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Feed-in tariff policy for biomass power generation: Incorporating the feedstock acquisition process

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  • Li, Yanan
  • Lin, Jun
  • Qian, Yanjun
  • Li, Dehong

Abstract

The high logistics costs of biomass feedstock and the involvement of other firms that use biomass and independent suppliers make feedstock acquisition increasingly difficult for biomass power plants. Governments provide feed-in tariffs (FiT) for biomass power plants to help reduce the negative impacts of high raw material costs. Using a game-theoretic approach, we study the optimal government FiT for biomass power plants and explore the effects of biomass feedstock competition and the presence of independent biomass feedstock suppliers on FiT strategy. Our results show that governments should subsidize biomass power plants whose competitiveness exceeds a certain threshold. The entry of a feedstock competitor into the biomass supply chain raises this threshold, but the involvement of an independent biomass supplier will not. However, the involvement of an independent biomass supplier reduces the efficiency of the FiT. In addition, FiT for biomass power plants should not be provided if government funds are below a certain threshold, as it does not increase social welfare. By comparing FiT with an alternative use of government funds, the technology subsidy, we find that the technology subsidy should be adopted instead of FiT if the government funds are below a threshold.

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  • Li, Yanan & Lin, Jun & Qian, Yanjun & Li, Dehong, 2023. "Feed-in tariff policy for biomass power generation: Incorporating the feedstock acquisition process," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1113-1132.
    • Handle: RePEc:eee:ejores:v:304:y:2023:i:3:p:1113-1132
    DOI: 10.1016/j.ejor.2022.05.011
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    as
    1. Moiseyev, Alexander & Solberg, Birger & Kallio, A. Maarit I., 2014. "The impact of subsidies and carbon pricing on the wood biomass use for energy in the EU," Energy, Elsevier, vol. 76(C), pages 161-167.
    2. Jonathan Chemama & Maxime C. Cohen & Ruben Lobel & Georgia Perakis, 2019. "Consumer Subsidies with a Strategic Supplier: Commitment vs. Flexibility," Management Science, INFORMS, vol. 65(2), pages 681-713, February.
    3. Hombach, Laura Elisabeth & Walther, Grit, 2015. "Pareto-efficient legal regulation of the (bio)fuel market using a bi-objective optimization model," European Journal of Operational Research, Elsevier, vol. 245(1), pages 286-295.
    4. Natalia Fabra & Mar Reguant, 2014. "Pass-Through of Emissions Costs in Electricity Markets," American Economic Review, American Economic Association, vol. 104(9), pages 2872-2899, September.
    5. Li, Yumin, 2018. "Incentive pass-through in the California Solar Initiative – An analysis based on third-party contracts," Energy Policy, Elsevier, vol. 121(C), pages 534-541.
    6. Saidur, R. & Abdelaziz, E.A. & Demirbas, A. & Hossain, M.S. & Mekhilef, S., 2011. "A review on biomass as a fuel for boilers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(5), pages 2262-2289, June.
    7. Farmer, J. Doyne & Lafond, François, 2016. "How predictable is technological progress?," Research Policy, Elsevier, vol. 45(3), pages 647-665.
    8. Nock, Destenie & Levin, Todd & Baker, Erin, 2020. "Changing the policy paradigm: A benefit maximization approach to electricity planning in developing countries," Applied Energy, Elsevier, vol. 264(C).
    9. Sylvain Caurla & Philippe Delacote & Franck Lecocq & Ahmed Barkaoui, 2013. "Stimulating fuelwood consumption through public policies: an assessment of economic and resource impacts based on the french forest sector model," Post-Print hal-01072295, HAL.
    10. Magee, C.L. & Basnet, S. & Funk, J.L. & Benson, C.L., 2016. "Quantitative empirical trends in technical performance," Technological Forecasting and Social Change, Elsevier, vol. 104(C), pages 237-246.
    11. Sam Aflaki & Paul R. Kleindorfer & Victor Sáenz Miera Polvorinos, 2013. "Finding and Implementing Energy Efficiency Projects in Industrial Facilities," Post-Print hal-00823923, HAL.
    12. Dong, Changgui & Wiser, Ryan & Rai, Varun, 2018. "Incentive pass-through for residential solar systems in California," Energy Economics, Elsevier, vol. 72(C), pages 154-165.
    13. Bai, Yun & Ouyang, Yanfeng & Pang, Jong-Shi, 2016. "Enhanced models and improved solution for competitive biofuel supply chain design under land use constraints," European Journal of Operational Research, Elsevier, vol. 249(1), pages 281-297.
    14. Béla Nagy & J Doyne Farmer & Quan M Bui & Jessika E Trancik, 2013. "Statistical Basis for Predicting Technological Progress," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-7, February.
    15. Evans, Annette & Strezov, Vladimir & Evans, Tim J., 2010. "Sustainability considerations for electricity generation from biomass," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(5), pages 1419-1427, June.
    16. Huisman, Ronald & Kiliç, Mehtap, 2015. "Time variation in European carbon pass-through rates in electricity futures prices," Energy Policy, Elsevier, vol. 86(C), pages 239-249.
    17. Leilei Zhang & Guping Hu & Lizhi Wang & Yihsu Chen, 2016. "A bottom-up biofuel market equilibrium model for policy analysis," Annals of Operations Research, Springer, vol. 236(1), pages 75-101, January.
    18. Charles, Michael B. & Ryan, Rachel & Ryan, Neal & Oloruntoba, Richard, 2007. "Public policy and biofuels: The way forward?," Energy Policy, Elsevier, vol. 35(11), pages 5737-5746, November.
    19. Alfaro, Jose & Miller, Shelie, 2014. "Satisfying the rural residential demand in Liberia with decentralized renewable energy schemes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 903-911.
    20. Hombach, Laura Elisabeth & Büsing, Christina & Walther, Grit, 2018. "Robust and sustainable supply chains under market uncertainties and different risk attitudes – A case study of the German biodiesel market," European Journal of Operational Research, Elsevier, vol. 269(1), pages 302-312.
    21. Caurla, Sylvain & Delacote, Philippe & Lecocq, Franck & Barkaoui, Ahmed, 2013. "Stimulating fuelwood consumption through public policies: An assessment of economic and resource impacts based on the French Forest Sector Model," Energy Policy, Elsevier, vol. 63(C), pages 338-347.
    22. Heinz Kopetz, 2013. "Build a biomass energy market," Nature, Nature, vol. 494(7435), pages 29-31, February.
    23. Stoppato, Anna, 2012. "Energetic and economic investigation of the operation management of an Organic Rankine Cycle cogeneration plant," Energy, Elsevier, vol. 41(1), pages 3-9.
    24. Golecha, Rajdeep & Gan, Jianbang, 2016. "Biomass transport cost from field to conversion facility when biomass yield density and road network vary with transport radius," Applied Energy, Elsevier, vol. 164(C), pages 321-331.
    25. Eker, Sibel & van Daalen, Els, 2015. "A model-based analysis of biomethane production in the Netherlands and the effectiveness of the subsidization policy under uncertainty," Energy Policy, Elsevier, vol. 82(C), pages 178-196.
    26. Liu, H. & Jiang, G.M. & Zhuang, H.Y. & Wang, K.J., 2008. "Distribution, utilization structure and potential of biomass resources in rural China: With special references of crop residues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 12(5), pages 1402-1418, June.
    27. Yu-zhuo, Zhang & Xin-gang, Zhao & Ling-zhi, Ren & Ji, Liang & Ping-kuo, Liu, 2017. "The development of China's biomass power industry under feed-in tariff and renewable portfolio standard: A system dynamics analysis," Energy, Elsevier, vol. 139(C), pages 947-961.
    28. Leilei Zhang & Guping Hu & Lizhi Wang & Yihsu Chen, 2016. "A bottom-up biofuel market equilibrium model for policy analysis," Annals of Operations Research, Springer, vol. 236(1), pages 75-101, January.
    29. Tan, Qinliang & Wang, Tingran & Zhang, Yimei & Miao, Xinyan & Zhu, Jun, 2017. "Nonlinear multi-objective optimization model for a biomass direct-fired power generation supply chain using a case study in China," Energy, Elsevier, vol. 139(C), pages 1066-1079.
    30. De Meyer, Annelies & Cattrysse, Dirk & Van Orshoven, Jos, 2015. "A generic mathematical model to optimise strategic and tactical decisions in biomass-based supply chains (OPTIMASS)," European Journal of Operational Research, Elsevier, vol. 245(1), pages 247-264.
    31. Wang, Xiaolei & Ouyang, Yanfeng & Yang, Hai & Bai, Yun, 2013. "Optimal biofuel supply chain design under consumption mandates with renewable identification numbers," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 158-171.
    32. Shadi Goodarzi & Sam Aflaki & Andrea Masini, 2019. "Optimal Feed‐In Tariff Policies: The Impact of Market Structure and Technology Characteristics," Production and Operations Management, Production and Operations Management Society, vol. 28(5), pages 1108-1128, May.
    33. Daniel L. Sanchez & James H. Nelson & Josiah Johnston & Ana Mileva & Daniel M. Kammen, 2015. "Biomass enables the transition to a carbon-negative power system across western North America," Nature Climate Change, Nature, vol. 5(3), pages 230-234, March.
    34. Liu, Zuoming, 2019. "The optimal biopower capacity in co-firing plants– An empirical analysis," Energy Economics, Elsevier, vol. 78(C), pages 392-400.
    35. Wen, Wen & Zhang, Qin, 2015. "A design of straw acquisition mode for China's straw power plant based on supply chain coordination," Renewable Energy, Elsevier, vol. 76(C), pages 369-374.
    36. Maxime C. Cohen & Ruben Lobel & Georgia Perakis, 2016. "The Impact of Demand Uncertainty on Consumer Subsidies for Green Technology Adoption," Management Science, INFORMS, vol. 62(5), pages 1235-1258, May.
    37. Wang, Xingwei & Cai, Yanpeng & Dai, Chao, 2014. "Evaluating China's biomass power production investment based on a policy benefit real options model," Energy, Elsevier, vol. 73(C), pages 751-761.
    38. Saed Alizamir & Francis de Véricourt & Peng Sun, 2016. "Efficient Feed-In-Tariff Policies for Renewable Energy Technologies," Operations Research, INFORMS, vol. 64(1), pages 52-66, February.
    39. Nasiri, Fuzhan & Zaccour, Georges, 2009. "An exploratory game-theoretic analysis of biomass electricity generation supply chain," Energy Policy, Elsevier, vol. 37(11), pages 4514-4522, November.
    40. Zhang, Xingping & Luo, Kaiyan & Tan, Qinliang, 2016. "A feedstock supply model integrating the official organization for China's biomass generation plants," Energy Policy, Elsevier, vol. 97(C), pages 276-290.
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