基于IPMOCSA的光伏微网混合储能容量优化配置*

doi:10.11985/2021.03.021

摘要/Abstract

摘要：

针对光伏微网中混合储能的容量优化配置问题,以经济性为目标考虑微电网和大电网的交互功率成本建立系统经济优化模型,并提出一种改进的多目标乌鸦算法进行求解,获得优化配置结果。考虑分时电价设计微电网的系统运行策略,建立系统的运行成本模型,在此基础上建立不同类型储能介质的投资模型。利用以经济最优为目标,获得不同类型储能介质的容量优化配置占比,并对比多目标粒子群算法进行算例验证。结果表明提出的IPMOCSA求解精确度更高、收敛速度更快,混合储能配置成本节省了5.13%,配置方法对实际应用有一定参考性。

关键词: 微电网, 混合储能, 容量配置, 乌鸦算法

Abstract:

Aiming at the capacity optimization allocation problem of hybrid energy storage in photovoltaic micro-grid, the system economic optimization model was established by taking the interactive power cost of micro-grid and large grid as the objective, and an improved multi-objective crow search algorithm is proposed to solve the problem and obtain the optimal allocation results. Considering the time-of-use electricity price to design the system operation strategy of the micro-grid, establish the operating cost model of the system, and build the investment model of different types of energy-storing media. Using improved multi-objective crow search algorithm as the goal of economic optimization, the optimal allocation ratio of different types of energy storage media is obtained, and the multi-objective particle swarm optimization is used to verify the examples. The results show that the proposed improved multi-objective crow search algorithm solution has higher accuracy and convergence speed. The cost of hybrid energy storage configuration is saved by 5.13%, and the configuration method has certain reference for practical applications.

Key words: Micro-grid, hybrid energy storage, capacity configuration, crow search algorithm

中图分类号:

TM761

王红艳, 王依妍, 陈景文, 肖妍, 莫瑞瑞. 基于IPMOCSA的光伏微网混合储能容量优化配置^*[J]. 电气工程学报, 2021, 16(3): 152-160.

WANG Hongyan, WANG Yiyan, CHEN Jingwen, XIAO Yan, MO Ruirui. Optimal Configuration of Optical Storage Micro-grid Hybrid Energy Storage Capacity Based on IPMOCSA[J]. Journal of Electrical Engineering, 2021, 16(3): 152-160.

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Price(t)	ΔP(t)	SOC_G(t)<SOC_G_max SOC_N(t)<SOC_N_max	SOC_G(t)>SOC_G_max SOC_N(t)>SOC_N_max	SOC_G(t)>SOC_G_min SOC_N(t)>SOC_N_min	SOC_G(t)<SOC_G_min SOC_N(t)<SOC_N_min
Price_min	ΔP<0	M1：电网给负荷供电,同时给储能充电,若光伏存在,将光伏能量存储	M2：将光伏供给负荷	—	—
Price_ave Price_max	ΔP>0	M3：光伏优先给负荷供电,余电给储能充电	M4：余电上网	—	—
Price_ave Price_max	ΔP<0	—	—	M5：光伏+储能给负荷供电	M6：电网给负荷供电

性能指标	锂电池	超级电容
c_c/[元/(kW·h)]	3 500	6 000
c_g/(元/kW)	1 050	1 050
SOC_min	0.25	0.2
SOC_max	0.9	0.9
η_c(%)	0.9	0.9
η_f(%)	0.9	0.9
放电深度(%)	80	85
c_h/(元/kW)	1 085	550
c_q/[元/(kW·h)]	0	310
维护成本/[元/(kW·a)]	170	120
理论寿命/a	10	10

配置项		粒子群算法		改进乌鸦算法
配置项		锂电池	超级电容	锂电池			超级电容
光伏总容量/kW		181		181
占比		0.706	0.294	0.739		0.261
储能容量/(kW·h)		444.78	133.77	223.25		118.76
最大负荷日成本/元		1 839.792		1 752.934
日均投资总成本/元	1 694.264			1 607.406
年投资总成本/元		618 406.360			586 703.190