Optimal Siting and Sizing of DGs and CBs with Single and Multi-objective in Distribution Network with Various Load Models under Load Growth using a Novel Meta-heuristic Technique: A Comprehensive Analysis /

Abstract

Distribution network planning and operation are facing several problems, including asset congestion, voltage fluctuations, and system instability. These problems must be quantified by the adequate planning and modeling of distributed generators (DGs) and capacitor banks (CBs). This paper presents the optimal allocation of DGs in parallel with the CBs in Distribution Network (DN) with single and multi-objectives by using the proposed Gazelle optimization algorithm (GOA) and Mountain Gazelle optimizer (MGO). The single and multi-objectives framework includes both technical objectives, like minimization of active power losses (APL), voltage stability (VS), and voltage deviation (VD), and non-technical objectives, including minimization of emission of pollutants greenhouse gases (GHG) and total electricity purchase cost. Furthermore, these planning problems are investigated on different nonlinear voltage- dependent models at two different loading conditions from future planning perspectives. The effectiveness and feasibility of the proposed algorithm are evaluated on the two IEEE standard networks of 33 and 69 bus systems. Three case studies are assessed at all load models using different loading conditions. As a result, our proposed MGO algorithm demonstrates a remarkable reduction in active power loss (APL). Moreover, a comparative analysis of other existing research works validated the efficiency and feasibility of established algorithms at each case with each load model by improving all the objective functions of network planning.