STUDY ON OPTIMIZATION AND CONTROL STRATEGIES FOR WIND-GAS-STORAGE VIRTUAL POWER PLANT BASED ON TIME-OF-USE TARIFFS

Luan Fuming; Zhang Heng; Chen Haiping

doi:10.19912/j.0254-0096.tynxb.2025-0392

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Acta Energiae Solaris Sinica ›› 2026, Vol. 47 ›› Issue (8) : 308-317. DOI: 10.19912/j.0254-0096.tynxb.2025-0392

STUDY ON OPTIMIZATION AND CONTROL STRATEGIES FOR WIND-GAS-STORAGE VIRTUAL POWER PLANT BASED ON TIME-OF-USE TARIFFS

Luan Fuming^1,2, Zhang Heng¹, Chen Haiping¹

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Abstract

To address the challenges posed by wind power’s intermittency and random fluctuations to grid security, this paper investigates a wind-gas-storage virtual power plant （VPP）. By coupling an electric boiler, thermal storage tank, and lithium bromide heat pump, it constructs a “dual-decoupling architecture for electricity-heat interaction” and proposes a time-of-use electricity pricing-based, two-layer coordinated optimization control model for the VPP’s day-ahead and intraday operations. The upper layer aims to maximize pre-day net revenue by formulating dispatch plans based on wind power and thermal load forecasts. The lower layer targets real-time operational cost minimization by dynamically adjusting unit outputs according to real-time data. Research indicates that under this model, the VPP’s actual output precisely tracks pre-day declared plans, with intraday output deviation ranges （-37.8 MW to 64.0 MW） significantly narrower than wind forecast errors, effectively reducing penalty costs. Integrating energy storage systems enables energy transfer by storing electricity and heat during off-peak periods and releasing energy during peak periods, optimizing gas turbine operation strategies and enhancing economic benefits. Increasing battery storage capacity has a limited impact on net profit growth, while net profit growth slows after thermal storage capacity reaches 500 MW·h. This research provides important insights for promoting renewable energy integration and building low-carbon power systems.

Key words

virtual power plant / time-of-use tariff / electricity-heat decoupling / economic dispatch / collaborative optimization

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Luan Fuming, Zhang Heng, Chen Haiping. STUDY ON OPTIMIZATION AND CONTROL STRATEGIES FOR WIND-GAS-STORAGE VIRTUAL POWER PLANT BASED ON TIME-OF-USE TARIFFS[J]. Acta Energiae Solaris Sinica. 2026, 47(8): 308-317 https://doi.org/10.19912/j.0254-0096.tynxb.2025-0392

References

[1] 陈会来, 张海波, 王兆霖. 不同类型虚拟电厂市场及调度特性参数聚合算法研究综述[J]. 中国电机工程学报, 2023, 43(1): 15-27.
Chen H L, Zhang H B, Wang Z L.A review of market and scheduling characteristic parameter aggregation algorithm of different types of virtual power plants[J]. Proceedings of the CSEE, 2023, 43(1): 15-27.
[2] 田立亭, 程林, 郭剑波, 等. 虚拟电厂对分布式能源的管理和互动机制研究综述[J]. 电网技术, 2020, 44(6): 2097-2108.
Tian L T, Cheng L, Guo J B, et al.A review on the study of management and interaction mechanism for distributed energy in virtual power plants[J]. Power System Technology, 2020, 44(6): 2097-2108.
[3] 严兴煜, 高赐威, 陈涛, 等. 数字孪生虚拟电厂系统框架设计及其实践展望[J]. 中国电机工程学报, 2023, 43(2): 604-618.
Yan X Y, Gao C W, Chen T, et al.Framework design and application prospect for digital twin virtual power plant system[J]. Proceedings of the CSEE, 2023, 43(2): 604-618.
[4] 张智刚, 康重庆. 碳中和目标下构建新型电力系统的挑战与展望[J]. 中国电机工程学报, 2022, 42(8): 2806-2818.
Zhang Z G, Kang C Q.Challenges and prospects for constructing the new-type power system towards a carbon neutrality future[J]. Proceedings of the CSEE, 2022, 42(8): 2806-2818.
[5] 白雪岩, 樊艳芳, 刘雨佳, 等. 考虑可靠性及灵活性的风光储虚拟电厂分层容量配置[J]. 电力系统保护与控制, 2022, 50(8): 11-24.
Bai X Y, Fan Y F, Liu Y J, et al.Wind power storage virtual power plant considering reliability and flexibility tiered capacity configuration[J]. Power System Protection and Control, 2022, 50(8): 11-24.
[6] 栗然, 丁星, 孙帆, 等. 风险导向下基于成本效益分析的多投资商虚拟电厂容量配置模型[J]. 电力自动化设备, 2021, 41(1): 145-151.
Li R, Ding X, Sun F, et al.Risk-oriented capacity configuration model for multi-investor virtual power plant based on cost-benefit analysis[J]. Electric Power Automation Equipment, 2021, 41(1): 145-151.
[7] 袁桂丽, 陈少梁, 刘颖, 等. 基于分时电价的虚拟电厂经济性优化调度[J]. 电网技术, 2016, 40(3): 826-832.
Yuan G L, Chen S L, Liu Y, et al.Economic optimal dispatch of virtual power plant based on time-of-use power price[J]. Power System Technology, 2016, 40(3): 826-832.
[8] 袁桂丽, 贾新潮, 房方, 等. 虚拟电厂源荷双侧热电联合随机优化调度[J]. 电网技术, 2020, 44(8): 2932-2940.
Yuan G L, Jia X C, Fang F, et al.Joint stochastic optimal scheduling of heat and power considering source and load sides of virtual power plant[J]. Power System Technology, 2020, 44(8): 2932-2940.
[9] 王之琦, 蒋传文. 基于峰谷分时电价的虚拟电厂日前申报及运行优化[J]. 水电能源科学, 2020, 38(10): 185-189.
Wang Z Q, Jiang C W.Day-ahead declaration and operation optimization of virtual power plant based on peak-valley time-of-use price[J]. Water Resources and Power, 2020, 38(10): 185-189.
[10] Ghanuni A, Sharifi R, Feshki Farahani H.A risk-based multi-objective energy scheduling and bidding strategy for a technical virtual power plant[J]. Electric Power Systems Research, 2023, 220: 109344.
[11] Pourghaderi N, Fotuhi-Firuzabad M, Moeini-Aghtaie M, et al.Optimal energy and flexibility self-scheduling of a technical virtual power plant under uncertainty: a two-stage adaptive robust approach[J]. IET Generation, Transmission & Distribution, 2023, 17(17): 3828-3847.
[12] Pandey A K, Jadoun V K, Sabhahit J N.Real-time peak valley pricing based multi-objective optimal scheduling of a virtual power plant considering renewable resources[J]. Energies, 2022, 15(16): 5970.
[13] Ning L Y, Liang K, Zhang B, et al.A two-layer optimal scheduling method for multi-energy virtual power plant with source-load synergy[J]. Energy Reports, 2023, 10: 4751-4760.
[14] 刘军会, 龚健, 佟炳绅, 等. 基于分布式储能与光伏的虚拟电厂与配电网协同优化方法[J]. 中国电力, 2025, 58(6): 1-9.
Liu J H, Gong J, Tong B S, et al.Coordinated optimization method for virtual power plants and distribution networks considering distributed energy storage and photovoltaics[J]. Electric Power, 2025, 58(6): 1-9.
[15] 葛晓琳, 李佾玲, 曹旭丹, 等. 基于聚合导纳推导运算的虚拟电厂优化调度模型[J]. 太阳能学报, 2025, 46(1): 522-530.
Ge X L, Li Y L, Cao X D, et al.Optimal scheduling model of virtual power plants based on aggregated admittance derivative operation[J]. Acta Energiae Solaris Sinica, 2025, 46(1): 522-530.
[16] 李兆泽, 张继红, 游国栋, 等. 基于源荷两侧不确定的虚拟电厂灵活性调整建模及调度策略[J]. 电网技术, 2025, 49(7): 2799-2808, I0038-I0045.
Li Z Z, Zhang J H, You G D, et al. Modeling and scheduling strategies for flexibility adjustment in virtual power plants considering source and load uncertainties[J]. Power System Technology, 2025, 49(7): 2799-2808, I0038-I0045.
[17] 吕游, 毛乃新, 秦瑞钧, 等. 考虑风光及负荷不确定性的虚拟电厂低碳经济调度[J]. 太阳能学报, 2024, 45(11): 116-123.
Lyu Y, Mao N X, Qin R J, et al.Low-carbon economic dispatch of virtual power plants considering wind power, photovoltaic and load uncertainty[J]. Acta Energiae Solaris Sinica, 2024, 45(11): 116-123.
[18] 张旭, 李先允, 陈伊健, 等. 考虑并网波动性的虚拟电厂多目标优化调度模型[J]. 电气自动化, 2024, 46(6): 64-68.
Zhang X, Li X Y, Chen Y J, et al.Multi-objective optimization scheduling model of virtual power plants considering grid-connected volatility[J]. Electrical Automation, 2024, 46(6): 64-68.