Cost Optimization of Battery and Supercapacitor Hybrid Energy Storage System for Dispatching Solar PV Power

Pranoy Roy, Jiangbiao He, Y. Liao
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Abstract

This paper aims to optimize the cost of a battery and supercapacitor hybrid energy storage system (HESS) for dispatching solar power at one-hour increments for an entire day for megawatt-scale grid-connected photovoltaic (PV) arrays. A low-pass filter (LPF) is utilized to allocate the power between a battery and a supercapacitor (SC). The cost optimization of the HESS is calculated based on the time constant of the LPF through extensive simulations in a MATLAB/SIMULINK environment. Curve fitting and Particle Swarm Optimization (PSO) techniques are implemented to seek the optimum value of the LPF time constant. A fuzzy logic controller as a function of battery state of charge is developed to estimate the grid reference power for each one-hour dispatching period. Since the ambient temperature and PV cell temperature are different, this study also considers the relationship between them and presents their effects on energy storage cost calculations.
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调度太阳能光伏发电的电池与超级电容器混合储能系统成本优化
本文旨在优化电池和超级电容器混合储能系统(HESS)的成本,该系统用于兆瓦级并网光伏(PV)阵列全天以1小时增量调度太阳能。利用低通滤波器(LPF)在电池和超级电容器(SC)之间分配功率。通过在MATLAB/SIMULINK环境下的大量仿真,计算了基于LPF时间常数的HESS成本优化。采用曲线拟合和粒子群优化(PSO)技术寻求LPF时间常数的最优值。提出了一种基于电池充电状态的模糊控制器,用于估计每一小时调度时段的电网参考功率。由于环境温度和光伏电池温度不同,本研究也考虑了它们之间的关系,并给出了它们对储能成本计算的影响。
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