Open AccessMULTI-OBJECTIVE OPTIMIZATION FOR OPTIMAL HYBRID RENEWABLE ENERGY SOURCE SELECTION IN HYBRID RENEWABLE ENERGY SYSTEMS
Author(s) -
S. Jeyanthi Shilaja C
Publication year - 2021
Publication title -
psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.112
H-Index - 10
ISSN - 0033-3077
DOI - 10.17762/pae.v58i1.1496
Subject(s) - renewable energy , hybrid system , hybrid power , computer science , mathematical optimization , electric power system , population , wind power , reliability (semiconductor) , engineering , environmental economics , power (physics) , electrical engineering , economics , mathematics , physics , demography , quantum mechanics , machine learning , sociology
Power generation is more important to fulfill power demand throughout the world. Population and their electric power demand are increasing day by day. Achieve the energy demand from end-users, and recent research works have concentrated on designing a hybrid energy system. This paper proposed a multi-objective optimized model of a hybrid renewable energy system for a grid. The optimal model can choose a suitable design model of solar, wind, diesel, and batteries interconnected in the hybrid energy system. Optimization is applied for minimizing the system cost, fuel cost and diminish the fuel emission. It also aimed to improve the reliability of renewable sources. Initially, the problem is defined as a multi-objective problem and solved by a multi-objective evolutionary algorithm. From the simulation results, it is identified that the proposed multi-objective evolutionary algorithm performs better.