Revenue Model and Bidding Strategies for Stand Alone Energy Storage Participation in Spot Markets

YUAN Cen; DAI Jiang; WANG Mingjie; YANG Yue; WANG Mingyang; YAO Gang; ZHU Silin

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Revenue Model and Bidding Strategies for Stand Alone Energy Storage Participation in Spot Markets

更新时间：2025-09-25

- Revenue Model and Bidding Strategies for Stand Alone Energy Storage Participation in Spot Markets
- Issue 5, (2025)
- 作者机构：
  
  贵州电网有限责任公司电力调度控制中心
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2025
- 稿件说明：
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YUAN Cen, DAI Jiang, WANG Mingjie, et al. Revenue Model and Bidding Strategies for Stand Alone Energy Storage Participation in Spot Markets [J]. 2025, (5).
DOI：

YUAN Cen, DAI Jiang, WANG Mingjie, et al. Revenue Model and Bidding Strategies for Stand Alone Energy Storage Participation in Spot Markets [J]. 2025, (5). DOI：

摘要

电力现货市场通过供需关系发现电力价格，引导电力资源的精准高效配置。独立储能参与电力现货市场有助于利用价格信号指导主体参与电网的高峰顶峰与低谷消纳，从而提升电力系统运行效率。该文基于南方区域电力现货市场出清模型及独立储能价格政策，研究了储能参与电力现货市场的盈利模式及报量报价、报量不报价两种参与方式下的报价策略。首先，基于出清模型与储能价格政策，构建了以收益最大化为目标的储能充放电模型。其次，依据所构建的模型，提出了报量不报价、报量报价两种参与现货模式下的储能申报策略。最后，基于南方区域电力现货市场2024年11月结算试运行数据，测算了峰谷分时电价机制、报量不报价参与现货市场、报量报价参与现货市场三种模式下的预期收益，并分析了影响储能收益的关键因素。研究结果表明，在验证场景下，市场价格信号可有效引导储能充放电；在设定的储能价格政策下报量报价参与市场模式较报量不报价模式盈利能力更强，可获得疏导电网阻塞带来的经济效益。同时结果也证明，现货市场价格曲线、所在电网节点位置是影响储能在市场中获利能力的关键因素。

Abstract

Electricity spot markets discover real-time power prices through supply-demand dynamics to optimize power resource allocation. Independent energy storage participation leverages price signals to support grid peak-shaving and valley-filling

enhancing system efficiency. This study proposes storage revenue models and bidding strategies—comparing quantity bidding with price offers versus without price offers—using electricity spot market in the China Southern Region clearing mechanism and storage pricing policies. A revenue-maximizing charge-discharge optimization model was developed

and price declaration strategies for both participation schemes were formulated. Based on November 2024 actual data from the Southern Regional Electricity Spot Market

expected revenues were quantified across three operational modes: 1) time-of-use pricing

2) spot market participation with quantity-only bidding

and 3) spot market participation with quantity-price bidding

with key profitability factors analyzed. Results demonstrate effective price-guided storage operation

confirming that under current policies

the price-offer scheme delivers higher profitability than the non-price-offer alternative by capturing congestion management benefits. Simultaneously

the results confirm that market price curves and the grid node location critically determines the revenue potential of energy storage in electricity markets.

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references

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关立,周蕾,刘航航,等.独立储能电站参与电力现货市场机制及试运行分析[J].中国电力,2022,55(10):185-190.

殷豪,丁伟锋,陈顺,等.基于长短时记忆网络-纵横交叉算法的含高比例新能源电力市场日前电价预测[J].电网技术,2022,46(02):472-480.

韩升科,胡飞虎,陈之腾,等.基于GCN-LSTM的日前市场边际电价预测[J].中国电机工程学报,2022,42(09):3276-3286.

李明节,陈国平,董存,等.新能源电力系统电力电量平衡问题研究[J].电网技术,2019,43(11):3979-3986.

舒印彪,张智刚,郭剑波,等.新能源消纳关键因素分析及解决措施研究[J].中国电机工程学报,2017,37(01):1-9.

王皓,张舒淳,李维展,等.储能参与电力系统应用研究综述[J].电工技术,2020,(03):21-24+27.

赵小磊,姚良忠,刘运鑫,等.面向储能多应用价值协同的风光储系统日前优化调度方法[J].高电压技术,2024,50(06):2511-2522.

宋柄兵,顾洁.考虑电网输电能力改善的超导储能装置优化选址定容[J].电力系统及其自动化学报,2017,29(11):92-98.

张硕,陈媛丽,李英姿,等.计及电力现货机会成本的构网型储能电站调频辅助服务竞价出清双层博弈模型[J].中国电机工程学报,2024,44(S1):146-158.

李军徽,张靖祥,穆钢,等.辅助服务市场下独立储能调峰调频协同优化调度[J].中国电机工程学报,2025,45(02):650-665.

肖云鹏,张兰,张轩,等.包含独立储能的现货电能量与调频辅助服务市场出清协调机制[J].中国电机工程学报,2020,40(S1):167-180.

胡泽春,蔡福霖,冯建洲.兼顾新能源消纳与频率电压支撑的电池储能系统优化规划[J].电力自动化设备,2024,44(07):3-12.

李建林,丁子洋,游洪灏,等.构网型储能支撑新型电力系统稳定运行研究[J].高压电器,2023,59(07):1-11.

朱思霖,代江,赵翔宇,等.多能源联合运行市场机制的设计及思考[J].电力大数据,2025,28(01):12-22.

陈启鑫,房曦晨,郭鸿业,等.储能参与电力市场机制:现状与展望[J].电力系统自动化,2021,45(16):14-28.

李相俊,王上行,惠东.电池储能系统运行控制与应用方法综述及展望[J].电网技术,2017,41(10):3315-3325.

路小娟,白建聪,范多进,等.风光热储互补发电系统容量配置技术研究[J].热力发电,2024,53(03):51-58.

李雄威,王昕,顾佳伟,等.考虑火电深度调峰的风光火储系统日前优化调度[J].中国电力,2023,56(01):1-7+48.

李军徽,张嘉辉,李翠萍,等.参与调峰的储能系统配置方案及经济性分析[J].电工技术学报,2021,36(19):4148-4160.

李欣然,黄际元,陈远扬,等.大规模储能电源参与电网调频研究综述[J].电力系统保护与控制,2016,44(07):145-153.

Padmanabhan N, Ahmed M, Bhattacharya K, Battery Energy Storage Systems in Energy and Reserve Markets[J]. IEEE Transactions on Power Systems, 2020, 35(1): 215-226.

MOHSENIAN-RAD H. Optimal bidding, scheduling, and deployment of battery systems in California day-ahead energy market[J]. IEEE Transactions on Power Systems, 2016,31(1):442-453．

Payam Z D, Soroush S, Logan R, et al. Price impact assessment for large-scale merchant energy storage facilities[J], Energy, 2017, 125: 27-43.

刘军,吴梦凯,叶泽,等.进一步完善我国峰谷电价政策的思考与建议[J].价格理论与实践,2021,(02):62-66.

关立,周蕾,刘航航,等.独立储能电站参与电力现货市场机制及试运行分析[J].中国电力,2022,55(10):185-190.

殷豪,丁伟锋,陈顺,等.基于长短时记忆网络-纵横交叉算法的含高比例新能源电力市场日前电价预测[J].电网技术,2022,46(02):472-480.

韩升科,胡飞虎,陈之腾,等.基于GCN-LSTM的日前市场边际电价预测[J].中国电机工程学报,2022,42(09):3276-3286.

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