Hydro-Wind Power Joint Bidding Strategies for Electricity Spot Market Considering Uncertainties of Wind Power Output and Electricity Price

被引：0
|
作者：
Bai Q. [1 ,2 ,3 ]
Zhao Z. [1 ]
Jin X. [2 ]
Cheng C. [2 ]
Deng Z. [2 ]
Jia Z. [4 ]
机构：
[1] School of Electronic Information & Electrical Engineering, Dalian University of Technology, Dalian
[2] Institute of Hydropower & Hydroinformatics, Dalian University of Technology, Dalian
[3] Kunming Power Exchange Center Co., Ltd., Kunming
[4] School of Water Resources, North China University of Water Resources and Electric Power, Zhengzhou
来源：
Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2024年 / 48卷 / 11期
基金：
中国国家自然科学基金;
关键词：
electricity spot market; hydro-wind power joint bidding strategy; hydropower dispatch; risk preference; typical scenario set;
D O I：
10.7500/AEPS20230118004
中图分类号：
学科分类号：
摘要：
It is a general trend for renewable energy represented by wind power to participate in the electricity spot market, but the uncertainty of wind power output makes its market competitiveness weak, while the uncertainty of electricity price further increases the revenue risk it bears. Combining hydropower with flexible regulation capabilities is an effective solution, and formulating bidding strategies that align with the risk willingness of decision-makers is a key issue that needs to be solved urgently. Therefore, from the perspective of price takers, a bidding model of hydropower combined with wind power participating in the electricity spot market is proposed. In the model, a typical scenario set after Cartesian product combination is used to describe multiple uncertainties such as wind power output and market price, the conditional value at risk (CVaR) is used to measure the market risk caused by uncertainties, and the risk factor is included in the decision-making process as the risk preference of the decision-makers. The nonlinear function in the model is solved by introducing 0/1 integer variables and transforming it into a mixed-integer linear programming (MILP) model. The effectiveness of the model is validated against the background of a cascade hydropower station and a wind farm in a certain province in Southwestern China, and the impact of risk preference on bidding decisions is further analyzed. © 2024 Automation of Electric Power Systems Press. All rights reserved.
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页码：122 / 133
页数：11
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