Northern Goshawk Optimization for Optimal Allocation of Multiple Types of Active and Reactive Power Distribution Generation in Radial Distribution Systems for Techno-Environmental Benefits

Abstract

Radial distribution systems (RDSs) can work better from a technical, economic, and environmental point of view if they have the right mix of renewable energy-based distribution generation (DG) and reactive power sources like and distribution-static compensator (DSTATCOM). In this paper, the Northern Goshawk Optimization (NGO), a new meta-heuristic that mimics the hunting behaviour of the northern goshawk, is introduced as a way to figure out where and how big different types of active and reactive power DGs in RDSs should be. For the suggested multi-objective function, NGO is used to find the best places and sizes for photovoltaic systems (PVs), wind turbine systems (WTs), and DSTATCOMs. The main goals of the suggested method are to reduce distribution losses, improve the voltage profile, increase the voltage stability margin, and reduce greenhouse gas (GHG) emissions. Five different case studies are simulated to figure out how well the suggested method works with computers. Simulations use IEEE 33-bus feeder. When compared to the literature and other heuristic algorithms, the results show that NGO works. The computational efficiency of NGO is compared for four cases: (i) only PV ((ii) only WT (iii) only DSTATCOM and (vi) simultaneous PV, WT and DSTATCOM allocation. The results also show that the proposed NGO much efficient than other algorithms and also improves all techno-environmental factors and RDS performance in a big way