Price-quantity curve construction strategy for wind-storage power plants participating in the day-ahead spot market

Chu QI, Yilin LI, Siyao DU, Fanpeng ZENG, Xianmin MU, Quan LV, Zhiqiang WANG

Electric Power ›› 2026, Vol. 59 ›› Issue (8) : 194-204.

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Electric Power ›› 2026, Vol. 59 ›› Issue (8) : 194-204. DOI: 10.11930/j.issn.1004-9649.202604017
Original article

Price-quantity curve construction strategy for wind-storage power plants participating in the day-ahead spot market

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Abstract

In the context where wind-storage power plants are gradually participating in the electricity spot market under the "both quantity and price bidding"mode,this paper studies the decision-making problem of constructing price-quantity curves for wind-storage combined systems in the day-ahead energy market.Comprehensively considering the uncertainties of wind power output and electricity prices,energy storage lifetime degradation costs,and market rule constraints,a stochastic optimization model aimed at maximizing expected revenue is established.The model simulates the uncertainties of wind power output and market prices using the scenario method and generates optimal hourly price-quantity curves using a mixed-integer linear programming approach.Case study results show that the proposed model can effectively improve the market revenue performance of wind-storage power plants.Compared with the traditional"quantity-only bidding"mode,the price-quantity curve bidding strategy demonstrates significant advantages in reducing uncertainty costs and optimizing economic benefits.Furthermore,increasing the number of bidding segments significantly promotes revenue enhancement. The research results provide scientific decision support for the market-oriented operation of wind-storage power plants.

Key words

wind-storage power plant / spot market / price-quantity curve / bidding decision

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Chu QI , Yilin LI , Siyao DU , et al . Price-quantity curve construction strategy for wind-storage power plants participating in the day-ahead spot market[J]. Electric Power. 2026, 59(8): 194-204 https://doi.org/10.11930/j.issn.1004-9649.202604017

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Funding

National Key Research and Development Program of China(2025YFA1017900)

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