李军徽, 贾才齐, 朱星旭, 严干贵, 贾晨, 李扬. 降低火电调频损耗的混合储能系统容量优化配置双层模型[J]. 高电压技术, 2023, 49(9): 3965-3976. DOI: 10.13336/j.1003-6520.hve.20230219
引用本文: 李军徽, 贾才齐, 朱星旭, 严干贵, 贾晨, 李扬. 降低火电调频损耗的混合储能系统容量优化配置双层模型[J]. 高电压技术, 2023, 49(9): 3965-3976. DOI: 10.13336/j.1003-6520.hve.20230219
LI Junhui, JIA Caiqi, ZHU Xingxu, YAN Gangui, JIA Chen, LI Yang. Dual-layer Model for Capacity Optimization of Hybrid Energy Storage System to Reduce Thermal Power Frequency Modulation loss[J]. High Voltage Engineering, 2023, 49(9): 3965-3976. DOI: 10.13336/j.1003-6520.hve.20230219
Citation: LI Junhui, JIA Caiqi, ZHU Xingxu, YAN Gangui, JIA Chen, LI Yang. Dual-layer Model for Capacity Optimization of Hybrid Energy Storage System to Reduce Thermal Power Frequency Modulation loss[J]. High Voltage Engineering, 2023, 49(9): 3965-3976. DOI: 10.13336/j.1003-6520.hve.20230219

降低火电调频损耗的混合储能系统容量优化配置双层模型

Dual-layer Model for Capacity Optimization of Hybrid Energy Storage System to Reduce Thermal Power Frequency Modulation loss

  • 摘要: 针对如何在降低火电机组调频损耗,提高系统调频性能的同时减小储能全寿命周期成本,提出了一种混合储能辅助火电机组参与自动发电控制(automatic generation control, AGC)的双层优化配置模型。上层模型由基于经验模态分解(empirical mode decomposition, EMD)的火电–混合储能间AGC指令分配策略和计及全寿命周期内成本收益之差、AGC综合评判指标Kp的多目标优化配置模型组成,为底层模型提供AGC初步分解指令和功率、容量约束;底层模型由计及储能荷电状态(state of charge, SOC)恢复的混合储能控制策略和火电–混合储能调频响应模型组成,将经过EMD初步分解的AGC指令再次分配给各调频资源,并向上层模型提供各调频资源出力响应曲线和SOC变化曲线;采用基于优劣解距离法(technique for order preference by similarity to an ideal solution, TOPSIS)的多目标粒子群算法求解该双层模型,避免了传统多目标粒子群算法在Pareto解集中确定全局最优解的偶然性。基于华北某电厂运行数据开展仿真分析,结果表明混合储能双层优化配置模型可以有效降低火电机组调频损耗,显著提高火储联合调频系统经济性,为混合储能辅助传统调频电源提供配置方案参考。

     

    Abstract: Aiming at how to reduce the frequency modulation loss of thermal power units, to improve the frequency modulation performance of the system, and to reduce the life cycle cost of energy storage, we propose a dual-level optimal configuration model of hybrid energy storage assisted thermal power units participating in automatic generation control (AGC). The upper layer model is composed of empirical mode decomposition (EMD) and multi-objective optimization configuration model, in which EMD is based on AGC allocation strategy between thermal power and hybrid energy storage, and the cost-benefit difference in the life cycle and AGC comprehensive evaluation index Kp is taken into account in the multi-objective optimization configuration model. The upper layer model provides AGC preliminary decomposition instructions and power and capacity constraints for the underlying model. The underlying model consists of a hybrid energy storage control strategy considering state of charge (SOC) recovery and a thermal power-hybrid energy storage frequency modulation response model. The AGC firstly decomposed by EMD is reassigned to each frequency modulation resource, and the output curve and SOC curve are provided to the upper model. Then, a multi-objective particle swarm optimization algorithm based on technique for order preference by similarity to an ideal solution (TOPSIS) was used to solve the two-layer model, which avoids the contingency of the traditional multi-objective particle swarm optimization algorithm to determine the global optimum in the Pareto solution set. Lastly, the simulation analysis of operation data of a power plant in North China is performed. The results show that the hybrid energy storage dual-layer optimization model can effectively reduce the frequency modulation loss of thermal power units and significantly improve the economy of the combined thermal-storage frequency modulation system. The conclusion can provide a reference for the configuration scheme of hybrid energy storage auxiliary traditional frequency modulation power supply in the future.

     

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