been implemented in Thailand (OEPP, 2000; NEPO, 1997).
*Corresponding author. Tel.: +662-986-9009x2206; fax: +662-9869113. E-mail addresses: [email protected] (B. Limmeechokchai), [email protected] (R.M. Shrestha).
In the context of power generation, the supply-side options and DSM programs are considered as the viable options to mitigate CO2 emission. CO2 emission could be mitigated through technological substitutions towards cleaner and more efficient supply-side options in power generation while it could also be mitigated through DSM options that reduce electricity demand (Shrestha et al., 1999). Traditionally, the electricity generation expansion planning process in Thailand is to identify the sequence of generation additions resulting in meeting the forecasted demand at a minimum total system cost. While the traditional resource planning (TRP) process focuses only on the supply-side options, the integrated resource planning (IRP) process includes both the supply-side and the demand-side options to meet the forecasted demand in a least-cost manner. Therefore, both the TRP and IRP plans are investigated in this study to find out the least-cost electricity generation expansion plans and to identify the options for mitigating CO2 emission. The sensitivity analyses of the uncertainties in parameters such as fuel price, peak demand, and capital cost are also presented. In addition, the variations in expansion plans in terms of generationmix, total cost, and CO2 emission are analyzed for four different levels of CO2 emission reduction targets.
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2. Electricity sector in Thailand The existing power plants in 1998 consisted of 161 units of various generating stations with total capacity of 18,174.5 MW (excluding 0.53 MW of renewable energy). The total capacity consisted of 2874 MW (15.8%) of hydro, 6517 MW (35.9%) of conventional oil/gas and lignite-fired plants, 5074 MW (27.9%) of combined-cycle plants, 892 MW (4.9%) of gas turbine and diesel plants, and 2818 MW (15.5%) of capacity purchased from other power suppliers (EGAT, 1999a). 2.1. DSM in Thailand Thailand became the first country in Asia to formally adopt a nationwide DSM master plan. In 1992, the Royal Thai Government approved the program budget of US$ 189 million to implement DSM programs in the country. The World Bank, under the auspices of the Global Environment Facility (GEF), has also supported the project with a grant funding of US$ 15.5 million. For over 8 years, after EGAT had launched the DSM program in 1992, various DSM programs had been implemented with aims to promote the use of energy efficient appliances, to create the attitude of energy conservation, and to support and pursue energy efficiency and load management technologies. EGAT has implemented DSM programs in three main sectors: residential, commercial, and industrial sectors. The DSM programs included the following: *
* * * * *
energy efficient fluorescent lamp program, known as thin tube program, refrigerator efficiency labeling program, air conditioner efficiency labeling program, high efficiency motor program, compact fluorescent lamp program, and cool storage program.
For the thin tube program, EGAT engaged in direct negotiations with Thai lamp manufacturers to voluntarily agree to ban the production of low-efficiency lamps and only produce high-efficiency lamps, which emit the equipment lumen output. By mid-1995, all lamp manufacturers and importers complied with the agreement. So, the impact of this program has been substantial, because the efficiency of all lamps sold in Thailand was improved at up-stream. For refrigerators and air conditioners, EGAT adopted a product efficiency labeling approach, where all participating brands of refrigerators and air conditioners would carry a label, which indicates the efficiency label, annual kWh consumption and the energy saving estimates. (Ratanopas, 1997). To date, the successful campaigns of DSM programs in Thailand are the labeling campaign for efficient
refrigerators and air-conditioners, which has now become a symbol of efficiency and energy saving. The major DSM campaigns are composed of the energyefficient thin tube program, refrigerator labeling program, and air conditioner labeling program. These programs have resulted in the total saving of 566 MW of peak demand, 3140 GWh of energy and the reduction of 2.32 million tonnes of carbon dioxide emissions (EGAT, 2000). Therefore, these major DSM programs will be continuously implemented well into the future to achieve the perpetual energy efficiency. Moreover, the electricity efficient ballasts and the high efficiency electric motors could be included in the campaign soon.
3. Data and assumptions in electricity generation expansion planning In this study, the analytical tool used to find out the least-cost power generation expansion plans is the IRP model, developed by Shrestha et al. (2001). The IRP model considers both demand- and supply-side options to meet the electricity demand in a least-cost manner, subject to a given emission reduction target. The leastcost plans are divided into two main categories: the TRP plan and the IRP plan. In the TRP plan, only supplyside options are considered. In the IRP plan, five DSM options are included in the analyses to simultaneously compete with the supply-side options. The CO2 reduction targets of 5%, 10%, 20% and 30% in the context of mitigation of greenhouse gas emissions from the power sector are introduced to both the TRP and the IRP plans. The emissions of CO2 SO2 and NOx are calculated based on emission factors provided by the Intergovernmental Panel on Climate Change (IPCC, 1996). The important assumptions and constraints used in the analyses are as follows: *
*
*
A planning horizon of 15 years (i.e., 2003–2017) with the base year in 1998 is considered. The minimum and maximum reserve margins of 15% and 25% are adopted (EGAT, 1999a). The natural gas imported from neighboring countries is considered to be enough for approximately 11,650 MW of additional capacity (EGAT, 1999a).
3.1. Load forecast data The annual peak loads figures used in the study correspond to the load forecast for the period 2003–2011 under the moderate economic recovery scenario of the Electricity Generating Authority of Thailand (EGAT, 1999a). The growth rate of peak demand during 2003– 2011 is assumed to continue during 2012–2017 in deriving the load forecast at a constant system load
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factor of 0.73. The peak load is expected to increase from 18,399 MW in 2003 to 39,490 MW in 2017. The load data used in the model are the average chronological load curves (CLCs) which are divided into three seasons; winter, summer, and rainy seasons. Each season is represented by one CLC of the peak day in that season.
commercial sector is not considered as an option in this study. The data on the projected stock of electric appliances, and their annual energy saving are obtained from the DSM office of EGAT. The technical details and costs of existing and efficient appliances are based on Shrestha et al. (1998) and market surveys.
3.2. Supply-side options
3.4. Cases considered in this study
3.2.1. Candidate power plants The candidate plants used in the IRP model are divided into two groups: conventional power plant options, and clean and efficient technology options (see Table 1). In Thailand, renewable energy such as biomass energy, hydro and solar-power, has been an important source of energy. These energy resources are the important options to mitigate greenhouse gases emission. Additionally the EGAT has been interested in the research and development of clean coal technology, such as integrated gasification combined cycle (IGCC) (EGAT, 1999b). The data on conventional thermal and hydropower plants are based on EGAT (1999a). While the data on clean technologies are obtained from TEI (1990) and Limmeechokchai and Chungpaibulpatana (1999).
The case studies are divided into two baseline cases: the traditional electricity planning or the TEP case and the IRP with clean supply-side options or the IRC case. The TEP case is used as a reference case for the comparison of the other cases. In the TEP case, only the clean supply-side options are considered to meet the projected demand. Whereas in the IRC case both supply- and demand-side options are considered. The clean supply-side options are also included in both the TEP case and the IRC case. In addition, four levels of CO2 limitation, 5%, 10%, 20%, and 30% are applied to the TEP case called the TEP05, TEP10, TEP20, and
3.3. DSM options Five DSM options are considered in this study, which included efficient lightings, efficient refrigerators, and efficient air-conditioner in the residential sector, efficient air-conditioner in the commercial sector, and efficient electric motors in the industrial sector. (see details in Table 2). The efficient fluorescent tubes are considered to have completely replaced the use of conventional fluorescent tubes in the commercial sector. Since no manufacturers produced the conventional tubes after the year 1995. Thus, the efficient lighting program in the
Table 2 Demand-side-management options considered in the IRP model Sector
DSM options
Residential
DSM1: replacement of 20 and 40-W fluorescent lamps with 18 and 36-W fluorescent lamps DSM2: replacement of conventional refrigerator with the most energy efficient Refrigerator DSM3: replacement of conventional airconditioner with the most energy efficient airconditioner DSM4: replacement of conventional airconditioner with the most energy efficient airconditioner DSM5: replacement of 5–500 hp conventional motors with the energy efficient motors
Commercial
Industrial
Table 1 Candidate plants in the IRP model Plant type
Fuel type
Capacity (MW)
Heat rate (kcal/kwh)
CO2 emission factor (g/kwh)
Traditional plants Coal based Coal based Oil based Gas turbine Combined cycle
Imported coal Imported coal Fuel oil Diesel Natural gas
700 1000 1000 200 600
2391 2321 2340 2742 1859
947 919 636 860 473
Clean supply side plants IGCC PFBC Biomass Solar power Mini-hydro power
Imported coal Imported coal Biomass — —
500 500 100 1 10
2200 2195 2378 — —
821 903 0 0 0
Notes: IGCC stands for integrated gasification combined cycle; PFBC stands for pressurized fluidized bed combustion.
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TEP30 cases, respectively, and the IRC case called the IRC05, IRC10, IRC20 and IRC30, respectively.
the total capacity of coal-based plants in all cases, presented in Table 4. Substitutions for coal-based plants are gas-based and biomass-based plants in both the TEP case and the IRC case with CO2 limitations. Although the CO2 emission constraints are applied in the TEP and IRC cases, the solar power, IGCC and PFBC plants are not selected due to their high total system costs compared to other clean supply-side options. In the IRC case, the additional capacity in the planning horizon is less than the TEP case due to end use energy savings with the use of DSM options. In the IRC case, and the 1IRC case with CO2 limitations, the cumulative generation is decreased by an average of 6.5% compared to the TEP case, as shown in Table 5. The peak load avoided due to the use of efficient air conditioners in both residential and commercial sectors account for approximately 79% of the total peak load avoided. The corresponding figures for efficient refrigerators, motors and lamps are about 10%, 8% and 3%, respectively.
4. Results of the least-cost analyses 4.1. Utility planning implications The results of the least-cost plans from the IRP model reveal that the coal-based power plants take the largest share in the total additional capacity in the TBP case and also in the IRC case, presented in Table 3. In the TEP case, 5 units of 100-MW biomass-based plants and 10 units of 10-MW hydro power plants are committed, while in the IRC case, 6 units of 100-MW biomass-based plants and 10 units of 10-MW hydro power plants are committed. The introduction of CO2 limitation shifts the power plant types from high-carbon-content fuelbased plants to low-carbon-content fuel-based plants. The higher the percentage of CO2 limitation, the lower is
Table 3 Number of committed plants in all cases Case study
TEP TEP05 TEP10 TEP20 TEP30 IRC IRC05 IRC10 IRC20 IRC30
Total number of committed power plants (2003–2017) 1000-MW coal
700-MW coal
600-MW CC
100-MW biomass
10-MW hydro
20 20 16 14 11 20 20 19 15 12
6 — 3 1 1 — 1 — 1 1
15 19 19 19 19 19 19 19 19 19
5 20 39 73 103 6 — 17 49 78
10 10 10 10 10 10 10 9 10 10
Additional capacity (MW)
Cumulative generation (TWh)
33,800 33,500 33,500 33,500 33,500 32,100 32,200 32,190 32,100 32,000
3096 3096 3096 3096 3096 2894 2894 2894 2894 2894
Notes: CC stands for combined-cycle power plant.
Table 4 Capacity-mix by plant types in 2017 Case study
TEP TEP05 TEP10 TEP20 TEP30 IRC IRC05 IRC10 IRC20 IRC30
Total capacity requirement (MW)
49,706 49,406 49,806 49,406 49,406 48,006 48,106 48,096 48,006 47,906
Capacity-mix (%) Coal-fired
Oil-fired
CC
GT
IPP
Hydro
Biomass
52.31 44.12 40.28 33.40 27.32 45.41 46.77 46.25 36.45 30.27
5.98 6.01 6.01 6.01 6.01 6.19 6.17 6.18 6.19 6.20
26.55 31.57 31.57 31.57 31.57 32.49 32.43 32.43 32.49 32.56
0.31 0.31 0.31 0.31 0.31 0.32 0.32 0.32 0.32 0.32
7.84 7.89 7.89 7.89 7.89 8.12 8.10 8.10 8.12 8.13
6.01 6.04 6.04 6.04 6.04 6.22 6.21 6.19 6.22 6.23
1.01 4.05 7.89 14.78 20.85 1.25 0.00 3.53 10.21 16.28
Notes: CC stands for combined-cycle power plant; GT stands for gas turbine power plant; IPP stands for independent power producer.
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4.2. Environmental implications Energy savings through DSM options and the substitution of generation technologies from high carbon intensive fuel-based plant to low carbon intensive fuel- based plants directly affect environmental emissions especially the CO2 emission. The CO2 mitigations in all cases are compared to the TEP case. In the IRC case, 8.4% of CO2 emission are decreased by the reduction of electricity generation (see Fig. 1). When the CO2 limitations are introduced, the CO2 emissions decrease by 9.0%, 14.2%, 24.6% and 34.1% in the TEP05, TEP10, TEP20 and TEP30 cases, respectively. In the IRC case with CO2 limitations, the CO2 emissions are decreased by 9.3%, 14.4%, 24.2% and 34.1% in the IRC05, IRC10, IRC20 and IRC30 cases, respectively. In addition to the CO2 mitigation, other harmful emissions such as SO2 and NOx are also mitigated (see Fig. 2). The Table 5 Cumulative generation avoided and peak load avoided in 2017 DSM options
Peak load avoided (MW) in 2017 IRC
DSM1 DSM2 DSM3 DSM4 DSM5 Total peak load avoided in 2017 Cumulative generation avoided during 2003– 2017 (GWh)
36.4 129.2 233.7 764.4 99.1 1262.8
201,742
IRCO5 36.4 129.2 233.7 764.4 99.1 1262.8
201,742
IRC1O 36.4 129.2 233.7 764.4 99.1 1262.8
201,742
IRC2O 36.4 129.2 233.7 764.4 99.1 1262.8
201,742
IRC3O 36.4 129.2 233.7 764.4 99.1 1262.8
201,742
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SO2 and NOx mitigations correspond to the CO2 mitigations in all cases. However, the shift of power generation technologies from conventional technologies to clean technologies results in an increase in total system costs because the total system costs of clean technologies are higher than the conventional technologies. 4.3. Economic implications In the economic perspective, the total expenditure including DSM costs in the IRC case in the planning horizon are less than those in the TEP case by US$ 1592 million due to the reduction of electricity requirement, see Table 6. When different levels of CO2 limitation are introduced, the total costs in all cases increase owing to the increase of capital cost of power plants. The total costs increase by 0.7, 1.2%, 2.4% and 3.9% in the TEPO5, TBP10, TBP20 and TBP30 cases, respectively, compared to the TEP case. Although the total costs in the IRC with CO2 limitation cases increase, the total cost in those cases are still lower than that in the TEP case. The major reason is the less electricity generation. The results of those costs and the quantity of electricity generation directly effect the long run average cost (LRAC). The LRACs in all cases are higher than that in the TEP case. In both the TEP30 and the IRC30 cases, the LARCs increase approximately 4.0% compared to the TEP case. In the IRC case, however, the LRACs increase only 0.6% compared to the TEP case. 4.4. Marginal abatement cost (MAC) of CO2 As the previous mentioned, the introduction of CO2 limitation results in an increase in total system cost in all
Fig. 1. Cumulative CO2 mitigation in all cases during 2003–2017 compared to the base case.
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Fig. 2. Cumulative SO2 and NOx mitigation in all cases during 2003–2017 compared to the base case.
Table 6 Cumulative costs in all cases during 2003–2017 Case study
TEP TEP05 TEP10 TEP20 TEP30 IRC IRC05 IRC10 IRC20 IRC30
5. Sensitivity analyses
Coat components
Capital cost (106 US$)
Fuel and O&M (106 US$)
DSM cost (106 US$)
Total cost (106 US$)
5075 5331 5698 6357 7235 4602 4509 4756 5402 6259
25,092 25,032 24,829 24,535 24,119 23,795 23,897 23,785 23,494 23,101
— — — — — 178 178 178 178 178
30,167 30,363 30,527 30,892 31,354 28,574 28,584 28,719 29,074 29,538
LRAC (cents/ kWh)
In this study the sensitivity analysis is performed to examine the effect of variations in major parameters on utility planning, environmental, and economic implications. Sensitivity analyses are conducted for the TEP case and the IRC case. The five major parameters considered in sensitivity analyses are as follows:
3.10 3.12 3.14 3.17 3.22 3.12 3.12 3.13 3.17 3.22
*
Note: LRAC stands for long run average cost.
cases. The MAC in dollars per ton of carbon ($/ton C) is vary with the levels of CO2 limitation. In this study, the considered MAC is based on the TEP case. In the TEP case with CO2 limitation, the MACs range from 8.69 $/ton C at 5% CO2 limitation to 13.26 $/ton C at 30% CO2 limitation. Although the total system costs in the IRC baseline case are increased, these costs are less than that in the TEP case. Therefore, the MACs show negative values in all cases under the IRC baseline case. The MACs vary from 67.02 $/ton C in the IRC05 case to 7.01 $/ton C in the IRC30 case. The lowest MAC of 74.96 $/ton C is found in the IRC case.
*
*
*
*
change in gas price (725% in gas price in the TEP case), change in oil price (725% and 750% in oil price in the TEP case), change in coal price (710% in coal price in the TEP case), change in peak demand (720% in peak demand in the TEP case), and change in capacity costs of power plants that are not chosen by the IRP model.
The results of sensitivity analyses show that the variations of the peak demand directly affect the cumulative generation, CO2 emissions, and total system costs (see Table 7). As a result of the variation of peak demand from 20% to 20%, cumulative generation, cumulative CO2 emission, and total system costs would change in the range of 21% to 21%, 25% to 13%, and 22% to 25%, respectively. The variation of fuel prices likes gas, oil and coal prices has less impact on the system generation plan. The analyses of the change in capacity cost of power plants which are not chosen by the IRP model reveal that in the TEP case, the IGCC, PFBC and solar power plants are introduced in the plan if their capacity costs would be reduced by
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Table 7 Results of sensitivity analysis Parameters
Cumulative generation (% change)
Cumulative CO2 (% change)
Cumulative costs (% change)
TEP
TEP
TEP
IRC
IRC
IRC
Gas price +25% 25%
0.00 0.00
0.00 0.00
4.26 15.10
5.21 13.25
4.73 8.59
4.74 8.66
Oil price +25% 25% +50% 50%
0.00 0.00 0.00 0.00
0.00 0.00 0.00 0.00
1.28 9.70 0.66 8.34
0.18 10.64 1.24
5.69 5.03 5.48 13.49
5.67 5.03 5.48
Coal price +10% 10%
0.00 0.00
0.00 0.00
12.05 3.11
9.11 4.04
1.82 2.08
1.58 1.93
19.99 20.00
21.40 21.39
13.11 23.09
17.89 25.36
23.74 21.45
24.77 22.32
0.00 0.00 0.00
0.00 0.00 0.00
0.89 0.01 0.02
0.43 0.19 0.06
0.26 0.02 0.02
0.00 0.01 0.03
Peak demand +20% 20% Capital cost Reduction of IGCCa Reduction of PFBCb Reduction of Solarc
Notes: + stands for an increment; stands for a decrement. a 50% of capital cost is reduced in both the TEP case and the IRC case. b 50% of capital cost is reduced in both the TEP case and the IRC case. c 50% of capital cost is reduced in the TEP case while 20% of capital cost is reduced in the IRC case.
approximately 50%. In the IRC case, the IGCC and PFBC options are selected when their capacity costs are reduced by approximately 50% except the solar power plant which is decreased only 20%.
6. Conclusions The results of least-cost expansion plan reveal that the CO2 emission and the other harmful emissions could be avoided through both clean supply-side and DSM options. In the planning horizon the cumulative generation in the IRC case is less than the TEP case by 6.5%. As a result, the cumulative CO2 emission could be decreased by 8.4% through the combination of DSM and clean supply-side options in the IRC case compared to the TEP case. In addition, SO2 and NOx emissions are also mitigated. When the CO2 limitation is introduced along with clean supply-side options, the number of committed biomass-based plants is increased in order to meet the CO2 reduction targets. The results of the cases with CO2 limitations indicate that the biomass-based plant has high potential to mitigate CO2 from the power sector in Thailand but its high capacity cost results in high total system and long run average
costs. Moreover, the feasibility of biomass supply in Thailand should be taken into consideration. In addition, The solar power and clean-coal technologies (IGCC and PFBC) which have high potential to reduce CO2 emissions are not selected in all cases due to their high total system costs. However, in the sensitivity analyses those plants would be introduced in the plan if their capacity cost are decreased by approximately 50% of their current cost. The results of the total system cost and marginal abatement cost of CO2 emission show that these costs in the IRC baseline cases are lower than that in the TEP baseline cases especially in the IRC case (without CO2 limitation). As a result of this study, it reveals that the IRC case is the most appropriate plan to CO2 mitigation in Thailand.
Acknowledgements This work is in the framework of the Asian Regional Research Program in Energy, Environment and Climate (ARRPEEC) funded by the Swedish International Development Co-operation Agency (Sida). However, only the authors are responsible for the views expressed in the paper and for any errors.
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