Day-Ahead Market Modeling for Strategic Wind Power Producers under Robust Market Clearing
AbstractIn this paper, considering real time wind power uncertainties, the strategic behaviors of wind power producers adopting two different bidding modes in day-ahead electricity market is modeled and experimentally compared. These two different bidding modes only provide a wind power output plan and a bidding curve consisting of bidding price and power output, respectively. On the one hand, to significantly improve wind power accommodation, a robust market clearing model is employed for day-ahead market clearing implemented by an independent system operator. On the other hand, since the Least Squares Continuous Actor-Critic algorithm is demonstrated as an effective method in dealing with Markov decision-making problems with continuous state and action sets, we propose the Least Squares Continuous Actor-Critic-based approaches to model and simulate the dynamic bidding interaction processes of many wind power producers adopting two different bidding modes in the day-head electricity market under robust market clearing conditions, respectively. Simulations are implemented on the IEEE 30-bus test system with five strategic wind power producers, which verify the rationality of our proposed approaches. Moreover, the quantitative analysis and comparisons conducted in our simulations put forward some suggestions about leading wind power producers to reasonably bid in market and bidding mode selections. View Full-Text
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Zhao, H.; Wang, Y.; Zhao, M.; Tan, Q.; Guo, S. Day-Ahead Market Modeling for Strategic Wind Power Producers under Robust Market Clearing. Energies 2017, 10, 924.
Zhao H, Wang Y, Zhao M, Tan Q, Guo S. Day-Ahead Market Modeling for Strategic Wind Power Producers under Robust Market Clearing. Energies. 2017; 10(7):924.Chicago/Turabian Style
Zhao, Huiru; Wang, Yuwei; Zhao, Mingrui; Tan, Qingkun; Guo, Sen. 2017. "Day-Ahead Market Modeling for Strategic Wind Power Producers under Robust Market Clearing." Energies 10, no. 7: 924.
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