IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v304y2023i3p1113-1132.html
   My bibliography  Save this article

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

Author

Listed:
  • 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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221722003691
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2022.05.011?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. Farmer, J. Doyne & Lafond, François, 2016. "How predictable is technological progress?," Research Policy, Elsevier, vol. 45(3), pages 647-665.
    11. 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.
    12. 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.
    13. Liu, Zuoming, 2019. "The optimal biopower capacity in co-firing plants– An empirical analysis," Energy Economics, Elsevier, vol. 78(C), pages 392-400.
    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. 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.
    16. 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).
    17. 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.
    18. 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.
    19. Sam Aflaki & Paul R. Kleindorfer & Victor Sáenz Miera Polvorinos, 2013. "Finding and Implementing Energy Efficiency Projects in Industrial Facilities," Post-Print hal-00823923, HAL.
    20. 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.
    21. 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.
    22. 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.
    23. 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.
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    28. 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.
    29. 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.
    30. 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.
    31. 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.
    32. Heinz Kopetz, 2013. "Build a biomass energy market," Nature, Nature, vol. 494(7435), pages 29-31, February.
    33. 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.
    34. 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.
    35. 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.
    36. 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.
    37. 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.
    38. 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.
    39. 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.
    40. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tan, Zhizhou & Zeng, Xianhai & Lin, Boqiang, 2023. "How do multiple policy incentives influence investors’ decisions on biomass co-firing combined with carbon capture and storage retrofit projects for coal-fired power plants?," Energy, Elsevier, vol. 278(PB).
    2. Zhao Xin-gang & Wang Wei & Hu Shuran & Liu Xuan, 2023. "Impacts of Government Policies on the Adoption of Biomass Power: A System Dynamic Perspective," Sustainability, MDPI, vol. 15(2), pages 1-11, January.
    3. Dias, José Carlos & Nunes, João Pedro Vidal & da Silva, Fernando Correia, 2024. "Finite maturity caps and floors on continuous flows under the constant elasticity of variance process," European Journal of Operational Research, Elsevier, vol. 316(1), pages 361-385.
    4. Zhang, Huan & Duan, Xianglei & Jiang, Jianli, 2024. "Fixed rebate subsidy vs. unit price subsidy: Incentive effect on the biomass power supply chain," Energy Policy, Elsevier, vol. 187(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mafakheri, Fereshteh & Nasiri, Fuzhan, 2014. "Modeling of biomass-to-energy supply chain operations: Applications, challenges and research directions," Energy Policy, Elsevier, vol. 67(C), pages 116-126.
    2. Juanjuan Wu & Jian Zhang & Weiming Yi & Hongzhen Cai & Yang Li & Zhanpeng Su, 2021. "A Game-Theoretic Analysis of Incentive Effects for Agribiomass Power Generation Supply Chain in China," Energies, MDPI, vol. 14(3), pages 1-18, January.
    3. Singh, Anuraag & Triulzi, Giorgio & Magee, Christopher L., 2021. "Technological improvement rate predictions for all technologies: Use of patent data and an extended domain description," Research Policy, Elsevier, vol. 50(9).
    4. Brozynski, Max T. & Leibowicz, Benjamin D., 2022. "A multi-level optimization model of infrastructure-dependent technology adoption: Overcoming the chicken-and-egg problem," European Journal of Operational Research, Elsevier, vol. 300(2), pages 755-770.
    5. Caurla, Sylvain & Bertrand, Vincent & Delacote, Philippe & Le Cadre, Elodie, 2018. "Heat or power: How to increase the use of energy wood at the lowest cost?," Energy Economics, Elsevier, vol. 75(C), pages 85-103.
    6. Dosi, Giovanni & Grazzi, Marco & Mathew, Nanditha, 2017. "The cost-quantity relations and the diverse patterns of “learning by doing”: Evidence from India," Research Policy, Elsevier, vol. 46(10), pages 1873-1886.
    7. Duygu Akkaya & Kostas Bimpikis & Hau Lee, 2021. "Government Interventions to Promote Agricultural Innovation," Manufacturing & Service Operations Management, INFORMS, vol. 23(2), pages 437-452, March.
    8. Wolff, Michael & Becker, Tristan & Walther, Grit, 2023. "Long-term design and analysis of renewable fuel supply chains – An integrated approach considering seasonal resource availability," European Journal of Operational Research, Elsevier, vol. 304(2), pages 745-762.
    9. Wang, Zhanwu & Wang, Zhenfeng & Tahir, Nadeem & Wang, Heng & Li, Jin & Xu, Guangyin, 2020. "Study of synergetic development in straw power supply chain: Straw price and government subsidy as incentive," Energy Policy, Elsevier, vol. 146(C).
    10. Miguel Riviere & Sylvain Caurla & Philippe Delacote, 2020. "Evolving Integrated Models From Narrower Economic Tools : the Example of Forest Sector Models," Post-Print hal-02512330, HAL.
    11. Jung, Seung Hwan & Feng, Tianjun, 2020. "Government subsidies for green technology development under uncertainty," European Journal of Operational Research, Elsevier, vol. 286(2), pages 726-739.
    12. Anuraag Singh & Giorgio Triulzi & Christopher L. Magee, 2020. "Technological improvement rate estimates for all technologies: Use of patent data and an extended domain description," Papers 2004.13919, arXiv.org.
    13. Jonas Zetterholm & Elina Bryngemark & Johan Ahlström & Patrik Söderholm & Simon Harvey & Elisabeth Wetterlund, 2020. "Economic Evaluation of Large-Scale Biorefinery Deployment: A Framework Integrating Dynamic Biomass Market and Techno-Economic Models," Sustainability, MDPI, vol. 12(17), pages 1-28, September.
    14. Triulzi, Giorgio & Alstott, Jeff & Magee, Christopher L., 2020. "Estimating technology performance improvement rates by mining patent data," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    15. Guo, Yan & Yu, Xinning & Zhou, Caifeng & Lyu, Gaoyan, 2021. "Government subsidies for preventing supply disruption when the supplier has an outside option under competition," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 147(C).
    16. Zhang, Guanglu & McAdams, Daniel A. & Shankar, Venkatesh & Darani, Milad Mohammadi, 2017. "Modeling the evolution of system technology performance when component and system technology performances interact: Commensalism and amensalism," Technological Forecasting and Social Change, Elsevier, vol. 125(C), pages 116-124.
    17. Mario Coccia, 2019. "Technological Parasitism," Papers 1901.09073, arXiv.org.
    18. Coccia, Mario, 2019. "The theory of technological parasitism for the measurement of the evolution of technology and technological forecasting," Technological Forecasting and Social Change, Elsevier, vol. 141(C), pages 289-304.
    19. Etienne Lorang & Antonello Lobianco & Philippe Delacote, 2023. "Increasing Paper and Cardboard Recycling: Impacts on the Forest Sector and Carbon Emissions," Post-Print hal-03832461, HAL.
    20. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:304:y:2023:i:3:p:1113-1132. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.