基于集合经验模态分解和多目标遗传算法的火-多储系统调频功率双层优化

doi:10.19595/j.cnki.1000-6753.tces.230186

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Abstract Aiming at the power scheduling problem of frequency modulation involving multiple energy storage stations distributed in different network nodes of regional power grid, a two-layer optimization strategy for frequency modulated power of thermal generation and multi-storage system based on ensemble empirical mode decomposition (EEMD) and multi-objective genetic algorithm (MOGA) is proposed. This strategy includes a thermal power-energy storage frequency modulation power optimization layer and a multi energy storage power station frequency modulation power optimization layer: The upper layer counts the respective advantages of thermal power-energy storage allocation resources as well as the residual frequency modulation capacity of thermal power units and energy storage, constructs the optimization distribution model of thermal power-energy storage frequency modulation power, and completes the distribution of thermal power-energy storage frequency modulation power. The lower layer introduces the adaptive weight coefficient about frequency modulation cost and state of charge (SOC) comprehensive state, takes frequency modulation cost and SOC comprehensive state as the optimization objective, and completes the distribution of frequency modulation power among multiple energy storage systems.
In order to verify the effectiveness of the above control strategies, this paper takes an actual AGC command from a certain location in China for simulation analysis. The specific conclusions are as follows:
Firstly, the thermal power-energy storage frequency modulation power allocation model constructed in this article can decompose the original AGC instructions into the AGC instructions that the thermal power unit as a whole and the energy storage power station as a whole need to bear. The decomposed signal has a good tracking effect on the original signal. The frequency modulation signal borne by the thermal power unit under this strategy follows the original frequency modulation signal, which is 64.29% higher than the traditional filtering strategy.
Secondly, the dual level optimization model for frequency regulation power proposed in this article can improve the overall frequency regulation economy of the regional power grid. Compared with the capacity proportion allocation strategy, the frequency regulation cost of thermal power units is reduced by 3.00%, and the unit wear is also slightly reduced; Compared to the proportional allocation strategy, the overall unit energy consumption cost of energy storage plants has been reduced by 3.6%.
Finally, the frequency modulation power allocation model proposed in this article can coordinate the frequency modulation cost and SOC recovery of each energy storage station. On the basis of reducing the overall frequency regulation cost, the SOC maintenance effect of each energy storage station is 34.78% better than the proportional allocation strategy; The overall SOC balance effect of multiple energy storage power stations is 52.69% better than the proportional allocation strategy.

Key words： Multi thermal power-energy storage system secondary frequency modulation two-layer optimal control multi-objective genetic algorithm(MOGA) adaptive weight coefficient

Received: 21 February 2023

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TM73

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	Li Cuiping
	Si Wenbo
	Li Junhui
	Yan Gangui
	Jia Chen

Cite this article:

Li Cuiping,Si Wenbo,Li Junhui等. Two-Layer Optimization of Frequency Modulated Power of Thermal Generation and Multi-Storage System Based on Ensemble Empirical Mode Decomposition and Multi-Objective Genetic Algorithm[J]. Transactions of China Electrotechnical Society, 2024, 39(7): 2017-2032.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.230186 OR https://dgjsxb.ces-transaction.com/EN/Y2024/V39/I7/2017

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