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1.大连理工大学电子信息与电气工程学院,辽宁省大连市 116024
2.大连理工大学水电与水信息研究所,辽宁省大连市 116024
3.昆明电力交易中心有限责任公司,云南省昆明市 650011
4.华北水利水电大学水资源学院,河南省郑州市 450046
白庆立(1996—),男,硕士研究生,主要研究方向:清洁能源电力市场。E-mail:a15394848640@mail.dlut.edu.cn
赵志鹏(1992—),男,通信作者,博士,准聘副教授,主要研究方向:大规模水库优化调度方法及水电竞价。E-mail:dlutzhaozhipeng@foxmail.com
靳晓雨(1995—),男,博士研究生,主要研究方向:清洁能源电力市场、水风光多能源互补调度。E-mail:jxyleureka@163.com
收稿:2023-01-18,
修回:2023-07-08,
网络出版:2023-09-11,
纸质出版:2024-06-10
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白庆立,赵志鹏,靳晓雨等.考虑风电出力和电价不确定性的水风联合现货市场竞价策略[J].电力系统自动化,2024,48(11):122-133.
BAI Qingli,ZHAO Zhipeng,JIN Xiaoyu,et al.Hydro-Wind Power Joint Bidding Strategies for Electricity Spot Market Considering Uncertainties of Wind Power Output and Electricity Price[J].Automation of Electric Power Systems,2024,48(11):122-133.
白庆立,赵志鹏,靳晓雨等.考虑风电出力和电价不确定性的水风联合现货市场竞价策略[J].电力系统自动化,2024,48(11):122-133. DOI: 10.7500/AEPS20230118004.
BAI Qingli,ZHAO Zhipeng,JIN Xiaoyu,et al.Hydro-Wind Power Joint Bidding Strategies for Electricity Spot Market Considering Uncertainties of Wind Power Output and Electricity Price[J].Automation of Electric Power Systems,2024,48(11):122-133. DOI: 10.7500/AEPS20230118004.
以风电为代表的新能源参与现货市场已是大势所趋,但出力不确定性导致其市场竞争力较弱,而电价的不确定性又进一步增大了其承担的收益风险。联合具有灵活调节能力的水电是有效的解决途径,而制定符合决策者风险意愿的竞价策略则是其中亟须解决的关键问题。为此,从价格接受者角度提出了水电联合风电参与现货市场的竞价模型。模型中采用笛卡尔积组合后的典型场景集描述风电出力、市场电价等多种不确定性,采用条件风险价值衡量不确定性导致的市场风险,并以风险因子作为决策者风险偏好纳入决策过程。通过引入0/1整数变量,将模型中的非线性函数转换为混合整数线性规划模型予以求解。以中国西南某省梯级水电站和风电场为背景,验证了模型的有效性,并进一步分析了风险偏好对竞价决策的影响。
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.
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