eprintid: 17804 rev_number: 8 eprint_status: archive userid: 2 dir: disk0/00/01/78/04 datestamp: 2025-06-02 23:30:09 lastmod: 2025-06-02 23:30:11 status_changed: 2025-06-02 23:30:09 type: article metadata_visibility: show creators_name: Kaushik, Ekata creators_name: Prakash, Vivek creators_name: Ghandour, Raymond creators_name: Al Barakeh, Zaher creators_name: Ali, Ahmed creators_name: Mahela, Om Prakash creators_name: Álvarez, Roberto Marcelo creators_name: Khan, Baseem creators_id: creators_id: creators_id: creators_id: creators_id: creators_id: creators_id: roberto.alvarez@uneatlantico.es creators_id: title: Hybrid Combination of Network Restructuring and Optimal Placement of Distributed Generators to Reduce Transmission Loss and Improve Flexibility ispublished: pub subjects: uneat_eng divisions: uneatlantico_produccion_cientifica divisions: uninimx_produccion_cientifica full_text_status: public keywords: distributed energy generator; grid-oriented genetic algorithm; network restructuring; power system flexibility; utility transmission network abstract: A high penetration of renewable energy (RE) in utility grids creates the problems of power system flexibility, high transmission losses, and voltage variations. These problems can be solved using a hybrid combination of transmission network restructuring and optimal placement of distributed energy generator (DEG) units. Hence, this work investigated a technologically and economically feasible solution for improving the flexibility of power networks and reducing losses in a practical transmission utility network by implementing a restructuring of the network and optimal deployment of the distributed energy generators (DEGs). Two solutions for this network restructuring were proposed. Furthermore, a grid-oriented genetic algorithm (GOGA) was designed by combining the conventional genetic algorithm (GA) and mathematical solutions to identify optimal DEG placement. A power system restructuring and GOGA flexibility index (PSRGFI) was formulated for the assessment of network flexibility. A cost–benefit assessment was also performed to estimate the payback period for the investment required for restructuring of the network and DEG placement. The least-square approximation technique was applied for load projection for the year 2031 considering the base year 2021. It was established that minimization of transmission losses, reduction in voltage deviations, and improvement of network flexibility were achieved through hybrid application of network restructuring and DEG placement using GOGA. A network loss saving of 61.19 MW was achieved via optimal restructuring and GOGA. For the projected year 2031, the PSRGFI increased from 30.94 to 132.78 after the placement of DEGs using GOGA and optimal restructuring, indicating that network flexibility increased significantly. The payback period for the investment was very small, equal to 0.985 years. The performance of the designed method was superior to the GA-based method, simulated annealing technique, and bee colony algorithm (BCA) used for placement of DEG units in the test network. The study was completed using MATLAB software, considering data from a practical transmission network owned by Rajasthan Rajya Vidyut Prasaran Nigam Ltd. (RVPN), India. date: 2023-03 publication: Sustainability volume: 15 number: 6 pagerange: 5285 id_number: doi:10.3390/su15065285 refereed: TRUE issn: 2071-1050 official_url: http://doi.org/10.3390/su15065285 access: open language: en citation: Artículo Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Artículos y libros Universidad Internacional Iberoamericana México > Investigación > Producción Científica Abierto Inglés A high penetration of renewable energy (RE) in utility grids creates the problems of power system flexibility, high transmission losses, and voltage variations. These problems can be solved using a hybrid combination of transmission network restructuring and optimal placement of distributed energy generator (DEG) units. Hence, this work investigated a technologically and economically feasible solution for improving the flexibility of power networks and reducing losses in a practical transmission utility network by implementing a restructuring of the network and optimal deployment of the distributed energy generators (DEGs). Two solutions for this network restructuring were proposed. Furthermore, a grid-oriented genetic algorithm (GOGA) was designed by combining the conventional genetic algorithm (GA) and mathematical solutions to identify optimal DEG placement. A power system restructuring and GOGA flexibility index (PSRGFI) was formulated for the assessment of network flexibility. A cost–benefit assessment was also performed to estimate the payback period for the investment required for restructuring of the network and DEG placement. The least-square approximation technique was applied for load projection for the year 2031 considering the base year 2021. It was established that minimization of transmission losses, reduction in voltage deviations, and improvement of network flexibility were achieved through hybrid application of network restructuring and DEG placement using GOGA. A network loss saving of 61.19 MW was achieved via optimal restructuring and GOGA. For the projected year 2031, the PSRGFI increased from 30.94 to 132.78 after the placement of DEGs using GOGA and optimal restructuring, indicating that network flexibility increased significantly. The payback period for the investment was very small, equal to 0.985 years. The performance of the designed method was superior to the GA-based method, simulated annealing technique, and bee colony algorithm (BCA) used for placement of DEG units in the test network. The study was completed using MATLAB software, considering data from a practical transmission network owned by Rajasthan Rajya Vidyut Prasaran Nigam Ltd. (RVPN), India. metadata Kaushik, Ekata; Prakash, Vivek; Ghandour, Raymond; Al Barakeh, Zaher; Ali, Ahmed; Mahela, Om Prakash; Álvarez, Roberto Marcelo y Khan, Baseem mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, roberto.alvarez@uneatlantico.es, SIN ESPECIFICAR (2023) Hybrid Combination of Network Restructuring and Optimal Placement of Distributed Generators to Reduce Transmission Loss and Improve Flexibility. Sustainability, 15 (6). p. 5285. ISSN 2071-1050 document_url: http://repositorio.uneatlantico.es/id/eprint/17804/1/sustainability-15-05285.pdf