SCHEDULING STRATEGY FOR MULTIPLE VIRTUAL POWER PLANTS CONSIDERING QUANTITATIVE EVALUATION OF SERVICE QUALITY OF SHARED ENERGY STORAGE

Fan Hui, Niu Yuguang, Chen Yue, Bian Shujie

Acta Energiae Solaris Sinica ›› 2025, Vol. 46 ›› Issue (10) : 77-87.

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Acta Energiae Solaris Sinica ›› 2025, Vol. 46 ›› Issue (10) : 77-87. DOI: 10.19912/j.0254-0096.tynxb.2024-1072

SCHEDULING STRATEGY FOR MULTIPLE VIRTUAL POWER PLANTS CONSIDERING QUANTITATIVE EVALUATION OF SERVICE QUALITY OF SHARED ENERGY STORAGE

  • Fan Hui, Niu Yuguang, Chen Yue, Bian Shujie
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Abstract

Aiming at energy coupling problem existing in the coordination and interaction among multiple virtual power plants (MVPP), a quantitative evaluation function of service quality for shared energy storage (SES) is established. Combined with the evaluation function, a bi-level optimization scheduling strategy of energy sharing among MVPP is proposed. In the upper level, taking into account both the target of economic benefits and service quality of SES, the capacity allocation is optimized. In the lower level, the units output within MVPP and transaction power among them are optimized to minimize the operation cost. To address the uncertainty of RE, based on chance constraint, an optimization model is constructed, where the KKT condition and the Big-M method are used to transform bi-level model into an equivalent single-level model. Simulation verifies the rationality of the proposed model and cases analysis are employed to demonstrate the impact of SES service quality and confidence level on energy sharing and energy storage configuration of MVPP. In addition, results show that with the consideration of service quality for SES, the enthusiasm of MVPP to participate in power sharing is enhanced effectively, realizing the rational utilization of resources.

Key words

virtual power plant / shared energy storage / capacity allocation / chance constraint / bi-level optimization / uncertainty

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Fan Hui, Niu Yuguang, Chen Yue, Bian Shujie. SCHEDULING STRATEGY FOR MULTIPLE VIRTUAL POWER PLANTS CONSIDERING QUANTITATIVE EVALUATION OF SERVICE QUALITY OF SHARED ENERGY STORAGE[J]. Acta Energiae Solaris Sinica. 2025, 46(10): 77-87 https://doi.org/10.19912/j.0254-0096.tynxb.2024-1072

References

[1] 国务院. 国务院关于印发《2024—2025年节能降碳行动方案》的通知[EB/OL]. [2024-06-17].https://www.gov.cn/zhengce/zhengceku/202405/content_6954323.htm.
[2] 国家发展改革委. 关于加强电网调峰储能和智能化调度能力建设的指导意见[EB/OL].[2024-06-13]. https://www.ndrc.gov.cn/xxgk/zcfb/tz/202402/t20240227_1364257. html.
[3] TAN C X, TAN Z F, WANG G R, et al.Business model of virtual power plant considering uncertainty and different levels of market maturity[J]. Journal of cleaner production, 2022, 362: 131433.
[4] SU Y F, WANG J H, BAI G P, et al.Multi-objective optimal dispatching of wind-photoelectric-thermal power-pumped storage virtual power plant[C]//2021 IEEE Sustainable Power and Energy Conference(iSPEC). Nanjing, China, 2021: 107-111.
[5] 王伟韬, 王旭, 蒋传文, 等. 考虑夏普比率的虚拟电厂日前投标策略[J]. 电网技术, 2023, 47(4): 1512-1523.
WANG W T, WANG X, JIANG C W, et al.Day ahead bidding strategy for virtual power plants considering sharpe ratio[J]. Power system technology, 2023, 47(4): 1512-1523.
[6] LI Q, WEI F C, ZHOU Y C, et al.A scheduling framework for VPP considering multiple uncertainties and flexible resources[J]. Energy, 2023, 282: 128385.
[7] 国务院, 中共中央. 关于进一步深化电力体制改革的若干意见(中发[2015]9号)[EB/OL]. [2024-06-13].https://news.bjx.com.cn/html/20150410/606700-1.shtml.
[8] 国家能源局, 国家发展改革委. 国家能源局关于开展分布式发电市场化交易试点的通知[EB/OL].[2024-06-13]. https://zfxxgk.nea.gov.cn/auto87/201711/t20171113_3055.htm.
[9] 王佳惠, 牛玉广, 陈玥, 等. 计及火电深度调峰的高比例可再生能源电力系统日前优化调度研究[J]. 太阳能学报, 2023, 44(1): 493-499.
WANG J H, NIU Y G, CHEN Y, et al.Research on day-ahead optimal dispatching of high-proportion renewable energy power system considering deep peak load regulation of thermal power[J]. Acta energiae solaris sinica, 2023, 44(1): 493-499.
[10] 沈思辰, 韩海腾, 周亦洲, 等. 基于条件风险价值的多虚拟电厂电-碳-备用P2P交易模型[J]. 电力系统自动化, 2022, 46(18): 147-157.
SHEN S C, HAN H T, ZHOU Y Z, et al.Electricity-carbon-reserve peer-to-peer trading model for multiple virtual power plants based on conditional value-at-risk[J]. Automation of electric power system, 2022, 46(18): 147-157.
[11] 姜恩宇, 陈周, 史雷敏, 等. 计及多重不确定性与综合贡献率的多微网合作运行策略[J]. 太阳能学报, 2023,44(10): 80-89.
JIANG E Y, CHEN Z, SHI L M, et al.Cooperative operation strategy of multi-microgrids based on multiple uncertainties and comprehensive contribution rate[J]. Acta energiae solaris sinica, 2023,44(10): 80-89.
[12] PAN J, LIU X O, HUANG J J.Multi-level games optimal scheduling strategy of multiple virtual power plants considering carbon emission flow and carbon trade[J]. Electric power systems research, 2023, 223: 109669.
[13] CAO J Y, YANG D C, DEHGHANIAN P.Co-optimization of multiple virtual power plants considering electricity-heat-carbon trading: a Stackelberg game strategy[J]. International journal of electrical power & energy systems, 2023, 153: 109294.
[14] 葛晓琳, 曹旭丹, 李佾玲. 多虚拟电厂日前随机博弈与实时变时间尺度优化方法[J]. 电力自动化设备, 2023,43(11): 150-157.
GE X L, CAO X D, LI R L.Day-ahead stochastic game and real-time adaptive time scale optimization method for multiple virtual power plants[J]. Electric power automation equipment, 2023, 43(11): 150-157.
[15] 刘汶瑜, 陈中, 杜璞良, 等. 基于联盟博弈的多虚拟电厂参与日前电力市场竞标模型[J]. 电力自动化设备, 2024, 44(5): 135-142, 150.
LIU W Y, CHEN Z, DU P L, et al.Bidding model for multiple virtual power plants participating in day-ahead electricity market based on coalition game[J]. Electric power automation equipment, 2024, 44(5): 135-142, 150.
[16] ZHANG S X, LI Y W, DU E S, et al.A review and outlook on cloud energy storage: an aggregated and shared utilizing method of energy storage system[J]. Renewable and sustainable energy reviews, 2023, 185: 113606.
[17] LI Y W, XUE J J, BIAN J Y, et al.Cloud energy storage in multi energy systems: Optimal scheduling and profit-sharing approaches[C]//2021 IEEE Power & Energy Society General Meeting (PESGM). Washington, DC, USA, 2021: 1-5.
[18] 谢雨龙, 罗逸飏, 李智威, 等. 考虑微网新能源经济消纳的共享储能优化配置[J]. 高电压技术, 2022, 48(11): 4403-4413.
XIE Y L, LUO Y Y, LI Z W, et al.Optimal allocation of shared energy storage considering the economic consumption of microgrid new energy[J]. High voltage engineering, 2022, 48(11): 4403-4413.
[19] DONG H Y, FU Y B, JIA Q Q, et al.Optimal dispatch of integrated energy microgrid considering hybrid structured electric-thermal energy storage[J]. Renewable energy, 2022, 199: 628-639.
[20] 帅轩越, 王秀丽, 吴雄, 等. 计及电热需求响应的共享储能容量配置与动态租赁模型[J]. 电力系统自动化, 2021, 45(19): 24-32.
SHUAI X Y, WANG X L, WU X, et al.Shared energy storage capacity allocation and dynamic lease model considering electricity-heat demand response[J]. Automation of electric power systems, 2021, 45(19): 24-32.
[21] 胡银龙, 叶梓松, 解振霖, 等. 基于机会约束的售电公司共享储能经济运行优化[J]. 电力自动化设备, 2024, 44(5): 44-50.
HU Y L, YE Z S, XIE Z L, et al.Economic operation optimization of shared energy storage for electricity retailer based on chance constraint[J]. Electric power automation equipment, 2024, 44(5): 44-50.
[22] 吴盛军, 李群, 刘建坤, 等. 基于储能电站服务的冷热电多微网系统双层优化配置[J]. 电网技术, 2021, 45(10): 3822-3832.
WU S J, LI Q, LIU J K, et al.Bi-level optimal configuration for combined cooling heating and power multi-microgrids based on energy storage station service[J]. Power system technology, 2021, 45(10): 3822-3832.
[23] 刘宝碇, 赵瑞清. 随机规划与模糊规划[M]. 北京: 清华大学出版社, 1998.
LIU B D, ZHAO R Q.Stochastic programming and fuzzy programming[M]. Beijing: Tsinghua University Press, 1998.
[24] 张靠社, 冯培基, 张刚, 等. 考虑机会约束的多能源微电网双层优化配置[J]. 太阳能学报, 2021, 42(8): 41-48.
ZHANG K S, FENG P J, ZHANG G, et al.Bi-level optimization configuration method for multienergy microgrid considering chance constraints[J]. Acta energiae solaris sinica, 2021, 42(8): 41-48.
[25] HU J J, WANG Y D, DONG L.Low carbon-oriented planning of shared energy storage station for multiple integrated energy systems considering energy-carbon flow and carbon emission reduction[J]. Energy, 2024, 290: 130139.
[26] WANG J X, XU Z, SUN Y H, et al.Optimal configuration and pricing strategies for electric-heat cloud energy storage: a Stackelberg game approach[J]. Sustainable energy technologies and assessments, 2022, 53: 102596.
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