{"title":"Data-Driven Chance-Constrained Capacity Offering for Wind-Electrolysis Joint Systems","authors":"Xuemei Dai;Chunyu Chen;Bixing Ren;Shengfei Yin","doi":"10.1109/OAJPE.2025.3545858","DOIUrl":null,"url":null,"abstract":"An alkaline water electrolyzer (AWE) that converts surplus electricity from fluctuating power of a wind farm (WF) is a promising technology for large-scale and cost-effective hydrogen production. By considering the complementarity of the AWEs and the WF in offering market services, this paper treats the AWE and the WF as a coalition and proposes a joint bidding strategy in the energy and regulation markets to maximize the coalition’s revenue. To overcome the influence of wind and hydrogen uncertainties, we first establish a data-driven distributionally robust chance-constrained bidding model, which reduces market risks by observing uncertainty-related chance constraints for any distribution in the ambiguity set. Then, we use the Shapley value method to evaluate the marginal contribution of the AWE and the WF. Further we propose a game-theory-based bidding revenue allocation scheme. Eventually, case studies based on real-world market data demonstrate that the total profit of the proposed joint bidding strategy increases 27.4% if compared with individual bidding strategy. The average marginal cost of hydrogen production can be reduced by <inline-formula> <tex-math>$5.1~ {\\$}/$ </tex-math></inline-formula>kg if compared with only participating in the energy market.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"111-121"},"PeriodicalIF":3.3000,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10908898","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Open Access Journal of Power and Energy","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10908898/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
An alkaline water electrolyzer (AWE) that converts surplus electricity from fluctuating power of a wind farm (WF) is a promising technology for large-scale and cost-effective hydrogen production. By considering the complementarity of the AWEs and the WF in offering market services, this paper treats the AWE and the WF as a coalition and proposes a joint bidding strategy in the energy and regulation markets to maximize the coalition’s revenue. To overcome the influence of wind and hydrogen uncertainties, we first establish a data-driven distributionally robust chance-constrained bidding model, which reduces market risks by observing uncertainty-related chance constraints for any distribution in the ambiguity set. Then, we use the Shapley value method to evaluate the marginal contribution of the AWE and the WF. Further we propose a game-theory-based bidding revenue allocation scheme. Eventually, case studies based on real-world market data demonstrate that the total profit of the proposed joint bidding strategy increases 27.4% if compared with individual bidding strategy. The average marginal cost of hydrogen production can be reduced by $5.1~ {\$}/$ kg if compared with only participating in the energy market.