计及电价不确定性和损耗成本的储能竞价策略

李柯江; 宋天昊; 韩肖清; 张东霞

doi:10.7500/AEPS20200219005

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计及电价不确定性和损耗成本的储能竞价策略

学术研究 | 更新时间：2025-06-16

- 计及电价不确定性和损耗成本的储能竞价策略
- Bidding Strategy of Energy Storage Considering Electricity Price Uncertainty and Loss Cost
- 电力系统自动化-方正平台 2020年44卷第17期页码：52-59
- 作者机构：
  
  太原理工大学电气与动力工程学院，山西省太原市 030024
- 作者简介：
  
  李柯江(1996—)，男，硕士研究生，主要研究方向：新能源消纳、电力市场。E-mail：likejiangwzx@163.com
  宋天昊(1994—)，男，博士研究生，主要研究方向：储能规划与运行优化。E-mail：song_th510@163.com
  韩肖清(1964—)，女，通信作者，教授，博士生导师，主要研究方向：电力系统运行与控制、微电网及新能源技术。E-mail：hanxiaoqing@tyut.edu.cn
- 基金信息：
  
  国家自然科学基金-山西煤基低碳联合基金项目(U1910216)
- DOI：10.7500/AEPS20200219005
  中图分类号：
- 收稿日期：2020-02-19，
  
  修回日期：2020-05-19，
  
  网络出版日期：2020-06-24，
  
  纸质出版日期：2020-09-10
- 稿件说明：
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李柯江,宋天昊,韩肖清等.计及电价不确定性和损耗成本的储能竞价策略[J].电力系统自动化,2020,44(17):52-59.

LI Kejiang,SONG Tianhao,HAN Xiaoqing,et al.Bidding Strategy of Energy Storage Considering Electricity Price Uncertainty and Loss Cost[J].Automation of Electric Power Systems,2020,44(17):52-59.
李柯江,宋天昊,韩肖清等.计及电价不确定性和损耗成本的储能竞价策略[J].电力系统自动化,2020,44(17):52-59. DOI： 10.7500/AEPS20200219005.

LI Kejiang,SONG Tianhao,HAN Xiaoqing,et al.Bidding Strategy of Energy Storage Considering Electricity Price Uncertainty and Loss Cost[J].Automation of Electric Power Systems,2020,44(17):52-59. DOI： 10.7500/AEPS20200219005.

摘要

储能是促进新能源消纳、提高电力系统稳定性和灵活性的有效措施。然而储能参与电力市场的策略极其复杂，现已成为实现储能商业化应用的关键问题之一。文中提出储能在日前和实时市场价格不确定环境下考虑循环损耗成本的最优竞价策略。为权衡储能多次循环增加的售电利润和损耗成本，在制定储能竞价策略时，将其循环损耗成本的影响计及在内，并充分考虑电池充、放电深度对循环损耗成本和利润的影响；在日前市场中建立电价-电量投标模型，对电价和电量同时进行投标以充分考虑电价不确定性；在实时市场中建立电量投标模型对日前市场投标进行弥补修正，使竞价策略更加合理与优化。算例验证了所提储能竞价策略的有效性，并说明所建模型可以确定最优电池充、放电深度。

Abstract

Energy storage is an effective measure to promote the consumption of renewable energy and improve the stability and flexibility of power system. The strategy of energy storage participating in the electricity market is extremely complex

which has become one of the key issues for the commercial application of energy storage. With uncertain electricity prices in day-ahead and real-time electricity markets

this paper proposes an optimal bidding strategy of energy storage considering cycle loss cost. In order to weigh the increasing profit of electricity sales and loss cost after multiple energy storage cycles

the impact of its cycle loss cost is considered when formulating the energy storage bidding strategy. And the impact of battery charging and discharging depth on cycle loss cost and profit is fully considered. In day-ahead market

an electricity price-quantity bidding model is established to bid for electricity price and electricity quantity simultaneously to fully consider the uncertainty of electricity price. In real-time market

the electricity quantity bidding model is established to revise and amend the bidding in day-ahead market

so that the bidding strategy is more reasonable and optimal. Case studies verify the effectiveness of the proposed energy storage bidding strategy

and indicate that the model can determine the optimal battery charging and discharging depth.

关键词

Keywords

references

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