Techno-Economic Feasible Region Study on New Energy Storage Participating in Electricity Market

Sirui ZHANG; Dong XIA; Dingchang TAN

doi:10.16513/j.2096-2185.DE.2409108

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Distributed Energy ›› 2024, Vol. 9 ›› Issue (1) : 64-71. DOI: 10.16513/j.2096-2185.DE.2409108

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Techno-Economic Feasible Region Study on New Energy Storage Participating in Electricity Market

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Abstract

New energy storage is pivotal for smoothing fluctuations in renewable energy generation and adapting to dynamic changes in load, and it is a crucial support for future power systems. With policies allowing new energy storage as an independent participant in the power market, studying its technical and economic feasible region during market transactions becomes crucial to influence the widespread application and realization of commercial value in power systems. This paper establishes a trading model for new energy storage participating in electricity markets, outlines economic calculation methods for its participation in the electricity energy and peak shaving auxiliary service markets. Focusing on trading power, it characterizes the technical and economic feasible region of new energy storage in the electricity energy and auxiliary service markets, and studies the impact of factors like charge-discharge power and electricity prices. Through Matlab simulation analysis, the proposed method can effectively enhance situational awareness for new energy storage transactions, and provide decision-making support for market investors.

Key words

new energy storage / electric energy market / auxiliary service market / transactions / techno-economic feasible region

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Sirui ZHANG , Dong XIA , Dingchang TAN. Techno-Economic Feasible Region Study on New Energy Storage Participating in Electricity Market[J]. Distributed Energy Resources. 2024, 9(1): 64-71 https://doi.org/10.16513/j.2096-2185.DE.2409108

References

List( Publishing order | Descend order by publishing year | Descend order by cited within ) Chart analysis

[1]

陈国平，董昱，梁志峰. 能源转型中的中国特色新能源高质量发展分析与思考[J]. 中国电机工程学报，2020, 40(17): 5493-5506.

CHEN

Guoping

, DONG

, LIANG

Zhifeng

. Analysis and reflection on high-quality development of new energy with chinese characteristics in energy transition[J]. Proceedings of the CSEE, 2020, 40(17): 5493-5505.

Cited in this article [1]

[2]	武海燕，闫桂红，刘紫玉，等. 考虑安全稳定约束的电网新能源承载能力分析[J]. 内蒙古电力技术，2022, 40(4): 61-67. WU Haiyan, YAN Guihong, LIU Ziyu, et al. Analysis of new energy carrying capacity of power grid considering security and stability constraints[J]. Inner Mongolia Electric Power, 2022, 40(4): 61-67. Cited in this article [1]

[3]

梁琛，王维洲，马喜平，等. 基于随机潮流的高比例新能源接入配电网的极限线损分析[J]. 智慧电力，2022, 50(12): 34-40, 78.

LIANG

Chen

, WANG

Weizhou

, MA

Xiping

, et al. Analysis on limit line loss in high proportion of renewable energy distribution network based on stochastic power flow[J]. Smart Power, 2022, 50(12): 34-40, 78.

Cited in this article [1]

[4]	温佳鑫，卜思齐，陈麒宇，等. 基于数据学习的新能源高渗透电网频率风险评估[J]. 发电技术，2021, 42(1): 40-47. WEN Jiaxin, BU Siqi, CHEN Qiyu, et al. Data learning-based frequency risk assessment in a high-penetrated renewable power system[J]. Power Generation Technology, 2021, 42(1): 40-47. Cited in this article [1]

[5]	刘大正，崔咏梅，赵飞. 新型储能商业化运行模式分析与发展建议[J]. 分布式能源，2022, 7(5): 46-55. LIU Dazheng, CUI Yongmei, ZHAO Fei. Operating mode analysis and developmental suggestions of new energy storage in commercial application scenarios [J]. Distributed Energy, 2022, 7(5): 46-55. Cited in this article [1]

[6]

王彩霞，时智勇，梁志峰，等. 新能源为主体电力系统的需求侧资源利用关键技术及展望[J]. 电力系统自动化，2021, 45(16): 37-48.

WANG

Caixia

, SHI

Zhiyong

, LIANG

Zhifeng

, et al. Key technologies and prospects of demand-side resource utilization for power systems dominated by renewable energy[J]. Automation of Electric Power Systems, 2021, 45(16): 37-48.

Cited in this article [1]

[7]	肖云鹏，王锡凡，王秀丽，等. 面向高比例可再生能源的电力市场研究综述[J]. 中国电机工程学报，2018, 38(3): 663-674. XIAO Yunpeng, WANG Xifan, WANG Xiuli, et al. Review on electricity market towards high proportion of renewable energy[J]. Proceedings of the CSEE, 2018, 38(3): 663-674. Cited in this article [1]

[8]	鲁跃峰，郭祚刚，谷裕，等. 国内外新型储能相关政策及商业模式分析[J]. 储能科学与技术，2023, 12(9): 3019-3032. LU Yuefeng, GUO Zuogang, GU Yu, et al. Analysis of new energy storage policies and business models in China and abroad[J]. Energy Storage Science and Technology, 2023, 12(9): 3019-3032. Cited in this article [1]

[9]

时智勇，王彩霞，胡静. 独立新型储能电站价格形成机制及成本疏导优化方法[J]. 储能科学与技术，2022, 11(12): 4067-4076.

SHI

Zhiyong

, WANG

Caixia

, HU

Jing

. A price formation mechanism and cost diversion optimization method for designing an independently new energy-storing power station[J]. Energy Storage Science and Technology, 2022, 11(12): 4067-4076.

Cited in this article [1]

[10]	张忠，刘玥，石智豪. 储能的竞价策略及电力市场出清方法研究[J]. 电网技术，2023, 47(11): 4555-4564. ZHANG Zhong, LIU Yue, SHI Zhihao. Bidding strategy of energy storage and corresponding market clearing methods [J]. Power System Technology, 2023, 47(11): 4555-4564. Cited in this article [1]

[11]

叶晖，李爱魁，田刚领，等. 考虑能量效率和SOC均衡的电池储能电站双层功率分配策略[J/OL]. 中国电机工程学报：1-11[2023-09-25].

https://kns-cnki-net.webvpn.ncepu.edu.cn/kcms/detail/11.2107.tm.20230919.1029.002.html

Hui

, LI

Aikui

, TIAN

Gangling

, et al. Double-layer power distribution strategy for battery storage power station considering energy efficiency and state-of-charge balance[J/OL]. Proceedings of the CSEE: 1-11[2023-09-25].

https://kns-cnki-net.webvpn.ncepu.edu.cn/kcms/detail/11.2107.tm.20230919.1029.002.html

Cited in this article [1]

[12]	李建林，康靖悦，董子旭，等. 共享储能电站优化选址定容研究[J]. 分布式能源，2022, 7(3): 1-11. LI Jianlin, KANG Jingyue, DONG Zixu, et al. Optimal location and capacity of shared energy storage power station[J]. Distributed Energy, 2022, 7(3): 1-11. Cited in this article [1]

[13]

齐彩娟，车彬，杨燕，等. 考虑新能源消纳与储能参与调频的共享储能主从博弈鲁棒定价方法[J]. 中国电力，2023, 56(8): 26-39.

Caijuan

, CHE

Bin

, YANG

Yan

, et al. Master-slave game-based robust pricing method of shared energy storage considering renewable energy accommodation and energy storage participating in frequency modulation[J]. Electric Power, 2023, 56(8): 26-39.

Cited in this article [1]

[14]	CHEN C, ZHU Y, ZHANG T, et al. Two-stage multiple cooperative games-based joint planning for shared energy storage and local integrated energy systems[J]. Energy, 2023, 284: 129114. Cited in this article [1]

[15]	SONG X, ZHANG H, FAN L, et al. Planning shared energy storage systems for the spatio-temporal coordination of multi-site renewable energy sources on the power generation side[J]. Energy, 2023, 282: 128976. Cited in this article [1]

[16]	DING Y, XU Q, HAO L, et al. A stackelberg game-based robust optimization for user-side energy storage configuration and power pricing[J]. Energy, 2023, 283: 128429. Cited in this article [1]

[17]	鹿婷，贾继超，彭晓涛. 一种考虑经济调度的风电场储能控制策略[J]. 分布式能源，2019, 4(3): 40-49. LU Ting, JIA Jichao, PENG Xiaotao. An energy storage control strategy for wind farm considering economic dispatching[J]. Distributed Energy, 2019, 4(3): 40-49. Cited in this article [1]

[18]	傅旭，李富春，杨欣，等. 基于全寿命周期成本的储能成本分析[J]. 分布式能源，2020, 5(3): 34-38. FU Xu, LI Fuchun, YANG Xin, et al. Cost analysis of energy storage based on life cycle cost[J]. Distributed Energy, 2020, 5(3): 34-38. Cited in this article [1]

[19]

詹祥澎，杨军，韩思宁，等. 考虑电动汽车可调度潜力的充电站两阶段市场投标策略[J]. 电力系统自动化，2021, 45(10): 86-96.

ZHAN

Xiangpeng

, YANG

Jun

, HAN

Sining

, et al. Two-stage market bidding strategy of charging station considering schedulable potential capacity of electric vehicle[J]. Automation of Electric Power Systems, 2021, 45(10): 86-96.

Cited in this article [1]

[20]	王亚莉，叶泽，黄际元，等. 基于动态峰谷时段划分的储能调峰调频经济调度研究[J]. 中国电力，2022, 55(8): 64-72. WANG Yali, YE Ze, HUANG Jiyuan, et al. Research on economic scheduling of ES peak and frequency regulation based on dynamic peak-valley time division[J]. Electric Power, 2022, 55(8): 64-72. Cited in this article [2]