Evaluation of Business Mode for Large-Scale Energy Storage Applications Considering Capacity Constraints

doi:10.11930/j.issn.1004-9649.202101131

Abstract

Abstract: Considering the capacity-related constraints of the application value of energy storage, an accurate quantitative evaluation method for the business mode of large-scale energy storage applications is proposed. A double-cascade function is used to characterize the grid’s requirements for flexible adjustment of resource performance and capacity for energy storage, thermal power, etc. Then according to its revenue in power generation, transmission and distribution, electricity charge, and ancillary service income generated by energy storage at the source, grid, and load side respectively, an income function is established for stakeholders including new energy asset owners, grid operators, users, and energy storage asset owners in the “energy storage +” scenario. Based on stakeholders' share, an energy storage cost function is set up according to the energy storage capacity allocated for the corresponding revenue. Taking account of the investment entities such as new energy, power grids, users or third parties, a game model for energy storage investment is constructed with the objective as the maximization of the net income. Finally, according to the actual situation in Gansu Province, the business mode of large-scale promotion of energy storage under different mode scenarios was evaluated, and the sensitivity analysis of key parameters was conducted to demonstrate the effects of various combinations of operation modes on specific source-load regions. Therefore the feasibility of the proposed method is verified.

Key words: energy storage, business mode, renewable energy, double level model, game theory

KAI Saijiang, TAN Jie, SUN Yiqian, WANG Heng, YUAN Tiejiang. Evaluation of Business Mode for Large-Scale Energy Storage Applications Considering Capacity Constraints[J]. Electric Power, 2022, 55(4): 203-213,228.

Add to citation manager EndNote|Ris|BibTeX

URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202101131

https://www.electricpower.com.cn/EN/Y2022/V55/I4/203

References

[1] 袁铁江, 胡克林, 关宇航, 等. 风电–氢储能与煤化工多能耦合系统及其氢储能子系统的 EMR 建模[J]. 高电压技术, 2015, 41(7): 2156–2164
YUAN Tiejiang, HU Kelin, GUAN Yuhang, et al. Modeling on hydrogen producing progress in EMR based wind power-hydrogen energy storage and coal chemical pluripotent coupling system[J]. High Voltage Engineering, 2015, 41(7): 2156–2164
[2] ALAPERÄ I, HONKAPURO S, TIKKA V, et al. Dual-purposing UPS batteries for energy storage functions: a business case analysis[J]. Energy Procedia, 2019, 158: 5061–5066.
[3] 薛金花, 叶季蕾, 陶琼, 等. 基于多场景的商业园区源-储-荷系统运营模式及投资决策研究[J]. 电力自动化设备, 2019, 39(2): 78–83,92
XUE Jinhua, YE Jilei, TAO Qiong, et al. Multi-scenarios based operation mode and investment decision of source-storage-load system in business park[J]. Electric Power Automation Equipment, 2019, 39(2): 78–83,92
[4] 元博, 张运洲, 鲁刚, 等. 电力系统中储能发展前景及应用关键问题研究[J]. 中国电力, 2019, 52(3): 1–8
YUAN Bo, ZHANG Yunzhou, LU Gang, et al. Research on key issues of energy storage development and application in power systems[J]. Electric Power, 2019, 52(3): 1–8
[5] 康重庆, 姚良忠. 高比例可再生能源电力系统的关键科学问题与理论研究框架[J]. 电力系统自动化, 2017, 41(9): 2–11
KANG Chongqing, YAO Liangzhong. Key scientific issues and theoretical research framework for power systems with high proportion of renewable energy[J]. Automation of Electric Power Systems, 2017, 41(9): 2–11
[6] 白建华, 辛颂旭, 刘俊, 等. 中国实现高比例可再生能源发展路径研究[J]. 中国电机工程学报, 2015, 35(14): 3699–3705
BAI Jianhua, XIN Songxu, LIU Jun, et al. Roadmap of realizing the high penetration renewable energy in China[J]. Proceedings of the CSEE, 2015, 35(14): 3699–3705
[7] HAMELINK M, OPDENAKKER R. How business model innovation affects firm performance in the energy storage market[J]. Renewable Energy, 2019, 131: 120–127.
[8] TSCHIGGERL K, SLEDZ C, TOPIC M. Considering environmental impacts of energy storage technologies: a life cycle assessment of power-to-gas business models[J]. Energy, 2018, 160: 1091–1100.
[9] LI X, CHALVATZIS K J, STEPHANIDES P, et al. Bringing innovation to market: business models for battery storage[J]. Energy Procedia, 2019, 159: 327–332.
[10] 修晓青, 李建林, 李文启, 等. 储能系统商业模式及其优化规划方法[J]. 电力建设, 2019, 40(6): 41–48
XIU Xiaoqing, LI Jianlin, LI Wenqi, et al. Research on business model and optimization planning method of energy storage station[J]. Electric Power Construction, 2019, 40(6): 41–48
[11] 胡静, 李琼慧, 黄碧斌, 等. 适应中国应用场景需求和政策环境的电网侧储能商业模式研究[J]. 全球能源互联网, 2019, 2(4): 367–375
HU Jing, LI Qionghui, HUANG Bibin, et al. Business model research of energy storage on grid side adapted to application scenarios and policy environment in China[J]. Journal of Global Energy Interconnection, 2019, 2(4): 367–375
[12] 曾辉, 孙峰, 邵宝珠, 等. 澳大利亚100 MW储能运行分析及对中国的启示[J]. 电力系统自动化, 2019, 43(8): 86–92
ZENG Hui, SUN Feng, SHAO Baozhu, et al. Analysis of Australian 100 MW energy storage operation and its enlightenment to China[J]. Automation of Electric Power Systems, 2019, 43(8): 86–92
[13] HARTMANN B, VOKONY I, SORÉS P, et al. Service aspect assessment of energy storage under the ownership of distribution system operators[J]. Journal of Energy Storage, 2019, 25: 100861.
[14] HARTMANN B, DIVÉNYI D, VOKONY I. Evaluation of business possibilities of energy storage at commercial and industrial consumers–a case study[J]. Applied energy, 2018, 222: 59–66.
[15] LOMBARDI P, SCHWABE F. Sharing economy as a new business model for energy storage systems[J]. Applied energy, 2017, 188: 485–496.
[16] LIU J, ZHANG N, KANG C, et al. Cloud energy storage for residential and small commercial consumers: a business case study[J]. Applied Energy, 2017, 188: 226–236.
[17] 王宣元, 刘敦楠, 刘蓁, 等. 泛在电力物联网下虚拟电厂运营机制及关键技术[J]. 电网技术, 2019, 43(9): 3175–3183
WANG Xuanyuan, LIU Dunnan, LIU Zhen, et al. Operation mechanism and key technologies of virtual power plant under ubiquitous internet of things[J]. Power System Technology, 2019, 43(9): 3175–3183
[18] 丁玉龙, 来小康, 陈海生. 储能技术及应用[M]. 北京: 化学工业出版社, 2018.
[19] 方彤, 蒋东方, 杨洋, 等. 基于NSGA-II和熵权法的氢综合能源系统商业运营模式[J]. 中国电力, 2022, 55(1): 110–118
FANG Tong, JIANG Dongfang, YANG Yang, et al. Research on business operation mode of hydrogen integrated energy system based on NSGA-II and entropy weight method[J]. Electric Power, 2022, 55(1): 110–118
[20] 陈晨, 李端超, 王海伟, 等. 考虑不确定性的综合能源系统日前经济调度[J]. 电力科学与技术学报, 2021, 36(2): 24–30
CHEN Chen, LI Duanchao, WANG Haiwei, et al. Study on day-ahead economic dispatch of integrated energy system considering uncertainty[J]. Journal of Electric Power Science and Technology, 2021, 36(2): 24–30
[21] 胡伟, 杨梓俊, 王瑾然, 等. 园区综合能源系统日前多目标优化调度[J]. 电力科学与技术学报, 2021, 36(1): 13–20
HU Wei, YANG Zijun, WANG Jinran, et al. Multi-objective optimal scheduling of integrated energy system in the industry park[J]. Journal of Electric Power Science and Technology, 2021, 36(1): 13–20
[22] 蒋东方, 贾跃龙, 鲁强, 等. 氢能在综合能源系统中的应用前景[J]. 中国电力, 2020, 53(5): 135–142
JIANG Dongfang, JIA Yuelong, LU Qiang, et al. Application prospect of hydrogen energy in integrated energy systems[J]. Electric Power, 2020, 53(5): 135–142
[23] 黄帅飞, 丁晓群, 高乾恒, 等. 光-氢-储系统接入配电网的有功-无功协调优化[J]. 南方电网技术, 2018, 12(7): 44–51
HUANG Shuaifei, DING Xiaoqun, GAO Qianheng, et al. Active-reactive power coordination optimization in distribution network interconnected with photovoltaic-hydrogen-energy storage systems[J]. Southern Power System Technology, 2018, 12(7): 44–51
[24] 杨祺铭, 季陈林, 刘友波, 等. 多条公交线路的光储充电站日内滚动优化策略[J]. 智慧电力, 2020, 48(8): 44–50,90
YANG Qiming, JI Chenlin, LIU Youbo, et al. Day-rolling optimization strategy for photovoltaic-energy storage charging station with multiple electric bus lines[J]. Smart Power, 2020, 48(8): 44–50,90
[25] 丁明, 施建雄, 韩平平, 等. 光储系统参与电网调频及调峰的综合控制策略[J]. 中国电力, 2021, 54(1): 116–123,174
DING Ming, SHI Jianxiong, HAN Pingping, et al. An integrated control strategy for photovoltaic-energy storage system participating in frequency regulation and peak shaving of power grid[J]. Electric Power, 2021, 54(1): 116–123,174