Optimal Integration of Active and Reactive Power DGs in Distribution Network via a Novel Multi-Objective Intelligent Technique

• Published in: 2024 IEEE 4th International Conference in Power Engineering Applications: Powering the Future: Innovations for Sustainable Development, ICPEA 2024
• Main Author: Abdullah A.; Musirin I.; Othman M.M.; Rahim S.R.A.; Shaaya S.A.; Senthil Kumar A.V.
• Format: Conference paper
• Language: English
• Published: Institute of Electrical and Electronics Engineers Inc. 2024
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85191739695&doi=10.1109%2fICPEA60617.2024.10498595&partnerID=40&md5=7f1239ee241ed192b3d0f6d17a874cf8

This work introduces a novel approach called the Multi-Objective Integrated Immune Moth Flame Evolutionary Programming (MO-IIMFEP) algorithm. This algorithm aims to determine the optimal sizes and positions for Type III distributed generators (DGs) that generate both active and reactive power. The objectives involve reducing overall losses in the distribution system while adhering to voltage restrictions and taking into account the cost limitations connected with the installation of DG. MO-IIMFEP overcomes the constraints of traditional Evolutionary Programming (EP) and Moth Flame Optimization (MFO), particularly in effectively handling local optima. Fuzzy logic is employed in MO-IIMFEP to determine the best solution to compromise conflicting goals, as obtained from the non-dominated Pareto solutions. The efficacy of MOIIMFEP in identifying optimal solutions for multi-objective problems is demonstrated through comprehensive assessments conducted on the 118-Bus Radial Distribution Systems (RDS), comparing it against MO-EP and MO-MFO. The results underscore the strategic benefits of DG installation in sustaining voltage levels, reducing power losses, and minimizing total operating costs for power suppliers. © 2024 IEEE.