Bidding strategy of wind-solar hybrid generation system in the spot market considering bidding deviation penalty

• Published in: IOP conference series. Earth and environmental science Vol. 770; no. 1; pp. 12028 - 12033
• Main Authors: You, Daning, Liu, Hanghang, Si, Juncheng, Zhou, Lei, Sun, Mingyu, Jiang, Ting
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.05.2021
• Subjects: Alternative energy sources; Complementarity; Deviation; Electric power; Electric power generation; Electric power grids; Electricity distribution; Electricity pricing; Energy consumption; Energy output; Energy storage; Hybrid systems; Markets; Mixed integer; Optimization; Probability distribution; Renewable energy; Renewable resources; Solar energy; Strategy; Wind
• ISSN: 1755-1307; 1755-1315; 1755-1315
• DOI: 10.1088/1755-1315/770/1/012028

In recent years, as State Grid Shandong Electric Power Company is one of the key pilot construction units of the new strategy of “realizing the coordination and interaction of source network, load and storage”, renewable energy power generation systems have gradually changed from a subsidy object to an independent bidding subject when participating in the spot power market of Shandong Province. The uncertainty of renewable energy output and spot market price leads to the loss caused by bidding deviation when participating in the power market competition, and the income drops significantly. The good complementarity of wind and solar energy can reduce the fluctuation of renewable energy output and promote renewable energy consumption. First, the joint output probability distribution of a wind-solar hybrid generation system is simulated based on Copula function. Then, aimed at maximizing the bidding profit of the wind-solar hybrid generation system in spot market, a two-stage mixed integer stochastic optimization bidding model considering bidding deviation penalty is established. The conditional value at risk theory is used to evaluate the risk of renewable energy and electricity price forecast deviation, and the optimal bidding strategy is obtained.