Investigating cost-effective policy incentives for renewable energy in Japan: A recursive cge approach for an optimal energy mix

Huang, Michael C.; Kim, Chul Ju Working Paper Investigating cost-effective policy incentives for renewable energy in Japan: A recursive cge approach for an optimal energy mix ADBI Working Paper Series, No. 1033 Provided in Cooperation with: Asian Development Bank Institute (ADBI), Tokyo Suggested Citation: Huang, Michael C.; Kim, Chul Ju (2019) : Investigating cost-effective policy incentives for renewable energy in Japan: A recursive cge approach for an optimal energy mix, ADBI Working Paper Series, No. 1033, Asian Development Bank Institute (ADBI), Tokyo This Version is available at: https://hdl.handle.net/10419/222800 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by-nc-nd/3.0/igo/ ADBI Working Paper Series INVESTIGATING COST-EFFECTIVE POLICY INCENTIVES FOR RENEWABLE ENERGY IN JAPAN: A RECURSIVE CGE APPROACH FOR AN OPTIMAL ENERGY MIX Michael C. Huang and Chul Ju Kim No. 1033 November 2019 Asian Development Bank Institute The Working Paper series is a continuation of the formerly named Discussion Paper series; the numbering of the papers continued without interruption or change. ADBI’s working papers reflect initial ideas on a topic and are posted online for discussion. Some working papers may develop into other forms of publication. Suggested citation: Huang, M. C. and C. J. Kim. 2019. Investigating Cost-Effective Policy Incentives for Renewable Energy in Japan: A Recursive CGE Approach for an Optimal Energy Mix. ADBI Working Paper 1033. Tokyo: Asian Development Bank Institute. Available: https://www.adb.org/publications/investigating-cost-effective-policy-incentives-renewableenergy-japan Please contact the authors for information about this paper. Email: [email protected] Michael C. Huang is a research fellow at the Ocean Policy Research Institute of the Sasakawa Peace Foundation and the National Graduate Institute for Policy Studies. Chul Ju Kim is deputy dean of the Asian Development Bank Institute. The views expressed in this paper are the views of the author and do not necessarily reflect the views or policies of ADBI, ADB, its Board of Directors, or the governments they represent. ADBI does not guarantee the accuracy of the data included in this paper and accepts no responsibility for any consequences of their use. Terminology used may not necessarily be consistent with ADB official terms. Working papers are subject to formal revision and correction before they are finalized and considered published. Asian Development Bank Institute Kasumigaseki Building, 8th Floor 3-2-5 Kasumigaseki, Chiyoda-ku Tokyo 100-6008, Japan Tel: +81-3-3593-5500 Fax: +81-3-3593-5571 URL: www.adbi.org E-mail: [email protected] © 2019 Asian Development Bank Institute ADBI Working Paper [Do not enter] Huang and Kim Abstract The Great East Japan Earthquake (GEJE) and Fukushima nuclear disaster that occurred in 2011 gave a sharp reminder to Japan’s energy security to reconsider the reduction of nuclear power dependence with a better energy mix. We use a recursive CGE model based on Japan’s renewable energy input-output model to analyze the energy composite of power generation and consumption to investigate cost-effective policy incentives to achieve an optimal energy mix with the goal of reducing the nuclear power dependence to less than 5% within 20 years. Moreover, we create scenarios of (1) nuclear power decommission, (2) renewable energy promotion, and (3) virtual power plant (VPP) implementation with public R&D expenditure and power infrastructure investment. The simulation results show that renewable energy could gradually replace nuclear power with capital-use subsidies. Most important of all, the implementation of VPPs could reduce both the fiscal costs and social costs of promoting renewable energy while facilitating power generation. Keywords: recursive CGE model, renewable energy, Japan, optimal energy mix JEL Classification: C6, Q4 ADBI Working Paper [Do not enter] Huang and Kim Contents 1. INTRODUCTION ......................................................................................................... 1 2. LITERATURE SURVEY .............................................................................................. 2 3. CGE MODEL STRUCTURE ........................................................................................ 4 4. DATA AND SCENARIOS ............................................................................................ 8 5. SIMULATION RESULTS AND CONCLUDING REMARKS ........................................ 9 REFERENCES ..................................................................................................................... 13 ADBI Working Paper [Do not enter] Huang and Kim 1 1. INTRODUCTION The Fukushima nuclear disaster triggered by the Great East Japan Earthquake (GEJE) in 2011 gave a sharp reminder to people around the world, and gave governments and society a greater incentive to advocate the use of renewable energy for power generation. According to METI (2018), wanting to reduce the 25.1% nuclear power dependence, in 2010, Japan actively employed various policies to encourage household and electricity sectors to use more renewable power, such as solar power, wind power, and geothermal power. These policy incentives include subsidizing the implementation of power generation equipment and better electricity buy-in rates. In order to reduce the risk of nuclear disaster, the Government of Japan and society at large began a prudent reconsideration of advocating the use of renewable energy for power generation. Japan temporarily suspended all nuclear reactors for technical inspection after the GEJE. Nuclear power generation was at one point reduced to zero in the year 2014 (METI 2018) but gradually increased afterwards. As a consequence, the share of Japan’s nuclear power generation dropped to 2.8% of the total power generation while 22 reactors were scheduled for decommissioning, the cost of which would be a vital issue for power companies. On the other hand, the renewable energy sources for power regeneration increased from 9.5% (2010) to 16.1% (2017). Despite a satisfactory trend for renewable energy, the overcapacity of solar power in the Kyushu region of Japan resulted in a shutdown of solar power generation facilities for a number of days. Such issues highlight that the key for renewable energy not only lies in power generation but also in allocation. Up to 2019, Japan actively employed various policies to encourage household and energy sectors to change their power use from fossil to renewable sources such as solar, wind, and geothermal power. These policy incentives included subsidizing the implementation of power generation equipment and legislating electricity buy-in rates. The major reason for a substantial increase in the number of household solar power generation facilities installed is the feed-in tariff (FIT) regulation, which could be considered a production subsidy at a fixed price for a power generation company to buy electricity generated by households. However, this FIT system faced termination in 2019, and therefore the regulations for promoting renewable energy should be changed to a cost-effective policy. The study uses a recursive CGE model focused on energy sectors to create scenarios for policy simulation on nuclear power decommissioning plan while subsidizing renewable power for policy analysis. The structure and data in the study are based on the extended input-output table of renewable energy developed by Washizu, Nakano, and Arai (2015). The energy composite path is illustrated with a review of various indicators such as changes in sectoral output and price. The fiscal and social costs are examined for cost-effectiveness. The simulation results enable quantitative analysis in order to open the black box of renewable energy subsidy and the cost of nuclear decommissioning through policy incentives. Such a framework could be referred to policy options to determine an optimal energy mix, assisting power companies in developing appropriate measures to confront critical challenges for energy transmission. ADBI Working Paper [Do not enter] Huang and Kim 2 After this introduction, the study proceeds as follows: Part 2 comprises a literature survey and focuses on methodology and mainstream renewable energy; Part 3 introduces and illustrates our CGE model structure, parameter calibrations, and its dynamic framework; in Part 4, we explain the data and scenarios we use for policy simulations; finally, in Part 5, the simulation results will be demonstrated and we will further interpret their implications and make policy recommendations as concluding remarks. 2. LITERATURE SURVEY For simulation studies, Komiyama, Shibata, and Fujii (2013) discussed issues regarding the optimal Japanese energy composite from an engineering perspective while Ban (2016) focused on the social impact made by renewable energy. Based on the extended input-output table of renewable energy developed by Washizu, Nakano, and Arai (2015), the study uses a dynamic CGE model to create scenarios for simulating policy on abolishing nuclear power while subsidizing renewable power. The energy composite path is illustrated with a review of various indicators such as changes in sectoral output, price, and external trade while its fiscal and social costs are examined for cost-effectiveness. Japan’s energy policy and structure have changed significantly from increasing energy self-sufficiency to diversifying the energy sources after the GEJE. Yamazaki and Takeda (2017) analyze the environmental impacts of Japan’s energy circumstance with examinations on renewable energy in the “New policy scenario” suggested by the International Energy Agency (IEA). In the implementation of a feed-in tariff (FIT) system based on a multi-regional, recursive dynamic CGE model, it was found that a nuclear power phase-out policy would decrease the GDP with more greenhouse gas emissions. Japan’s energy-intensive policy that generates negative externalities should be carefully considered. Modeling an energy mix optimization has always been required along with the transition of energy sources and infrastructure. Allan et al. (2008) criticize the rebound effects for consumer service would restrict the analysis, and reduce efficiency; instead, they used a CGE model to analyze system-wide ramifications of policy intervention for industrial energy efficiency. By using a mathematical model, Incekara (2019) interprets Turkey’s 2018‒35 power generation plan with policy suggestions aimed at improving pollution levels with a view to fulfilling the commitment to the Kyoto Protocol. Fuzzy multi-objective linear programming (MOLP) was applied to the private sector’s energy target with the aim of minimizing the costs of energy-related products and CO2 emissions. The simulation results suggested that Turkey’s use of renewable energy would increase substantially; however, the costs of energy infrastructure and technology advancement were not discussed and this could lead to questions on policy feasibilities. Kriechbaum, Scheiber, and Kienberger (2018) point out that the energy grid system requires transition to support the integration of renewable energy sources while several aspects are essential for modeling a grid-based multi-energy system. With spatial consideration of necessary data, the resolutions of energy infrastructure could be identified and such work is expected to contribute to more efficient electricity converters in a grid-based energy system. An economic assessment remains desirable to provide policy analysis on incentive setting for implementing the system and evaluating its costeffectiveness. ADBI Working Paper [Do not enter] Huang and Kim 3 The power grid is the key infrastructure for providing a reliable and sustainable power supply in the face of a continuous growth in demand. Gabbar and Zidan (2016) indicate that the Canadian government and energy stakeholders are looking for new power technologies for integrating the use of power generation with cost-effectiveness and environmental friendliness. A spatial analysis and geographic information system (GIS) are applied for identifying transmission, distribution, and generation sites. The modeling results have provided an informative key performance index (KPI) as the aspects of cost, quality, reliability, and environmental friendliness may serve as vital references for grid system implementation and design. Given the increasing popularity of renewable energy use among regional households, the implementation of virtual power plants (VPPs) have become an important issue. Kasaei, Gandomkar, and Nikoukar (2017) point out that the high penetration of renewable energy sources such as wind and solar power still cause uncertainty as regards a steady power supply, and thus such variable outputs should aggregate through collections of other power generators, and storage systems to control the load for a better energy management system. Such a system has contributed to the concept of the VPPs. Despite the feature of zero marginal cost occurrence for power generation by renewable energy, the variable nature and uncertainty of the power supply remains the main concern for improving the energy mix. Pandžić, Kuzle, and Capuder (2013) considers weekly self-scheduling of a VPP of energy sources, a storage system with a conventional power plant to construct the optimal power allocation based on a linear programing model for long-term contracts. While the renewable energy source is used as backup energy after reaching the peak, such a variable could enable flexible operation and reduce uncertainty. It was also assessed that the storage capacity could be the key determinant for increasing the renewable energy resource ratio. Lima et al. (2018) use a stochastic programming method to address the optimal operation of a VPP. Forecast data from the European Centre for Medium-Range Weather Forecasts (ECMWF) were applied to calculate the utilization of renewable resources with the decomposition methods and risk management. Based on their computational results, the efficiency of decomposition methods is determined by parallel solutions. Along with the technology advancement, Adu-Kankam and Camarinha-Matos (2018) believe that VPPs will eventually overcome the stochastic nature of distributed energy resources with smart grid implementation as the key power infrastructure. Zajc, Kolenc, and Suljanović (2019) also emphasize the role of science and technology advancement for VPPs in the smart distribution and control of such service provision. Especially the downstream communication protocols between VPPs, transmission, and a distribution system would lead the electricity market to making optimal energy mix choices. With such a trend, strategic and dynamic collaborative network principles need to be formed. Yu et al. (2019) indicate that market price and power load demand are the major uncertainty factors for VPPs. Optimization with a mathematical descriptive could help identify the stochastic uncertainty systematically. The price could substantially affect the incentive for implementing renewable energy infrastructure, while the system should be designed based on evidence of the overall social welfare improvement evaluated by stakeholders. ADBI Working Paper [Do not enter] Huang and Kim 4 3. CGE MODEL STRUCTURE Our recursive dynamic CGE model was developed on the basis of the static model by Huang and Hosoe (2016). It is a single-country and open-economy model and distinguishes 18 sectors (Table 1) and suffix of variables (Table 2). The model structure demonstrates a multisectoral economy from activities of production, consumption, and capital accumulation through policy intervention. For domestic production, 𝑌𝑌𝑗𝑗 is the composite factor used by the j-th sector composite factor production function (Cobb– Douglas), while 𝐹𝐹ℎ,𝑗𝑗 is the h-th factor input by the j-th sector. 𝑌𝑌𝑗𝑗= 𝑏𝑏𝑗𝑗∏𝐹𝐹ℎ,𝑗𝑗𝛽𝛽ℎ,𝑗𝑗 ℎ ∀𝑗𝑗 (1) 𝐹𝐹ℎ,𝑗𝑗= 𝛽𝛽ℎ,𝑗𝑗𝑝𝑝𝑗𝑗 𝑦𝑦 �1+𝜏𝜏ℎ,𝑗𝑗 𝑓𝑓�𝑝𝑝ℎ,𝑗𝑗 𝑓𝑓𝑌𝑌𝑗𝑗 ∀ℎ,𝑗𝑗 (2) Table 1: Sector Abbreviation Sector Description Sector Description AGR Agriculture COA Coal MAN Manufacture GAS Natural gas ETS Electricity transmission PET Petroleum STL Steel NCU Nuclear power RAD Research and development SOL Solar power TEQ Transportation equipment WIN Wind power CON Construction GEO Geothermal power TRS Transportation WAT Hydropower SRV Service ELY Electricity Note: We aggregate the 124 sectors of the renewable energy input-output table into 18 sectors by distinguishing power generation from conventional fossil fuel (COA, GAS, PET) and renewable energy (SOL, WIN, GEO, WAT). Other manufacturing sectors (AGR, MAN, STL, TEQ, SRV) are also listed to review the impact on economic activity. In this input-output table, separation of power generation and transmission helps us distinguish electricity generation (ELY) and transmission (ETS) to analyze the implementation of virtual power plants under the implantation policy through government expenditure on research and development (R&D) and power infrastructure investment. Table 2: Model System Suffix Type of Goods/Factors in Suffix Symbol Abbreviations Energy goods ei, ej COA, PET, GAS, WIN, GEO, SOL, WAT, ELY Nonenergy goods for industries ni, nj { i } { ei } Energy goods for households ei2, ej2 PET, GAS, WIN, GEO, SOL, WAT, ELY Nonenergy goods for households ni2, nj2 { i } { ei2 } Nonelectricity goods ne { i } ELY Factor h, k CAP, LAB Mobile factor h_mob LAB Time period t 0, 1, 2, …, 30 Note: The model system and formula used in the dissertation are stated in the following section. For the dynamic model, the time suffix t is not shown for simplicity unless needed. ADBI Working Paper [Do not enter] Huang and Kim 11 Figure 5: The Output Change: Comparison of Nuclear Power Decommission Policy with Renewable Energy Incentive and VPP Implementation Note: Nuclear power generation shows a sharp decrease under the decommission policy while other conventional fossil fuels such as coal, petroleum, and gas increase significantly. Meanwhile, renewable energy sources such as solar, wind, geothermal, and even water power generation provide an even greater increase in power generation. With the implementation of VPPs, it could be found that the output of electricity transmission sector decreases by 15% because of improvement of efficiency, while other energy sources had some vibrations for output increase, indicating that a VPP could improve the electricity allocation in a more efficient mix. Figure 6: The Output Price Change: Nuclear Power Decommission Policy with Renewable Energy Incentive and VPP Implementation Note: The indicators of output price change indicate the technology improvement and the incentive for using such energy sources. With the policy incentive for renewable energy, the output prices decrease substantially in solar, wind, and geothermal power. Due to the limitation of dam construction, the output price of a water energy source does not decrease like other renewable energy sources. However, it is interesting to find the decrease in output prices of an electricity transmission system, electricity and water power generation, implying that the investment in a VPP could further facilitate a higher energy mix performance from all sorts of power generation. Nevertheless, the simulation results provide visualized consequences and impact the social economy as regards the policy implementation on nuclear decommission, renewable-energy promotion, and VPP implementation. The cost-effectiveness examined in the scenarios suggests that the power transmission system could help reduce both fiscal and social costs, indicating comprehensive plans for promoting renewable energy. While confronting the overcapacity and inefficiency of power generation from renewable energy sources, it would be indispensable for governments at all levels to help the energy sector to develop a VPP system to strengthen the power resilience. The VPP system includes a storage system that could also be of importance against large-scale natural disasters. ADBI Working Paper [Do not enter] Huang and Kim 12 Figure 7: Annual Fiscal Costs of Policy Incentives (billion JPY) * Million JPY. Note: When we compare the annual fiscal costs of capital-use subsidy on renewable energy and implementation of VPPs, it shows that the implementation of a VPP would actually reduce the fiscal cost because of the improvement of power generation efficiency by 1 and 2%, respectively, in nuclear and solar power. The reason why geothermal and wind power do not show a reduction could be due to their limited implementation geographically in power generation in the year 2005. It is also notable that the capacity of wind power (as of 2005) is relatively small compared with other energy sources, but the implementation of a VPP could increase its capacity. The fiscal costs of R&D and power infrastructure investment in energy and VPP implementation are approximately 150 billion and 100 billion JPY, respectively. Figure 8: Welfare Analysis: Social Costs of Promoting RE Compared with VPP Implementation (unit: billion JPY) Note: The social costs of policy represent the household utility in equivalent variation between the policy interventions that cause changes in the price and the quantity of consumption. Based on the simulation results of output and price, the implementation of a VPP could increase the power generation efficiency so that the allocation of electricity from energy sources could be better facilitated, easing the social costs while the technology could be fully installed from the 10th year. The VPP and technology input also show lower social cost than the renewable energy capital-use subsidy. Such consequences imply that the VPP system could lead to higher cost-effectiveness simply by providing incentives for renewable energy. Although the model is a single-country model, the optimal energy mix has reflected the choice of power generation method among all energy sources. The recursive CGE model based on Japan’s 2005 renewable energy input-output table provided evidencebased analysis on setting incentives for renewable energy after the termination of FIT, and these informative outcomes could also provide policy implications for the development of a renewable energy input-output table in many other countries. ADBI Working Paper [Do not enter] Huang and Kim 13 REFERENCES Adu-Kankam, K. and Camarinha-Matos, L. (2018) Towards collaborative virtual power plants: Trends and convergence, Sustainable Energy, Grids and Networks, 16, 217−230. Allan, G., Gilmartin, M. McGregor, P., Swales, J. and Turner, K. (2008) Modelling the economy-wide rebound effect in H. Herring and S. Sorrell (eds) Energy Efficiency and Sustainable Consumption: The Rebound Effect, Palgrave Macmillan, London. Armington, P. (1969) A theory of demand for products distinguished by place of production, International Monetary Fund Staff Papers, 16, 159–178. Ban, K. 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