Multi-DGPV Planning Using Artificial Intelligence

• Main Authors: Abdullah A., Musirin I., Othman M.M., Rahim S.R.A., Sentilkumar A.V.
• Other Authors: 57197864035
• Format: Article
• Published: Ismail Saritas 2024
• Subjects: Backward forward sweep; Distributed generation; Distributed generation photovoltaic; Evolutionary programming; Loss minimization; Optimization; Total voltage deviation

This article investigates the impact of multi-Distributed Generation Photovoltaic (DGPV) installation and their degree of penetration on controlling power loss in the radial distribution system. The Integrated Immune Moth Flame Evolution Programming (IIMFEP), a unique hybrid optimization technique, was utilized to identify the ideal DGPV size and location for base case conditions and under load variations. The IIMFEP approach is compared against Evolutionary Programming (EP), Artificial Immune System (AIS), and Moth Flame Optimization (MFO) and validated using the IEEE 118-Bus Radial Distribution Systems (RDS). Incorporating multi-DGPV into a system reduces the total real and reactive power loss while simultaneously increasing the minimum voltage and decreasing the total voltage deviation. In every instance examined in this study, the IIMFEP method yields optimal solutions superior to those generated by the other three methods. As the number of DGPV units increased to nine, the percentage of power loss reduction became the highest among all DG units examined, and DG penetration reached 94.26 percent. This research provides the power system operator with comprehensive findings demonstrating the impact of installing multi-DGPV in distribution networks on system loss. � 2023, Ismail Saritas. All rights reserved.