Optimal Sizing and Deployment of Renewable Energy Generators in Practical Transmission Network Using Grid-Oriented Multiobjective Harmony Search Algorithm for Loss Reduction and Voltage Profile Improvements

Kumar, Pramod and Swarnkar, Nagendra Kumar and Mahela, Om Prakash and Khan, Baseem and Anand, Divya and Singh, Aman and Vidal Mazón, Juan Luis and Alharithi, Fahd S. and Saikia, Lalit Chandra UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, divya.anand@uneatlantico.es, UNSPECIFIED, juanluis.vidal@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2023) Optimal Sizing and Deployment of Renewable Energy Generators in Practical Transmission Network Using Grid-Oriented Multiobjective Harmony Search Algorithm for Loss Reduction and Voltage Profile Improvements. International Transactions on Electrical Energy Systems, 2023. pp. 1-19. ISSN 2050-7038

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Abstract

This paper presents grid-oriented multiobjective harmony search algorithm (GOMOHSA) to incorporate the multiple grid parameters for minimization of the active power loss, reactive power loss, and total voltage deviations (TVD) in a part of practical transmission network of Rajasthan Rajya Vidyut Prasaran Nigam Limited (RVPN) in southern parts of Rajasthan state of India. This is achieved by optimal deployment of optimally sized renewable energy (RE) generators using GOMOHSA. Performance indexes such as active power loss minimization index (APMLI), the reactive power loss minimization index (RPMLI), and the total voltage deviation improvement index (TVDII) are introduced to evaluate the health of the test network with different load scenarios. Performance of proposed GOMOHSA has been tested for five different operating scenarios of loads and RE generation. It is established that the proposed GOMOHSA finds the optimal deployment of optimally sized RE generators, and the investment cost of deployment of these RE generators can be recovered within a time period that is less than 5 years. Performance of GOMOHSA is superior compared to a conventional genetic algorithm (GA) in terms of performance indexes, RE generator capacity, payback period, and parameter sensitivity. Study is performed using MATLAB software for loading scenario of base year 2021 and projected year 2031.

Item Type: Article
Subjects: Subjects > Engineering
Divisions: Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Depositing User: Sr Bibliotecario
Date Deposited: 02 Jun 2025 13:09
Last Modified: 02 Jun 2025 13:09
URI: http://repositorio.funiber.org/id/eprint/17806

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