Coyote Optimization Algorithm-Based PV Planning Strategy for Maximizing Hosting Capacity in A Distribution System

This paper declares a Coyote Optimization Algorithm (COA)-based method of determining both optimal PV locations and sizes simultaneously in a distribution system with the largest hosting capacity (HC) of solar photovoltaic (PV) generation and minimizing system voltage deviation. The objective function includes PV hosting capacity (PVHC) and voltage deviation amplitude at each bus. The RMS bus voltage, the maximum size of each PV placement at an installed bus, the total active power losses, and reverse power flow at the substation are constraints to be met. The problem is solved using the Coyote Optimization Algorithm (COA). The IEEE 123-bus system is applied to test the proposed method. Results are compared with those obtained by other metaheuristic methods, including Genetic Algorithm and Particle Swarm Optimization. Test results show that the COA method yields exceptional solutions compare to GA and PSO methods in both optimality and convergence.