Multitype Energy Storage Participation Peak Load Regulation Model and Its Optimal Scheduling Strategy

XIE Daiyu,LI Hongzhou,CHEN Biao,LI Peikai,LI Guangming,DAI Wei

Distributed Energy ›› 2024, Vol. 9 ›› Issue (2) : 19-29.

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Distributed Energy ›› 2024, Vol. 9 ›› Issue (2) : 19-29. DOI: 10.16513/j.2096-2185.DE.2409203
Basic Research

Multitype Energy Storage Participation Peak Load Regulation Model and Its Optimal Scheduling Strategy

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Abstract

In order to achieve the strategic goals of "carbon peak" and "carbon neutral", China's power grid will gradually be built into a green smart grid with new energy as the main power source and multiple types of power sources coexisting. However, the limited peak regulation capacity of traditional conventional power sources is difficult to meet the peak regulation demand of the future power system after accessing high proportion of new energy, which restricts the absorption capacity of new energy and reduces the safety and economy of system operation. Therefore, it is necessary to build multiple types of energy storage models, such as pumped storage, electrochemical energy storage, and electric vehicle virtual energy storage. Combined with four typical scenarios and extreme scenarios of a provincial power system, an optimal peak regulation efficiency model from the perspective of dispatching agency is proposed based on the existing energy storage peak regulation auxiliary service compensation mechanism. Through simulation verification using historical data from a provincial power grid, it has been demonstrated that this model plays a positive role in reducing frequent start-stop cycles for thermal power units and improving economic efficiency in peak regulation. This promotes both economic viability and safe operation for future advanced electricity systems.

Key words

multitype energy storage / depth peak regulation / optimized scheduling / peak load compensation mechanism / new energy consumption

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Daiyu XIE , Hongzhou LI , Biao CHEN , et al . Multitype Energy Storage Participation Peak Load Regulation Model and Its Optimal Scheduling Strategy[J]. Distributed Energy Resources. 2024, 9(2): 19-29 https://doi.org/10.16513/j.2096-2185.DE.2409203

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Funding

Natural Science Foundation of Guangxi(2021GXNSFBA220032)
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