Bidding modes for renewable energy considering electricity-carbon integrated market mechanism based on multi-agent hybrid game
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DOI: 10.1016/j.energy.2022.125616
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Cited by:
- Wu, Shengyang & Ding, Zhaohao & Wang, Jingyu & Shi, Dongyuan, 2023. "Unveiling bidding uncertainties in electricity markets: A Bayesian deep learning framework based on accurate variational inference," Energy, Elsevier, vol. 276(C).
- Nadeem, Muhammad & Wang, Zilong & Shakeel, Muhammad, 2023. "Real output, fossil fuels, clean fuels and trade dynamics: New insights from structural break models in China," Applied Energy, Elsevier, vol. 350(C).
- Dimitriadis, Christos N. & Tsimopoulos, Evangelos G. & Georgiadis, Michael C., 2023. "Optimal bidding strategy of a gas-fired power plant in interdependent low-carbon electricity and natural gas markets," Energy, Elsevier, vol. 277(C).
- 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).
- Zhou, Dequn & Zhang, Yining & Wang, Qunwei & Ding, Hao, 2024. "How do uncertain renewable energy induced risks evolve in a two-stage deregulated wholesale power market," Applied Energy, Elsevier, vol. 353(PB).
- Xiaohua Song & Yamin Huang & Yulin Zhang & Wen Zhang & Zeqi Ge, 2023. "An Appraisal on China’s Feed-In Tariff Policies for PV and Wind Power: Implementation Effects and Optimization," Sustainability, MDPI, vol. 15(6), pages 1-23, March.
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Keywords
Bidding mode; Renewable energy; Electricity market; Carbon emissions trading market; Multi-agent hybrid game;All these keywords.
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