Assessment of Energy Saving Potential in the Thai Residential Sector: Long-range Energy Alternatives Planning Approach

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1 The 2 nd Joint International Conference on Sustainable Energy and Environment (SEE 26) F-4 (O) 21-2 November 26, Bangkok, Thailand Assessment of Energy Saving Potential in the Thai Residential Sector: Long-range Energy Alternatives Planning Approach Bundit Limmeechokchai 1,* and Pimporn Chaosuangaroen 2 1 Sirindhorn International Institute of Technology, Thammasat University, Pathumthani, Thailand 2 The Joint Graduate School of Energy and Environment, King Mongkut s University of Technology Thonburi, Bangkok, Thailand Abstract: The total final energy consumption in Thailand rised up from 47,86 ktoe to 6,26 ktoe during 2 to 24, with an annual average growth rate of.96 %, while the annual growth rate of gross domestic product (GDP) equaled to.16% in the same period. During , the elasticity of energy demand was found to be 1.4:1. In 2, Ministry of Energy set a target to promote renewable energy and energy efficiency in the Renewable Portfolio Standard (RPS) and increase usage of renewable energy from.% to 8% within year 211, and reduce energy elasticity to 1:1. To achieve the target, Thai government has to overcome barriers in 2 major areas, which are renewable energy and energy efficiency. Thus, the development in energy policy measures is required in order to promote the renewable energy utilization and increase energy efficiency in the consumption sectors. Since non-electricity is the main form of energy that consumed in the residential sector, therefore, the efficiency improvement of cooking stove results in the largest amount of energy savings. The total energy saving in the residential sector is 7,291.6 ktoe, accounting for 29.42% of total residential final energy consumption in 22. This scenario also helps in the reduction in the largest amount of carbon dioxide emission. Keywords: Energy Saving Potential, Energy Consumption in Thai Residential Sector, Demand-Side-Management (DSM), Longrange Energy Alternatives Planning Models (LEAP), CO 2 Mitigation. 1. INTRODUCTION 1.1 Energy use pattern in the residential sector The changes in energy consumption patterns can be explained by two factors. The natural increase based on population growth and demographic changes such as household size and the changes in age groups is the first factor. Another factor is the rise of economic activity and development. The population of Thailand grew up from 199 to 2 with an annual growth rate of 1.16%. The increasing in population and economic expansion led to rapid growth in energy consumption. In 24, the total final energy consumption in the residential sector was 8,7 ktoe, accounted for 1.9% of the total final energy consumption. And the electricity consumption in this sector equals to 24,74 GWh, accounted for 21.% of the total electricity consumption for the whole country in the same period. [1-2] For the residential sectors, the electricity demands are mainly consumed by air conditioners and refrigerators. However, the main energy consumed in this sector is based on non-electricity, the proportions of non-electricity demand was 74.81% of total energy consumption in the residential sector in 24. The main utilization of non-electricity in the residential sector is used in cooking appliances, such as LPG cooking stove, Charcoal stove, etc. 1.2 End-use model In the end-use projection, a breakdown by sectors, activities, and end-uses are required in order to determine which end-uses are the most relevant. Once their magnitudes are quantified; therefore, it becomes more accurately to evaluate the potentials for energy efficiency improvement. Table 1 shows the breakdown of end-use model in this study. [] Table 1 Information required by end-use model Consumer class Income level (Baht/month) End-use Technology Fluorescent Residential sector High up to 7, Medium 2, 7, Medium 1 1,, Low 1, Lighting equipment Electric heating device Electric motor Incandescent Compact fluorescent Rice cooker Water heater Electric cooking appliance Electric iron Electric fan Water pump Washing machine Electric tools Corresponding author: bundit@siit.tu.ac.th 1

2 The 2 nd Joint International Conference on Sustainable Energy and Environment (SEE 26) F-4 (O) 21-2 November 26, Bangkok, Thailand Table 1 Information required by end-use model (continued) Consumer class Income level (Baht/month) End-use Technology Electric cooling device Air conditioner Refrigerator TV Residential sector High up to 7, Medium 2, 7, Medium 1 1,, Low 1, Electric load Non-electricity appliance VDO Radio Charcoal stove LPG stove Wood stove Kerosene Paddy husk Charcoal stove 1. Objective of bottom up analysis Major objective of bottom-up analysis is to construct a quantitative description of the energy conversion and uses technological structure. Firstly, an estimation of demand for each energy service is required, such as comfort and mobility. From this foundation, the future scenarios can be created by using different combinations of energy demand and supply technologies. [6] Scenario analysis is one of the comparisons of alternative combination of technological options in order to provide the same energy services level. Fundamentally, base line scenario is defined as the starting point in the analysis of energy-efficiency improvements. In the base case, the energy demand projection is based on the historical trend or the amount of future energy demand that will extended from the present trends, where it is assumed to have no implementations of energy conservation or energy-efficiency improvements. Fig. 1 Structure of the residential energy consumption model 2. METHODOLOGY To estimate the potential of energy saving, the projection of energy demand was grouped into two cases: the base-case or businessas-usual (BAU) scenario and the energy efficiency case or alternative scenario. 2.1 Analytical tool: Long-range Energy Alternatives Planning (LEAP) model The Long-ranged Energy Alternatives Planning (LEAP) model has been developed by the Stockholm Environment Institute- Boston (SEI-B). It is suitable for a various tasks including, energy consumption forecasting, environmental emission analysis, integrated resource planning, and energy scenario studies. The main concept of LEAP is an end-use driven scenario analysis. Besides, the model contains the technology and environmental data based (TED) that was used to estimate the environmental emissions from the energy utilization. 2

3 The 2 nd Joint International Conference on Sustainable Energy and Environment (SEE 26) F-4 (O) 21-2 November 26, Bangkok, Thailand In this study, the current energy situation is created first in the starting year (2), and a base line scenario can be developed by assuming constant of current trends. The data required for LEAP model inlcude the base year and any of the future years. By using the function such as extrapolation or interpolation or growth rate method, the energy demand projection and environmental emission can be estimated for the other years. In this study, carbon dioxide emission is considered by using the emission factors based on values that recommended by the Intergovernmental Panel on Climate Change (IPCC Tier 1 Default Emission Factors). [8] 2.2 Scenario construction and assumption used in this study Business-as-usual Scenarios The energy demand projection in the business-as-usual case for this study is based on the historical trend with the assumptions in the following table. The annual growth rate of number of household is equal to 1.9% and the growth rate of Gross Domestic Product (GDP) equals to.%. In this study, the penetration levels of each end-use device are assumed to be 1%. The growth rate of energy consumption in BAU for each sub-sector has been applied following the current trend from 2 to 24. [1, 2] Table 2 The assumptions used in the study for sub-sectors in the residential sector Sub-sectors Income (Baht/month) Share of income class (%) Year 2 Year 211 Year High income up to 7, Medium income 2, 7, Medium income 1 1,, Low income 1, Alternative Scenarios In this study, the efficiency improvement of six main appliances, including lighting equipment, electric heating device, electric motor, electric cooling device, electric load, and cooking stove are applied, shown in table, table 4. [4-, 7] For the scenario of the efficiency improvement of lighting devices, in case of fluorescent, the substitution of higher efficient lighting will occur in periods. The penetration level of high efficient lighting devices will replace the conventional light bulbs with the constant rates of 1, 2, and % of the total fluorescent market in 211, 216, and 22, respectively. While in the case of incandescent, compact fluorescent will replace the incandescent light with the constant rate of, 12., and 2% of the total incandescent market in the same period. Since the high efficient lighting equipments have the barrier of high cost, therefore, the assumption of the penetration level of % of the market refers to the % remain of the conventional lighting equipments, which have lower cost than the efficient one. Efficient Lighting Equipment Fluorescent 16W Fluorescent 18W Table Efficient lighting equipment scenario construction with the assumptions Changes in Penetration level (%) DSM Base year Period 1 Period Replace with FL 16W Period Fluorescent 2W Fluorescent 6W - Replace with FL 2W Incandescent 6W Incandescent 1W Compact Fluorescent 12W Compact Fluorescent 2W - Replace with CF 12W - Replace with CF 2W For other scenarios, the replacement of the high efficiency device in each sector is assumed to be linear. In each scenario, each device has 2 different efficiency improvements. In the first period (26-211), only the efficient 1 device, which has the higher efficiency than the conventional ones, for example, efficient 1 of heating device is the 1% efficiency improvement from conventional device, and will replace the conventional device. While in the second period ( ), the efficient 2 device or the higher efficiency improvement devices than efficient 1 device, will substitute the conventional ones and increase the shares until all household devices are the efficient devices. For the efficiency improvement of cooking stoves, only charcoal, LPG, and wood stove are considered in this scenario since they have the largest share of non-electricity consumption in the household.

4 The 2 nd Joint International Conference on Sustainable Energy and Environment (SEE 26) F-4 (O) 21-2 November 26, Bangkok, Thailand Scenario Efficient Heating device Efficient Electric motor Efficient Cooling device Efficient Electric load Efficient Cooking stove Charcoal stove LPG stove Wood stove Table 4 Assumptions in alternative scenarios Penetration level (%) Efficiency improvement (%) Base year 2. RESULTS AND DISCUSSION Period Period Energy conservation perspective The implement of high efficiency devices in the residential sector help in the reduction of electricity consumption in households. The most effective scenario for the reduction in electricity consumption is the efficiency improvement of electric cooling device, which results in the electricity reduction of 29.7, 92., and 1,28.4 GWh in the year 211, 216, and 22, respectively. The next effective scenario is the efficiency improvement of lighting equipments that help in the electricity saving of 77.2, 299., and GWh in the same period. The improvement of cooking stove gives the largest amount of energy saving in the residential sector approximated 1,846.4, 4,496.7, and 7,291.6 ktoe, which accounting for 1.1%, 27.74%, and 29.42% of total energy consumption from household in year 211, 216, and 22, respectively. Table Energy demand the residential sector in the selected years Scenario Energy demand (ktoe) Business as usual (BAU) 1,68 1,66 1,874 18,941 24,78 Efficient in Non-electric device 1,68 1,66 12,28 14,44 17,492 Efficient in Lighting 1,68 1,66 1,868 18,91 24,71 Efficient in Heating device 1,68 1,6 1,87 18,928 24,766 Efficient in Electric motor 1,68 1,66 1,874 18,99 24,781 Efficient in Electric load 1,68 1,6 1,866 18,917 24,71 Efficient in Cooling device 1,68 1,62 1,846 18,861 24,

5 The 2 nd Joint International Conference on Sustainable Energy and Environment (SEE 26) F-4 (O) 21-2 November 26, Bangkok, Thailand, Electricity saving (GWh) 2, 2, 1, 1, Efficient in Cooling device Efficient in Electric load Efficient in Electric motor Efficient in Heating device Efficient in Lighting system Year Fig. 2 Electricity saving potential in each scenario in selected years.2 Environmental emission perspective For the efficiency improvement of non-electricity devices or cooking stoves, it was not only help in the reduction of energy consumption from the residential sector but it also results in the mitigation of environmental emission that causes the global warming situation from energy utilization. The amount of Carbon dioxide (CO 2 equivalent) emission is considered in this study, which in the efficiency improvement in non-electricity device scenario is the most effective option to help in the reduction of CO 2 emission. In the year 22, approximately.42 million tonnes of CO 2 emission will be mitigated when compared with the BAU case, accounting for 48.14% of total amount of CO 2 emission in the residential sector. Million Tonnes Efficient in all non-electric devices Business as usual Years Fig. Global warming potential (CO 2 equivalent) for the selected scenarios

6 The 2 nd Joint International Conference on Sustainable Energy and Environment (SEE 26) F-4 (O) 21-2 November 26, Bangkok, Thailand 4. CONCLUSION In the residential sector, since non-electricity is the main energy consumed in this sector. Thus, the efficiency improvement program for cooking stoves such as charcoal, LPG, and wood stoves, is the most effective option to save the energy consumption in households, resulting in the largest amount of energy saving approximated to 7,291.6 ktoe or accounted for 29.42% of total energy consumption in the residential sector in 22. Moreover, the efficiency improvements of electric cooling devices are the most effective options for the reduction of electricity consumption in households. It helps in the reduction of CO 2 emission approximated.42 million tonnes in 22, which accounting for 48.14% of total amount of CO 2 emission from the residential sector.. ACKNOWLEDGMENTS The authors would like to thank the Joint Graduate School of Energy and Environment (JGSEE), King Mongkut's University of Technology Thonburi (KMUTT) for providing the fund for this study. The authors also would like to thank Energy Policy and Planning Office (EPPO), and Thailand Research Fund (TRF) for the support on this research work. 6. REFERENCES [1] Department of Alternative Energy Development and Efficiency (DEDE). (24), Thailand Energy Situation report, Ministry of Energy, Thailand. [2] Department of Alternative Energy Development and Efficiency (DEDE). (24), Electric Power in Thailand 24, Ministry of Energy, Thailand. [] National Statistical Office (NSO). (24), Report of the 24 Household Socio-Economic Survey: Whole Kingdom, Ministry of Information and Communication Technology, Thailand. [4] Santisirisomboon, J., et. Al., (21), Environmental emission abatement strategies in the energy sector: the integrated economic, environment and energy approach, Thesis ME-PHD-21-1, Sirindhorn International Institute of Technology, Thammasat University. [] Santisirisomboon, J., et. Al., (1999), Impacts of efficient electric end uses on power generation planning and emissions: a case study of residential sector in Thailand, Research and Development Journal of the Engineering Institute of Thailand, 1, pp [6] Swisher, J. and Jannuzzi, G. and Redlinger, R. (1997), Tools and Methods for Integrated Resource Planning: Improving Energy Efficiency and Protecting the Environment. Rinø National Laboratory: Grafisk Service, Denmark. [7] Tanatvanit, S., et. Al., (24), Mitigating environmental emissions from the energy sectors: analysis of technical and policy options in Thailand, Thesis ME-PHD-24-1, Sirindhorn International Institute of Technology, Thammasat University. [8] Stockholm Environment Institute (SEI), Long-range Energy Alternative Planning System (LEAP) Version 26.27, Stockholm Environment Institute, Boston Center, USA, Available from: 6