基于模糊自适应粒子群算法的光伏水泵系统尺寸优化

Nemouchi Wissem, Amrane Youssef, Haroun Smail, Boucetta Lakhdar Nadjib
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引用次数: 0

摘要

水是人类一切活动的发动机。今年阿尔及利亚经历了供水短缺,这使得地下水成为半主要的储备来源。基于光伏的抽水系统(PVPS)提出了一个有吸引力的解决方案,特别是在灌溉需求。为此,本文的主要目的是研究一种基于技术经济指标的抽水系统光伏能源优化方法。为了保证系统元素的最佳尺寸,该算法采用模糊自适应粒子群优化(PSO)进行优化配置。推荐的模型考虑了初始资本成本、操作成本和替换成本。模拟分析主要受荷载、气象资料要素参数的影响。本研究设计了一个自主式PVPS,以满足阿尔及尔小农田灌溉20年以上的用水需求。结果包括每个组件的最优数量,包括泵和电池,这些组件由光伏板作为可再生能源提供光伏泵系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal sizing of photovoltaic water pumping system using Fuzzy-Adaptive PSO
Water is engine of all human activity. This year Algeria has experienced a shortage of water supply which has made groundwater a semi-main source for reserve. Photovoltaic-based water pumping system (PVPS) presents an attractive solution to water access, especially in irrigation needs. In this regard, the main objective of this article is study investigates an optimization approach of photovoltaic energy for pumping systems based on technical and economical indicators. In order to ensure the best size of system elements, The algorithm optimization is configurated using fuzzy–adaptive particle swarm optimization (PSO). The recommended model takes into account initial capital cost, operation, and replacements costs. The simulation analysis is mainly affected by load, meteorological data elements parameters. For this study, an autonomous PVPS is designed to satisfy meet water demand for irrigation of small agricultural field over 20 years life span in Algiers. The results include optimal numbers of each component including pumps and batteries for storage supplied by photovoltaic panels taken as renewable energy sources which provide photovoltaic pumping systems.
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