eprintid: 17806 rev_number: 8 eprint_status: archive userid: 2 dir: disk0/00/01/78/06 datestamp: 2025-06-02 23:30:13 lastmod: 2025-06-02 23:30:15 status_changed: 2025-06-02 23:30:13 type: article metadata_visibility: show creators_name: Kumar, Pramod creators_name: Swarnkar, Nagendra Kumar creators_name: Mahela, Om Prakash creators_name: Khan, Baseem creators_name: Anand, Divya creators_name: Singh, Aman creators_name: Vidal Mazón, Juan Luis creators_name: Alharithi, Fahd S. creators_name: Saikia, Lalit Chandra creators_id: creators_id: creators_id: creators_id: creators_id: divya.anand@uneatlantico.es creators_id: creators_id: juanluis.vidal@uneatlantico.es creators_id: creators_id: title: 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 ispublished: pub subjects: uneat_eng divisions: uneatlantico_produccion_cientifica divisions: uninimx_produccion_cientifica divisions: uninipr_produccion_cientifica full_text_status: public 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. date: 2023-03 publication: International Transactions on Electrical Energy Systems volume: 2023 pagerange: 1-19 id_number: doi:10.1155/2023/6315918 refereed: TRUE issn: 2050-7038 official_url: http://doi.org/10.1155/2023/6315918 access: open language: en citation: Artículo Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Artículos y libros Universidad Internacional Iberoamericana México > Investigación > Producción Científica Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica Abierto Inglés 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. metadata Kumar, Pramod; Swarnkar, Nagendra Kumar; Mahela, Om Prakash; Khan, Baseem; Anand, Divya; Singh, Aman; Vidal Mazón, Juan Luis; Alharithi, Fahd S. y Saikia, Lalit Chandra mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, divya.anand@uneatlantico.es, SIN ESPECIFICAR, juanluis.vidal@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR (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 document_url: http://repositorio.uneatlantico.es/id/eprint/17806/1/International%20Transactions%20on%20Electrical%20Energy%20Systems%20-%202023%20-%20Kumar%20-%20Optimal%20Sizing%20and%20Deployment%20of%20Renewable%20Energy.pdf