@inproceedings{a99023651d004345a4f36c789e56313d,
title = "Chance-constrained bidding model for wind-storage system participation in the electricity market",
abstract = "The significant uncertainty in wind power output severely hinders the precise execution of electricity market bidding plans, potentially leading to substantial deviation penalties for wind farms. Energy storage, as a valuable resource for frequency regulation, plays a crucial role in mitigating these power discrepancies caused by wind variability. To minimize economic losses from bidding decision errors, this paper establishes a novel joint wind-storage system bidding model. The model takes into account the uncertainties of wind power output and applies chance constraints to manage the discrepancy between actual system output and bidding power. By applying the Conditional Value-at-Risk (CVaR) theory, the complex chance constraints are simplified into solvable inequalities. Simulation results confirm the model's accuracy and efficiency.",
keywords = "bidding strategy, chance constraints, electricity market, wind-storage system",
author = "Fengshuo Xiao and Xiong Wu and Guodong Guo and Dong Liu and Yawei Xue and Shengjin Huang",
note = "Publisher Copyright: Copyright {\textcopyright} 2025 SPIE.; 2nd International Conference on Power Electronics and Artificial Intelligence, PEAI 2025 ; Conference date: 17-01-2025 Through 19-01-2025",
year = "2025",
doi = "10.1117/12.3066790",
language = "英语",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Qiang Yang and Mahalle, \{Parikshit N.\} and Xuehe Wang",
booktitle = "Second International Conference on Power Electronics and Artificial Intelligence, PEAI 2025",
}