Economy-Wide Impacts of PV Electricity Generation in Thailand: An Input-Output Analysis

Transcription

1 conomy-wide Impacts of PV lectricity Generation in Thailand: An Input-Output Analysis Pawinee Suksuntornsiri 1, Warunee Tia 2 and Bundit Limmeechokchai 3,* 1 Faculty of ngineering, Burapha University, Chonburi, Thailand 2 School of nergy and Materials, King Mongkut s University of Technology Thonburi, Bangkok, Thailand 3 Sirindhorn International Institute of Technology, Thammasat University, Pathumthani, Thailand Abstract: The primary energy supply in Thailand has been mainly depended on imported fossil fuels. In 2005 commercial energy including coal, oil and natural gas shared about 83.5% in the total primary energy supply of the country. In 2005, electricity generated from hydro energy was accounted for 4.4% of national grid generation. In addition, renewable fuel consumption (solar, geothermal, paddy husk, bagasse, fuel wood, garbage, and agricultural waste) for electricity generation was accounted for only 3.1% in the total fuel consumption for electricity generation. However, Thailand has a high potential for solar energy utilization since Thailand situates in the hot and humid climate at latitude between 5-20 N. The average total solar radiation is found to be 18.2 MJ/m 2 -day. In 2005, the Ministry of nergy set a target of for renewable portfolio standard (RPS) to be 8% in One of the policies to achieve this target is to promote the rooftop PV for rural households and PV power plants. However, the assessment of the economy-wide impact of PV systems is necessary for proper policy formulation. This paper presents the energy input-output (IO) analysis of the economy-wide impact of policy on promotion of PV electricity generation in Thailand in order to propose the proper measures to achieve the RPS target. The indirect energy and indirect emissions are evaluated by using the input-output (IO) table. The input-output table in 2000 of 180 economic sectors is re-arranged and reduced to 50 sectors for this study. The revised energy IO model has been modified and also used to assess the economy-wide impacts. Though, the promotion of PV system could help Thailand to meet the target of RPS of 8% in 2011, results from IO analysis show the significant impacts of economy-wide total energy requirement, employment, and direct and indirect CO 2 emissions from PV electricity generation, which should be considered for policy on PV promotion. Keywords: Photovoltaic lectricity, Macro-conomic Impact, Total nergy Requirement, Total CO 2 mission, mployment ffect 1. INTRODUCTION Solar energy is one of the main renewable energy sources in the world. Since Thailand situates in the tropical zone, the potential of solar energy utilization is high. The average year-round solar intensity in Thailand is found to be 18.2 MJ/m 2 per day. However, the solar energy utilization for electricity generation as photovoltaic (PV) system is still costly, especially for Thailand as a PV imported country. In 2005, the PV installation in Thailand was found to be 26 MW p with about 70% of the installation is the rooftop PV system for the remote villagers [1, 2, 3]. From the study, it is estimated that in 2011 the total PV installation in Thailand will be about 60 MW p with total PV electricity generation of 87 GWh and in 2016 the total PV installation will be 120 MW p with total PV electricity generation of 175 GWh [4]. Generally renewable electricity generation is more expensive compared to traditional electricity generation. Therefore, the Thai government has to promote renewable electricity generation and provide incentive to the investors of renewable energy systems. One of the policy and measures for the renewable energy promotion is to provide the feed-in tariffs for each renewable energy system. In feed-in tariff context, the government buybacks the electricity from renewable energy systems in specified periods for activation of investment in renewable energy. The official feed-in tariffs will be given by the Ministry of nergy. In this study, two assumed feed-in tariffs are used in the analysis. The 2000 input-output (IO) table of 180 sectors was re-reduced to 50 main sectors. The revised energy IO table is used to evaluate the economy-wide impact of policy on promotion of PV in Thailand. 2. MTHODOLOGY This study employed the potential of PV installation during , presented in Table 1, for assessment of economy-wide total energy requirement, employment, and direct and indirect CO2 emissions from PV electricity generation in Thailand. The PV system is assumed to be the rooftop grid-connected type. The two feed-in tariffs for PV electricity generation are introduced to investigate the direct and indirect impact on economy. The 180-sector IO table in 2000 [5,6], obtained from National conomic & Social Development Board (NSDB) in 2005, is re-arranged and reduced to 50 main sectors for this study. However, one additional sector, i.e. PV assembly plants and distributors, is created and attached to the modified IO table. (see sector#51 in Table 2) The breakdown cost of a typical PV system in Thailand is presented in Table 3. Table 1 Target of PV installation in Thailand Year Capacity (MWp) nergy generation (GWh/y) Corresponding author: bundit@siit.tu.ac.th 1

2 Table 2 Modified input-output table for rooftop PV grid-connected system Modified sector Original 180 Sector Input/Output Definition Diesel Petroleum products and natural gas , , 126,128 quipment and machinery costs Metal products Battery lectricity storages and batteries Inverter & charger controller lectric devices lectricity lectric utilities Construction costs of factories/offices Non-residential construction Transportation costs Land transport , , 166, 170, Administration costs General services , Interest Financial institutes , 137,180 Water supply Other products 51 - PV assembly plants & installation PV manufacturer mployment Salary and labor costs Table 3 Breakdown cost of a typical rooftop grid-connected PV in Thailand. Item Cost (Baht) 1. Solar Module (3 kw), 140 Baht/Watt p 420, Inverter & grid protection 85, Controller 40, Material supplies for installation 30, Installation cost 25, Transportation 10,000 Total cost of a module Unit cost of PV system (Baht/Watt p ) 610, The PV installation in Table 1 is assumed distributed linearly during as well as the PV electricity generation. Though residential rooftop could be used for PV installation, in this study the target groups of rooftop grid-connected PV system will be retail stores and hotels. The large-scale rooftop PV installation in the retail stores and hotels as grid-connected system would be beneficial to the PV electricity production and make PV investment more economically attractive. 2.1 Case studies There are two case studies in this paper: the business-as-usual (BAU) case and the PV case. In the BAU case, the PV installation and PV electricity generation in Table 1 is assumed to be zero, i.e. PV grid-connected system does not exist. In the PV case, two hypothetical feed-in tariffs are assumed, i.e. the buyback rates from PV generation are 6 Baht/kWh and 15 Baht/kWh, which are supposed to be the suggested rate and maximum possible rate, respectively. Both rates, applied during , are assumed to be i) constant rate during (called constant FIT scenario), and ii) decreasing rate from 2006 to the expected average national electricity price in 2016 (called decreasing FIT scenario). 2.2 nergy Input-Output Analysis M The IO model [7] is employed in this study in order to evaluate the economy-wide impacts on economy, energy and environmental point of views. This study also takes the import effect into account. The Loentief s model, adopted from [8], with import structure M presents the economy-wide monetary output in the base year. X BAU M Y 1, 0 = [ I A BAU,0 BAU,0 ] BAU,0 The economy-wide monetary in the business-as-usual economy in year n is X 1 = [ I A M ] YBAU, n If the PV policy was imposed, the input structure, A, the import structure, M, and the final demand, Y in year n are changed to A, M, and Y, respectively. The economy-wide monetary output in year n will be X 1 PV, n = [ I A PV, n M PV, n] YPV, n The economy-wide monetary impact in the PV case in year n is expressed as X n = XPV, n X by given = FBAU, n.x and 2

3 , = F.X PV n PV, n PV, n where F and F PV, n are the sectoral primary-energy consumptions in year n. By consideration of only the effect of final energy consumption, the primary energy and renewable energy is taken out from F by multiplying each element of F by e kj [9] F kj = ekj.fkj The economy-wide impact on final energy consumption in the PV case in year n is n = PV, n where = Total energy consumption in the economy in year n in the BAU case PV, n = Total energy consumption in the economy in year n in the PV case The economy-wide CO 2 emission is obtained from P = ε. mission factors of the revised 1996 IPCC guidelines [10] are used in the matrix ε. The economy-wide CO 2 emissions in the PV case in year n is where P P n = PPV,n P BAU,n = Total CO 2 emissions from the economy in year n in the BAU case P PV,n = Total CO 2 emissions from the economy in year n in the PV case 2.3 Assessment of impacts of policy on PV promotion The economic sectors that would be affected are as follows: lectric Utilities The electric utilities will be directly affected by the inputs and outputs of the corresponding sectors. - lectric utilities will generate less electricity. On the other hand, the PV generation from the retail stores and hotels will be sold back to the grid under two feed-in tariff schemes as mentioned, resulting in changes in related sectors. However, the amount of national electricity generation will be the same as in the BAU case. - Besides the decrease of inputs in the electric utility sector, the cost of electricity generation will increase due to the higher rates of feed-in tariff compared with the BAU case Retail stores and Hotels The retail stores and hotels will have higher expenditures from PV installation costs PV manufacturers The PV manufacturers (sector#51) are subjected to investment for PV plants and installation including domestic costs and imported solar cells. The domestic costs include interest, transportation cost, and labor cost. 2.4 Assumptions used in analysis The PV type used in this study is of multi-crystalline silicon type. The PV plants are of assembly factories. The imported solar cells are assembled in module in the PV sector (sector#51). The breakdown cost of the PV system is presented in Table 3. The load factor of PV power generation is assumed to be 16%. Plant availability is 365 days per year. The study period is Annual fuel escalation rate is 4%. Annual growth rate of gross domestic product is 5%. The currency exchange rate is 40 Baht/US$. The cost of PV module is assumed decreasing from 140 Baht/Watt p in 2006 to 96 Baht/Watt p in 2011 and 68 Baht/Watt p. 3. RSULTS AND DISCUSSION 3.1 Impact on total primary fossil fuel Results of energy input-output (IO) analysis of policy on promotion of PV electricity generation in Thailand show that the total primary fossil fuel requirement under PV promotion during increases in both two feed-in tariffs. (see Tables 4 and 5) The constant feed-in tariff during results in higher fossil fuel requirement compared with the decreasing feed-in tariff. At the lower rate of 6 Baht/kWh, total primary fossil fuel requirement is less that at the rate of 15 Baht/kWh. The higher primary fossil fuel consumption in the constant FIT scenario is due to the higher revenue in the PV sector (sector#51), compared with the decreasing FIT scenario. The nation-wide primary fossil fuel requirement increases for both FIT scenarios about ktoe, accounting for about % of the BAU case. Therefore, the policy on PV promotion could result in higher nation-wide fossil fuel consumption. 3

4 Table 4 Total primary fossil fuel requirement during in the constant FIT scenario Total primary fossil fuel requirement (ktoe) BAU case 1,652,095 1,652,095 PV case 1,652,367 1,652,550 Fuel requirement Change 0.016% 0.028% Table 5 Total primary fossil fuel requirement during in the decreasing FIT scenario Total primary fossil fuel requirement (ktoe) BAU case 1,652,095 1,652,095 PV case 1,652,331 1,652,386 Fuel requirement Change 0.014% 0.018% 3.2 Impact on CO 2 emission The increase in total primary fossil fuel consumption in the economy results in increasing CO 2 emissions for both rates in the constant FIT and decreasing FIT scenarios. (see Tables 6 and 7) The corresponding total CO 2 emission would be increased by million tons, accounting for approximately % compared with the BAU case. At the rate of 15 Baht/kWh in the constant FIT scenario, the ratio of change in total CO 2 emission to the change in total fossil fuel consumption is found to be 1.03:1, and it is 1.14:1 for the case of 6 Baht/kWh in the decreasing FIT scenario. Table 6 Total CO 2 emission during in the constant FIT scenario Total CO 2 emission (million tons) BAU case 4,754,366 4,754,366 PV case 4,755,221 4,755,764 CO 2 emission 856 1,398 Change 0.018% 0.029% Table 7 Total CO 2 emission during in the decreasing FIT scenario Total CO 2 emission (million tons) BAU case 4,754,365 4,754,366 PV case 4,755,117 4,755,279 CO 2 emission Change 0.016% 0.019% 3.3 Impact on total national output Though the energy IO analysis of policy on promotion of PV system in Thailand reveals increasing in total primary fossil fuel consumption and CO 2 emissions, the PV investment and activities in the economy would result in higher total national output. In Tables 8 and 9, the total output during would be increased by approximately 100,000 million Baht, accounting for 0.03% compared with the BAU case. The rate of 15 Baht/kWh in the constant FIT scenario yields the largest total output increase, accounting for 0.041% of the total output in the BAU case. Table 8 Total output during in the constant FIT scenario Total output (million Baht) BAU case 312,861, ,861,182 PV case 312,962, ,990,198 Output 101, ,016 Change 0.032% 0.041% Table 9 Total output during in the decreasing FIT scenario Total output (million Baht) BAU case 312,861, ,861,182 PV case 312,957, ,965,516 Output 96, ,334 Change 0.031% 0.033% 4

5 3.3 Impact on total employment As the total output increases in the PV case, the total employment increases as well. The total employment in the PV case at 15 Baht/kWh in the constant FIT scenario is increased by 10,093 million Baht, accounting for 0.033% of the total employment in the BAU case. At this rate, the ratio of change in total employment to the change in total output is found to be 0.8:1, and it is 0.6:1 for the case of 6 Baht/kWh in the decreasing FIT scenario. However, the increase in domestic employment is found to be only 50% of the total employment increase. Table 10 Total employment during in the constant FIT scenario Total employment (million Baht) BAU case 30,766,729 30,766,729 PV case 30,772,846 30,776,822 mployment 6,117 10,093 Change 0.019% 0.033% Domestic employment 2,967 5,469 Table 11 Total employment during in the decreasing FIT scenario Total employment (million Baht) BAU case 30,766,729 30,766,729 PV case 30,772,083 30,773,266 mployment 5,355 6,538 Change 0.017% 0.021% Domestic employment 2,487 3, CONCLUSION The potential of solar energy utilization in Thailand is high. The average solar radiation in Thailand is found to be 18.2 MJ/m 2 per day. However, the electricity generation from photovoltaic (PV) system is still costly, especially for Thailand as a PV imported country. Though electricity generation from PV system seems to be less costly and less environmental emissions at generation level, the economy-wide impact from the energy IO analysis shows that the total primary fossil fuel requirement from PV activities in the economy would increase. The corresponding nation-wide CO 2 emissions also increase. However, the PV promotion in the economy would yield higher total national output, resulting in higher total employment. At the most attractive feed-in tariff of 15 Baht/kWh in the constant FIT scenario, the increases in primary fossil fuel consumption, CO 2 emission, total output, and total employment are found to be 0.028, 0.029, and 0.033% of the BAU case, respectively. The ratio of change in total employment to the change in total output is found to be 0.8:1, and it is 0.6:1 for the case of 6 Baht/kWh in the decreasing FIT scenario. However, the domestic employment is found to be only 50% of the total employment increase. Therefore, the policy makers should be aware of the implications of PV promotion on economy-wide impacts, especially for the case of Thailand as a PV imported country. Though solar energy is one of the main renewable energy sources, this study considered only economy-wide impacts from policy on PV promotion in Thailand. The life-cycle assessment of PV power generation in Thailand should also be studied. 5. ACKNOWLDGMNTS This study is prepared within the framework of the Research Programme on Policy Research for Promoting the Development and Utilization of Renewable nergy and the Improvement of nergy fficiency in Thailand funded by nergy Planning and Policy Office (PPO), coordinated by Thailand Research Fund (TRF) and the Joint Graduate School of nergy and nvironment (JGS), King Mongkut s University of Technology Thonburi (KMUTT). However, only the authors are responsible for the views expressed in the paper and for any errors. 6. RFRNCS [1] Korakot W. et al. (2006), Technology Assessment: The case of PV system, the Research Programme on Policy Research for Promoting the Development and Utilisation of Renewable nergy and the Improvement of nergy fficiency in Thailand, Thailand Research Fund. [2] DD (2006), lectric Power in Thailand 2005, Department of Alternative nergy Development and fficiency. [3] PA (2006), Solar Home System Project, Provincial lectricity Authority. [4] TRF (2006), 1 st Progress Report, the Research Programme on Policy Research for Promoting the Development and Utilisation of Renewable nergy and the Improvement of nergy fficiency in Thailand, nergy Planning and Policy Office (PPO). [5] National conomic and Social Development Board (NSDB) (2005), 2000 Input-output tables of Thailand. Available online: 21/09/2005. [6] National conomic and Social Development Board (NSDB) (2005), 1998 nergy input-output tables. Personal communications. [7] Loentief, Wassily (1986), Input-Output conomic, 2 nd dition. Oxford University Press, United States. [8] Lenzen, M. (2001). A generalized input-output multiplier calculus for Australia. conomic Systems Reserach, 13, 1, pp

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