数据驱动的机会约束的风力-电解联合系统容量提供

IF 3.3 Q3 ENERGY & FUELS
Xuemei Dai;Chunyu Chen;Bixing Ren;Shengfei Yin
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引用次数: 0

摘要

碱性水电解槽(AWE)将风力发电场(WF)的波动电力转化为剩余电力,是一种有前景的大规模和具有成本效益的制氢技术。考虑到AWE和WF在提供市场服务方面的互补性,本文将AWE和WF视为一个联盟,提出了能源市场和监管市场的联合竞标策略,以最大化联盟的收益。为了克服风能和氢气不确定性的影响,我们首先建立了一个数据驱动的分布鲁棒机会约束投标模型,该模型通过观察不确定性相关的机会约束来降低市场风险。然后,我们用Shapley值法来评估AWE和WF的边际贡献。在此基础上,提出了基于博弈论的招标收益分配方案。最后,基于真实市场数据的案例研究表明,与单个竞价策略相比,所提出的联合竞价策略的总利润增加了27.4%。与仅参与能源市场相比,制氢的平均边际成本可降低5.1~ {\$}/$ kg。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data-Driven Chance-Constrained Capacity Offering for Wind-Electrolysis Joint Systems
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.
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来源期刊
CiteScore
7.80
自引率
5.30%
发文量
45
审稿时长
10 weeks
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