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Energy storage subsidy estimation for microgrid: A real option game-theoretic approach

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  • Chen, Weidong
  • Zeng, Yu
  • Xu, Chongqing

Abstract

Microgrid development is presently limited due to high costs, especially its energy storage system (ESS) component. ESS subsidy policies, as the main response options, seem essential to be explored to promote the diffusion of microgrid. In this study, we propose an evolutionary game model combined with real options to guide ESS subsidy policies for microgrid by applying to a small electricity network served by a regulated utility. As there exists market share arrangements during the game, a multi-objective programming is formulated to determine the optimal investment capacity for each market participant. To evaluate our model, we provide a numerical example to demonstrate how different ESS subsidies affect the fluctuation amplitudes and equilibrium positions in microgrid diffusion process. The results indicate that price subsidy for energy storage has more significant effect than initial cost subsidy for microgrid development. In addition, although the importance of ESS electricity price subsidy is reflected, its combination with initial cost subsidy may both ensure investment value of microgrid and reduce the initial cost of such a capital-intensive component.

Suggested Citation

  • Chen, Weidong & Zeng, Yu & Xu, Chongqing, 2019. "Energy storage subsidy estimation for microgrid: A real option game-theoretic approach," Applied Energy, Elsevier, vol. 239(C), pages 373-382.
    • Handle: RePEc:eee:appene:v:239:y:2019:i:c:p:373-382
    DOI: 10.1016/j.apenergy.2019.01.232
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    4. Wei Chen & Yongle Tian & Kaiming Zheng & Nana Wan, 2023. "Influences of mechanisms on investment in renewable energy storage equipment," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(11), pages 12569-12595, November.
    5. Pablo Benalcazar & Adam Suski & Jacek Kamiński, 2020. "The Effects of Capital and Energy Subsidies on the Optimal Design of Microgrid Systems," Energies, MDPI, vol. 13(4), pages 1-23, February.
    6. Younes Zahraoui & Tarmo Korõtko & Argo Rosin & Hannes Agabus, 2023. "Market Mechanisms and Trading in Microgrid Local Electricity Markets: A Comprehensive Review," Energies, MDPI, vol. 16(5), pages 1-52, February.
    7. Liu, Jiangfeng & Zhang, Qi & Li, Hailong & Chen, Siyuan & Teng, Fei, 2022. "Investment decision on carbon capture and utilization (CCU) technologies—A real option model based on technology learning effect," Applied Energy, Elsevier, vol. 322(C).
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    9. Ting Zhang & Shuaishuai Cao & Lingying Pan & Chenyu Zhou, 2020. "A Policy Effect Analysis of China’s Energy Storage Development Based on a Multi-Agent Evolutionary Game Model," Energies, MDPI, vol. 13(23), pages 1-35, November.
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