Optimum sizing of hybrid PV/Wind/battery installation using a fuzzy PSO

Abdelhak Ben Jemaa, N. Essounbouli, A. Hamzaoui
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引用次数: 11

Abstract

This paper proposes a sizing methodology to optimize the configuration of the hybrid energy system. For this we used an approach of automatic fuzzy rule base generation by means of Fuzzy-Adaptive Particle Swarm Optimization (PSO), which changes dynamically the acceleration coefficient rates ensuring the convergence. This algorithm allows us to obtain the optimal number of photovoltaic panels, wind turbines and storage units ensuring the minimal global high efficiency system total cost and guaranteeing the permanent availabilty of energy to cover the load energy requirements. The database of wind speed taken hourly, the solar irradiance and the load data are used to stochastically model the wind turbines, photovoltaic generation and load. The total cost is the objective function and the technical size is considered as a contraint.
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利用模糊粒子群优化光伏/风能/电池混合装置的最佳尺寸
本文提出了一种优化混合能源系统配置的量化方法。为此,采用了一种基于模糊自适应粒子群算法(PSO)的自动模糊规则库生成方法,该方法动态地改变加速度系数速率以保证算法的收敛性。该算法使我们能够获得光伏板、风力涡轮机和储能单元的最优数量,以确保全球高效系统总成本最小,并保证能源的永久可用性,以满足负荷的能源需求。利用每小时风速数据库、太阳辐照度数据库和负荷数据库对风力发电机组、光伏发电机组和负荷进行了随机建模。以总成本为目标函数,以技术尺寸为约束。
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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