Optimal Planning of Multiple Renewable Energy-Integrated Distribution System With Uncertainties Using Artificial Hummingbird Algorithm

Appropriate installation of renewable energy-based distributed generation units (RDGs) is one the most important challenges and current topics interest in optimal functioning modern power networks. Due to intermittent nature energy sources, allocation sizing RDGs, particularly photovoltaic (PV) wind turbine (WT), remains a critical task. Based on new metaheuristic known as Artificial hummingbird algorithm (AHA), this paper provides novel approach for addressing problem RDG planning optimization. Considering various operational constraints, optimization developed with multiple objectives including loss reduction, voltage stability margin (VSM) enhancement, deviation minimization, yearly economic savings. Furthermore, using relevant probability distribution functions, ambiguities related stochastic PV WT output powers are evaluated. The proposed was compared two recent metaheuristics applied domain improved harris hawks particle swarm (HHO-PSO) hybrid phasor gravitational search (PPSOGSA). IEEE 33-bus 69-bus systems assessed test study. According findings, AHA delivers superior solutions enhances techno-economic benefits all scenarios