压缩储能与氢能驱动的虚拟电厂源-储-荷低碳经济调度

doi:10.19595/j.cnki.1000-6753.tces.250803

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Abstract

To address critical challenges in virtual power plant (VPP), including low hydrogen utilization efficiency, limited hydrogen blending applications in gas-fired units, and the narrow energy flow scope of existing energy storage systems, this paper proposes a low-carbon economic dispatch model for hydrogen-driven VPPs. The model integrates advanced adiabatic compressed air energy storage (AA-CAES) with a two-stage power-to-gas and carbon capture system (P2G-CCS), establishing a deeply coupled source-storage-load collaborative optimization framework. This framework enables unified coordination and dispatch of multiple energy carriers and devices within the VPP, aiming to significantly improve energy utilization efficiency, facilitate renewable energy integration, and substantially reduce system carbon emissions.
On the supply side, an innovative two-stage hydrogen utilization strategy is designed. In the first stage, hydrogen is produced via electrolysis using surplus renewable electricity. In the second stage, carbon dioxide captured from gas turbine emissions undergoes methanation to generate synthetic natural gas. The resulting synthetic gas mixture, rich in hydrogen, is co-fired in gas turbines and boilers. The model thoroughly considers the operational characteristics and efficiency variations of gas-fired equipment under different hydrogen blending ratios. It quantitatively analyzes the impact of hydrogen blending on overall system economics and carbon reduction benefits, verifying the rationality and technical feasibility of dynamic hydrogen blending strategies and providing scientific support for diversified hydrogen utilization in VPP.
Regarding energy storage, the cogeneration advantage of AA-CAES is fully exploited. The system recovers and stores thermal energy generated during the air compression process, which is then released during the discharge phase to meet heating demands within the VPP. This coordinated electric-thermal output enhances system dispatch flexibility, effectively mitigates the variability and uncertainty of renewable generation, reduces renewable energy curtailment risks, and improves overall energy efficiency and economic performance.
To achieve efficient coordinated operation among multiple energy carriers, a multi-energy coupled collaborative optimization dispatch model is developed. The objective is to minimize the comprehensive operating cost of the VPP, including fuel procurement expenses, carbon trading costs, carbon capture operational costs, and economic losses due to renewable energy curtailment. Considering the high nonlinearity, multiple variables, and complex constraints of the problem, a hybrid optimization algorithm combining the moth-flame optimization (MFO) algorithm with a differential evolution strategy—referred to as DE-MFO—is proposed. This algorithm enhances global search capability, accelerates convergence, and improves solution robustness, making it well-suited for large-scale complex energy system optimization.
Simulation case studies and comparative analyses validate the effectiveness and superiority of the proposed model and algorithm. Results demonstrate that the integration of AA-CAES and P2G-CCS not only significantly reduces total operating costs and carbon emissions of the VPP but also improves renewable energy accommodation and utilization efficiency. Additionally, the dynamic hydrogen blending strategy effectively supports flexible dispatch of gas turbines, achieving efficient and low-carbon hydrogen utilization. Overall, the proposed dispatch model and optimization method provide a solid theoretical foundation and practical technical pathway for multi-energy synergy and low-carbon operation in VPP, offering important guidance for the construction and operation of future clean energy systems.

Key words： Virtual power plant adiabatic compressed air energy storage power-to-gas hydrogen blending moth flame optimization algorithm

Received: 13 May 2025

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TM734

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	Shi Ruifeng
	Lin Yongqi
	Zhang Lingzhi
	Ma Kai
	Jia Limin

Cite this article:

Shi Ruifeng,Lin Yongqi,Zhang Lingzhi等. Compressed Storage and Hydrogen-Driven Virtual Power Plant: Low-Carbon Economic Dispatch of Generation-Storage-Load[J]. Transactions of China Electrotechnical Society, 0, (): 258110-258110.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.250803 OR https://dgjsxb.ces-transaction.com/EN/Y0/V/I/258110

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