Multi-objective optimal allocation of multiple capacitors and distributed generators considering different load models using Lichtenberg and thermal exchange optimization techniques

Abstract Integrating distributed generations (DGs) into the radial distribution system (RDS) are becoming more crucial to capture benefits of these DGs. However, non-optimal integration renewable DGs and shunt capacitors may lead several operational challenges in systems, including high energy losses, poor voltage quality, reverse power flow, lower stability. Therefore, this paper, multi-objective optimization problem is expressed with precisely selected three conflicting goals, incorporating reduction both loss deviation improvement A new index for called root mean square suggested. The proposed problems addressed using two freshly metaheuristic techniques optimal sitting sizing multiple SCs unity optimally factors RDS, presuming voltage-dependent load models. These thermal exchange (MOTEO) Lichtenberg algorithm (MOLA), which regarded as being physics-inspired techniques. MOLA inspired by physical phenomena lightning storms figures (LF), while MOTEO developed based on concept Newtonian cooling law. a hybrid differs from many literature since it combines population trajectory-based search approaches. Further, methodology implemented IEEE 69-bus network during scenarios, such bi- tri-objective problems. fetched simulation outcomes confirmed superiority achieving accurate non-dominated solutions fewer outliers standard among all studied metrics.