Optimal Sizing of Hybrid Renewable Energy System using Manta Ray Foraging Technique

Priyanka Brahamne, Assoc. Prof. M. P. S. Chawla, Dr. H. K. Verma
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Abstract

In this paper, a method for optimizing the size of a standalone hybrid that consists of a wind, PV, and biomass energy system with battery storage is discussed. Hybrid renewable energy systems are required in off-the-grid communities. For such systems, the optimal system sizing can be regarded as one of the constrained optimization issues. This research presents an intelligent approach based on modern optimization for designing the hybrid renewable energy system optimally using the manta ray foraging technique, minimizing overall annualized system cost and satisfying load demand. In order to confirm the effectiveness of the proposed method, results are compared against findings from the ABC algorithm. The results have proven that the MRFO algorithm has fast convergence properties, the ability to deliver high-quality results, and the capacity to manage a smooth power flow under the same ideal conditions.
基于蝠鲼觅食技术的混合可再生能源系统优化规模
本文讨论了一种优化由风能、光伏和生物质能系统和电池存储组成的独立混合动力系统的尺寸的方法。离网社区需要混合可再生能源系统。对于这类系统,最优系统规模可视为约束优化问题之一。提出了一种基于现代优化的智能方法,利用蝠鲼觅食技术优化设计混合可再生能源系统,使系统年化总成本最小并满足负荷需求。为了验证该方法的有效性,将结果与ABC算法的结果进行了比较。结果证明,MRFO算法具有快速收敛特性,能够提供高质量的结果,并且能够在相同的理想条件下管理平稳的潮流。
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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