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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摘要

针对分布于区域电网不同网络节点的多座储能电站参与电网调频功率调度问题,提出了一种基于集合经验模态分解(Ensemble Empirical Mode Decomposition, EEMD)和多目标遗传算法(Multi-Objective Genetic Algorithm, MOGA)的火-多储系统调频功率双层优化策略。该策略包含火-储调频功率优化层和多储能电站调频功率优化层：上层计及火-储调配资源各自优势及剩余调频能力,构建火-储调频功率优化分配模型,完成火-储调频功率的分配;下层引入关于调频成本和荷电状态(State of Charge, SOC)的自适应权重系数,以调频成本最低和SOC均衡为优化目标,完成调频功率在多储能电站之间的分配。仿真结果表明,所提策略可以提升区域电网调频效果并降低调频成本,均衡控制多个储能电站的调频成本和SOC,可以防止经济性较好的储能电站长期处于SOC越限边缘状态,提升储能电站参与调频的积极性和可持续性。

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关键词 ：多火电储能系统, 二次调频, 双层优化控制, MOGA算法, 自适应权重系数

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 MOGA algorithm adaptive weight coefficient

收稿日期: 2023-09-06

PACS:

TM73

基金资助:

国家电网有限公司科技项目资助（5108-202299257A-1-0-ZB）

通讯作者: 通讯作者李军徽男,1976年生,教授,博士生导师,研究方向为新能源发电联网运行关键技术和储能技术的应用。E-mail：lijunhui@neepu.edu.cn

作者简介: 李翠萍女,1982年生,副教授,硕士生导师,研究方向为储能技术在电力系统中的应用。E-mail：licuipingabc@163.com

引用本文:

李翠萍, 司文博, 李军徽, 严干贵, 贾晨. 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[J]. 电工技术学报, 0, (): 230186-. Li Cuiping, Si Wenbo, Li Junhui, Yan Gangui, Jia Chen. 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. Transactions of China Electrotechnical Society, 0, (): 230186-.

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