Multi Dimension-Based Optimal Allocation of Uncertain Renewable Distributed Generation Outputs with Seasonal Source-Load Power Uncertainties in Electrical Distribution Network Using Marine Predator Algorithm

In the last few years, integration of renewable distributed generation (RDG) in electrical distribution network (EDN) has become a favorable solution that guarantees and keeps satisfying balance between production consumption energy. this work, various metaheuristic algorithms were implemented to perform validation their efficiency delivering optimal allocation both RDGs based on multiple photovoltaic (PVDG) wind turbine (WTDG) EDN while considering uncertainties energy output as well load demand’s variation during all year’s seasons. The convergence characteristics results reveal marine predator algorithm was effectively quickest best technique attain solutions after small number iterations compared rest utilized algorithms, including particle swarm optimization, whale optimization algorithm, moth flame optimizer slime mold algorithm. Meanwhile, an example, minimized seasonal active losses down 56.56% 56.09% for applied networks IEEE 33 69-bus, respectively. To reach those results, multi-objective function (MOF) developed simultaneously minimize technical indices total power loss index (APLI) reactive (RPLI), voltage deviation (VDI), operating time (OTI), coordination interval (CTII) overcurrent relay test system EDNs, order approach practical case, which there are too many parameters be optimized, different constraints, uncertain variable data production.