Optimal Allocation and Sizing of Distributed Generation in IEEE-85 BUS System Considering Various Load Models Using Multi-objective Metaheuristic Algorithms

Present-day distribution systems are bidirectional due to the integration of renewable energy sources and distributed generation. For efficient operation of the distribution systems, the loss reduction and voltage management are of the essential operational requirements. In India, the overall transmission and distribution losses for the 2018–2019 financial year were 20.66% and that needs major concerns for better efficiency of the system. The distribution system experiences voltage deviation and stability issues due to the improper management of the reactive power management and load growth. In order to limit these losses and better voltage profile, the system shall be planned with better control of reactive power and reduced losses. The losses and voltage can be better managed with the distribution generation integration into the existing system with optimal location and size. In this paper, DGs (distributed generation) in the radial distribution network have been optimally located and sized to minimize the line loss and enhance the voltage profile. This study aims to develop a multi-objective optimization model that considers various distribution load models while maximizing both technical and financial advantages. The appropriate positioning and sizing of DG resources in distribution networks are significantly influenced by load models and therefore, different load models have been incorporated in this study. The multi-objective function (MOF) contains the cost of active power loss reduction, voltage deviation enhancement, and the cost of installing DGs. The effects of four different load models are investigated using metaheuristic techniques. The study is carried out on an IEEE 85-bus radial distribution network as a test system. A comparison of results using Whale Optimization (WO), Grey Wolf Optimization (GWO), and Firefly Algorithm (FA) is analyzed to verify the effectiveness of the applied techniques.