Multi-Objective Optimization of PV/Wind/ESS Hybrid Microgrid System Considering Reliability and Cost Indices

A. Parizad, Konstadinos. J. Hatziadoniu
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引用次数: 10

Abstract

Recently, power system planers are moving toward sustainable sources of energy like solar and wind. However, some technical issues such as intermittent behavior of Renewable Energy Source (RES) and its reliability should be taken into account. In this paper, a hybrid PV/Wind system combined with hydrogen ESS system is compared to one with battery storage. Multi-objective Particle Swarm Optimization (MOPSO) is employed to size system components in order to supply the load of an autonomous microgrid considering cost and reliability indices. In this problem, photovoltaic arrays and wind turbines are subject to failure. Moreover, to increase the accuracy of calculation, the annual load, wind, and solar profiles from NREL (Illinois, USA) are applied to the optimization problem. A comprehensive cost function is defined to cover the capital, replacement, operation and maintenance costs as well as the number of replacements and interest rate during the project period (20 years). To increase the reliability of a stand-alone system as well as customer's satisfaction three reliability indices i.e., Loss of Energy Expected (LOEE), Loss of Load Expected (LOLE), and Equivalent Loss Factor (ELF) are taken into account. Results reveal that the proposed method can find the best configuration for both fuel cell/ battery based ESS system with the highest reliability and the lowest cost.
考虑可靠性和成本指标的光伏/风能/ESS混合微电网多目标优化
最近,电力系统规划者正在转向太阳能和风能等可持续能源。但是,可再生能源的间歇性特性及其可靠性等技术问题需要考虑。本文将结合氢ESS系统的光伏/风能混合系统与电池储能系统进行了比较。考虑成本和可靠性指标,采用多目标粒子群优化(MOPSO)对系统部件进行尺寸优化,为自主微电网供电。在这个问题中,光伏阵列和风力涡轮机容易发生故障。此外,为了提高计算的准确性,还将美国伊利诺斯州NREL的年负荷、风能和太阳能剖面应用于优化问题。定义综合成本函数,包括项目期间(20年)的资本、更换、运行和维护成本以及更换次数和利率。为了提高独立系统的可靠性以及客户满意度,考虑了三个可靠性指标,即预期能量损失(LOEE),预期负荷损失(LOLE)和等效损耗因子(ELF)。结果表明,所提出的方法可以找到可靠性最高、成本最低的燃料电池ESS系统的最佳配置。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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