IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v308y2024ics0360544224028354.html
   My bibliography  Save this article

Exploring the diffusion of low-carbon power generation and energy storage technologies under electricity market reform in China: An agent-based modeling framework for power sector

Author

Listed:
  • Han, Jian
  • Tan, Qinliang
  • Ding, Yihong
  • Liu, Yuan

Abstract

Promoting the widespread adoption of multi-complementary low carbon power generation technologies is a fundamental strategy for attaining carbon neutrality within the electricity sector. In the context of electricity market reform, this study develops an agent-based modeling framework integrated simulation with optimization. The model uses agent-based simulation to analyze annual market dynamics and low-carbon technology diffusion, with a two-stage optimization for energy storage and spot market simulation. The research findings indicate: (1) For different power generation technologies, the spot market can establish differentiated average prices, making the market price of carbon-captured coal power higher than that of conventional coal power, which are advantageous in reducing the subsidies required to promote the diffusion of carbon capture technology. (2) Expanding the spot market scale and implementing differentiated capacity compensation mechanisms both promote carbon capture technology diffusion. Nevertheless, with the marginal clearing mechanism, thermal power holds a average price advantage than renewable energy. Failing to control the growth of thermal power capacity will result in increased carbon emissions. (3) After 2030, energy storage's role in balancing supply and demand grows. Storage capacity should align with renewable energy scale and the regional characteristics of wind and solar resources to prevent overbuilding and stranded assets.

Suggested Citation

  • Han, Jian & Tan, Qinliang & Ding, Yihong & Liu, Yuan, 2024. "Exploring the diffusion of low-carbon power generation and energy storage technologies under electricity market reform in China: An agent-based modeling framework for power sector," Energy, Elsevier, vol. 308(C).
    • Handle: RePEc:eee:energy:v:308:y:2024:i:c:s0360544224028354
    DOI: 10.1016/j.energy.2024.133060
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544224028354
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2024.133060?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. Liu, Jinqi & Wang, Jihong & Cardinal, Joel, 2022. "Evolution and reform of UK electricity market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    2. Pan, Xunzhang & Ma, Xueqing & Zhang, Yanru & Shao, Tianming & Peng, Tianduo & Li, Xiang & Wang, Lining & Chen, Wenying, 2023. "Implications of carbon neutrality for power sector investments and stranded coal assets in China," Energy Economics, Elsevier, vol. 121(C).
    3. Li, Tianyu & Gao, Ciwei & Chen, Tao & Jiang, Yu & Feng, Yingchun, 2022. "Medium and long-term electricity market trading strategy considering renewable portfolio standard in the transitional period of electricity market reform in Jiangsu, China," Energy Economics, Elsevier, vol. 107(C).
    4. Iychettira, Kaveri K. & Hakvoort, Rudi A. & Linares, Pedro & de Jeu, Rob, 2017. "Towards a comprehensive policy for electricity from renewable energy: Designing for social welfare," Applied Energy, Elsevier, vol. 187(C), pages 228-242.
    5. He, Gang & Kammen, Daniel M., 2016. "Where, when and how much solar is available? A provincial-scale solar resource assessment for China," Renewable Energy, Elsevier, vol. 85(C), pages 74-82.
    6. Ding, Yihong & Tan, Qinliang & Shan, Zijing & Han, Jian & Zhang, Yimei, 2023. "A two-stage dispatching optimization strategy for hybrid renewable energy system with low-carbon and sustainability in ancillary service market," Renewable Energy, Elsevier, vol. 207(C), pages 647-659.
    7. Tan, Qinliang & Han, Jian & Liu, Yuan, 2023. "Examining the synergistic diffusion process of carbon capture and renewable energy generation technologies under market environment: A multi-agent simulation analysis," Energy, Elsevier, vol. 282(C).
    8. He, Zhenglei & Liu, Chang & Wang, Yutao & Wang, Xu & Man, Yi, 2023. "Optimal operation of wind-solar-thermal collaborative power system considering carbon trading and energy storage," Applied Energy, Elsevier, vol. 352(C).
    9. Lee, Jui-Yuan, 2017. "A multi-period optimisation model for planning carbon sequestration retrofits in the electricity sector," Applied Energy, Elsevier, vol. 198(C), pages 12-20.
    10. He, Gang & Kammen, Daniel M., 2014. "Where, when and how much wind is available? A provincial-scale wind resource assessment for China," Energy Policy, Elsevier, vol. 74(C), pages 116-122.
    11. Han, Zhixin & Fang, Debin & Yang, Peiwen & Lei, Leyao, 2023. "Cooperative mechanisms for multi-energy complementarity in the electricity spot market," Energy Economics, Elsevier, vol. 127(PB).
    12. Tao, Zhenmin & Moncada, Jorge Andrés & Poncelet, Kris & Delarue, Erik, 2021. "Review and analysis of investment decision making algorithms in long-term agent-based electric power system simulation models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 136(C).
    13. Müller, Leander A. & Leonard, Alycia & Trotter, Philipp A. & Hirmer, Stephanie, 2023. "Green hydrogen production and use in low- and middle-income countries: A least-cost geospatial modelling approach applied to Kenya," Applied Energy, Elsevier, vol. 343(C).
    14. Guo, Hongye & Davidson, Michael R. & Chen, Qixin & Zhang, Da & Jiang, Nan & Xia, Qing & Kang, Chongqing & Zhang, Xiliang, 2020. "Power market reform in China: Motivations, progress, and recommendations," Energy Policy, Elsevier, vol. 145(C).
    15. Cai, Liya & Luo, Ji & Wang, Minghui & Guo, Jianfeng & Duan, Jinglin & Li, Jingtao & Li, Shuo & Liu, Liting & Ren, Dangpei, 2023. "Pathways for municipalities to achieve carbon emission peak and carbon neutrality: A study based on the LEAP model," Energy, Elsevier, vol. 262(PB).
    16. Tong, Ziqiang & Mansouri, Seyed Amir & Huang, Shoujun & Rezaee Jordehi, Ahmad & Tostado-Véliz, Marcos, 2023. "The role of smart communities integrated with renewable energy resources, smart homes and electric vehicles in providing ancillary services: A tri-stage optimization mechanism," Applied Energy, Elsevier, vol. 351(C).
    17. Zhang, Pan & Mansouri, Seyed Amir & Rezaee Jordehi, Ahmad & Tostado-Véliz, Marcos & Alharthi, Yahya Z. & Safaraliev, Murodbek, 2024. "An ADMM-enabled robust optimization framework for self-healing scheduling of smart grids integrated with smart prosumers," Applied Energy, Elsevier, vol. 363(C).
    18. Aghahosseini, Arman & Solomon, A.A. & Breyer, Christian & Pregger, Thomas & Simon, Sonja & Strachan, Peter & Jäger-Waldau, Arnulf, 2023. "Energy system transition pathways to meet the global electricity demand for ambitious climate targets and cost competitiveness," Applied Energy, Elsevier, vol. 331(C).
    19. Kang, Jidong & Ng, Tsan Sheng & Su, Bin, 2020. "Optimizing electricity mix for CO2 emissions reduction: A robust input-output linear programming model," European Journal of Operational Research, Elsevier, vol. 287(1), pages 280-292.
    20. Panos, Evangelos & Kober, Tom & Wokaun, Alexander, 2019. "Long term evaluation of electric storage technologies vs alternative flexibility options for the Swiss energy system," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    21. Xu, Guangyue & Zang, Lanmei & Schwarz, Peter & Yang, Hualiu, 2023. "Achieving Chinaʼs carbon neutrality goal by economic growth rate adjustment and low-carbon energy structure," Energy Policy, Elsevier, vol. 183(C).
    22. Iychettira, Kaveri K. & Hakvoort, Rudi A. & Linares, Pedro, 2017. "Towards a comprehensive policy for electricity from renewable energy: An approach for policy design," Energy Policy, Elsevier, vol. 106(C), pages 169-182.
    23. Fabra, Natalia, 2023. "Reforming European electricity markets: Lessons from the energy crisis," Energy Economics, Elsevier, vol. 126(C).
    24. Richstein, Jörn C. & Chappin, Emile J.L. & de Vries, Laurens J., 2014. "Cross-border electricity market effects due to price caps in an emission trading system: An agent-based approach," Energy Policy, Elsevier, vol. 71(C), pages 139-158.
    25. Parzen, Maximilian & Abdel-Khalek, Hazem & Fedotova, Ekaterina & Mahmood, Matin & Frysztacki, Martha Maria & Hampp, Johannes & Franken, Lukas & Schumm, Leon & Neumann, Fabian & Poli, Davide & Kiprakis, 2023. "PyPSA-Earth. A new global open energy system optimization model demonstrated in Africa," Applied Energy, Elsevier, vol. 341(C).
    26. Chen, Huadong & Wang, Can & Cai, Wenjia & Wang, Jianhui, 2018. "Simulating the impact of investment preference on low-carbon transition in power sector," Applied Energy, Elsevier, vol. 217(C), pages 440-455.
    27. Glismann, Samuel, 2021. "Ancillary Services Acquisition Model: Considering market interactions in policy design," Applied Energy, Elsevier, vol. 304(C).
    Full references (including those not matched with items on IDEAS)

    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. Tan, Qinliang & Han, Jian & Liu, Yuan, 2023. "Examining the synergistic diffusion process of carbon capture and renewable energy generation technologies under market environment: A multi-agent simulation analysis," Energy, Elsevier, vol. 282(C).
    2. Tao, Zhenmin & Moncada, Jorge Andrés & Poncelet, Kris & Delarue, Erik, 2021. "Review and analysis of investment decision making algorithms in long-term agent-based electric power system simulation models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 136(C).
    3. Chen, Huadong & Wang, Can & Cai, Wenjia & Wang, Jianhui, 2018. "Simulating the impact of investment preference on low-carbon transition in power sector," Applied Energy, Elsevier, vol. 217(C), pages 440-455.
    4. Khan, Agha Salman M. & Verzijlbergh, Remco A. & Sakinci, Ozgur Can & De Vries, Laurens J., 2018. "How do demand response and electrical energy storage affect (the need for) a capacity market?," Applied Energy, Elsevier, vol. 214(C), pages 39-62.
    5. Jimenez, I. Sanchez & Ribó-Pérez, D. & Cvetkovic, M. & Kochems, J. & Schimeczek, C. & de Vries, L.J., 2024. "Can an energy only market enable resource adequacy in a decarbonized power system? A co-simulation with two agent-based-models," Applied Energy, Elsevier, vol. 360(C).
    6. Zhang, Xiaodong & Patino-Echeverri, Dalia & Li, Mingquan & Wu, Libo, 2022. "A review of publicly available data sources for models to study renewables integration in China's power system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    7. Li, Pei-Hao & Barazza, Elsa & Strachan, Neil, 2022. "The influences of non-optimal investments on the scale-up of smart local energy systems in the UK electricity market," Energy Policy, Elsevier, vol. 170(C).
    8. Melliger, Marc & Chappin, Emile, 2022. "Phasing out support schemes for renewables in neighbouring countries: An agent-based model with investment preferences," Applied Energy, Elsevier, vol. 305(C).
    9. Barazza, Elsa & Strachan, Neil, 2020. "The impact of heterogeneous market players with bounded-rationality on the electricity sector low-carbon transition," Energy Policy, Elsevier, vol. 138(C).
    10. Zhang, Haoran & Li, Ruixiong & Cai, Xingrui & Zheng, Chaoyue & Liu, Laibao & Liu, Maodian & Zhang, Qianru & Lin, Huiming & Chen, Long & Wang, Xuejun, 2022. "Do electricity flows hamper regional economic–environmental equity?," Applied Energy, Elsevier, vol. 326(C).
    11. Liu, Hailiang & Andresen, Gorm Bruun & Greiner, Martin, 2018. "Cost-optimal design of a simplified highly renewable Chinese electricity network," Energy, Elsevier, vol. 147(C), pages 534-546.
    12. Hongli Liu & Xiaoyu Yan & Jinhua Cheng & Jun Zhang & Yan Bu, 2021. "Driving Factors for the Spatiotemporal Heterogeneity in Technical Efficiency of China’s New Energy Industry," Energies, MDPI, vol. 14(14), pages 1-21, July.
    13. Li, Wei & Lu, Can & Zhang, Yan-Wu, 2019. "Prospective exploration of future renewable portfolio standard schemes in China via a multi-sector CGE model," Energy Policy, Elsevier, vol. 128(C), pages 45-56.
    14. Jiang, Suqin & Chen, Zun & Shan, Li & Chen, Xinyu & Wang, Haikun, 2017. "Committed CO2 emissions of China's coal-fired power generators from 1993 to 2013," Energy Policy, Elsevier, vol. 104(C), pages 295-302.
    15. Gosens, Jorrit, 2017. "Natural resource endowment is not a strong driver of wind or PV development," Renewable Energy, Elsevier, vol. 113(C), pages 1007-1018.
    16. Niamir, Leila & Filatova, Tatiana & Voinov, Alexey & Bressers, Hans, 2018. "Transition to low-carbon economy: Assessing cumulative impacts of individual behavioral changes," Energy Policy, Elsevier, vol. 118(C), pages 325-345.
    17. Serban, Ioan, 2018. "A control strategy for microgrids: Seamless transfer based on a leading inverter with supercapacitor energy storage system," Applied Energy, Elsevier, vol. 221(C), pages 490-507.
    18. Anwar, Muhammad Bashar & Stephen, Gord & Dalvi, Sourabh & Frew, Bethany & Ericson, Sean & Brown, Maxwell & O’Malley, Mark, 2022. "Modeling investment decisions from heterogeneous firms under imperfect information and risk in wholesale electricity markets," Applied Energy, Elsevier, vol. 306(PA).
    19. Liu, Xi & Du, Huibin & Brown, Marilyn A. & Zuo, Jian & Zhang, Ning & Rong, Qian & Mao, Guozhu, 2018. "Low-carbon technology diffusion in the decarbonization of the power sector: Policy implications," Energy Policy, Elsevier, vol. 116(C), pages 344-356.
    20. Zhang, Pengpeng & Zhang, Lixiao & Tian, Xin & Hao, Yan & Wang, Changbo, 2018. "Urban energy transition in China: Insights from trends, socioeconomic drivers, and environmental impacts of Beijing," Energy Policy, Elsevier, vol. 117(C), pages 173-183.

    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:energy:v:308:y:2024:i:c:s0360544224028354. 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.journals.elsevier.com/energy .

    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.