考虑后悔规避的风储联合参与日前市场竞标策略
DOI:
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

TM 732;

基金项目:

国家自然科学基金项目(面上项目,重点项目,重大项目)


Bidding Strategy of Wind-storage Combined System Participating in Day-ahead Market Based on Regret Aversion
Author:
Affiliation:

Fund Project:

The National Natural Science Foundation of China (General Program, Key Program, Major Research Plan)

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    为应对风储联合参与日前市场竞标的风险,减弱决策者的后悔心理,本文提出了一种考虑后悔规避的风储联合参与日前市场竞标策略。采用蒙特卡洛方法将风电出力、市场电价的随机模型转化为多概率场景的确定模型;在日前市场竞标阶段,引入后悔度指标描述风储联合系统的后悔心理,同时考虑实时市场的不平衡结算因素,以最小-最大后悔度为优化目标,建立风储联合参与日前市场的竞标模型。最后,通过算例分析将本文方法与随机规划法和鲁棒优化法的竞标策略进行对比,验证了本文所提方法的有效性和可行性。

    Abstract:

    In order to cope with the risk of wind-storage combined system participating in day-ahead market bidding and reduce the regret of decision makers, in this paper, a strategy for participation of wind-storage combined system in day-ahead market bidding with consideration of regret aversion was proposed. The Monte Carlo method was used to transform the stochastic model of wind power output and market electricity price into a deterministic model of multi-probability scenarios. In the day-ahead market bidding stage, the regret degree was introduced to describe the regret psychology of the wind-storage combined system, and the imbalance settlement of the real-time market was also considered. A bidding model of wind-storage combined system participating in the day-ahead market was established,with the minimum-maximum regret degree as the optimization objective. Finally, the method in this paper was compared with the bidding strategies of stochastic optimization method and robust optimization method through the analysis of examples. It can be seen that the method proposed in this paper is effective and feasible.

    参考文献
    相似文献
    引证文献
引用本文

姚生奎,钟浩,袁文,等. 考虑后悔规避的风储联合参与日前市场竞标策略[J]. 科学技术与工程, 2022, 22(7): 2735-2740.
Yao Shengkui, Zhong Hao, Yuan Wen, et al. Bidding Strategy of Wind-storage Combined System Participating in Day-ahead Market Based on Regret Aversion[J]. Science Technology and Engineering,2022,22(7):2735-2740.

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2021-05-26
  • 最后修改日期:2022-02-24
  • 录用日期:2021-11-10
  • 在线发布日期: 2022-03-16
  • 出版日期:
×
律回春渐,新元肇启|《科学技术与工程》编辑部恭祝新岁!
亟待确认版面费归属稿件,敬请作者关注