Solving Probabilistic Optimal Power Flow with Renewable Energy Sources in Transmission Networks Using Whale Optimization Algorithm

Thermal generators, which have a finite supply of fuel for electricity production, are typically the focus of the conventional optimum power flow problem (OPF), while electrical network emissions are frequently disregarded. The growing recognition of renewable energy sources, praised for their sustainability, availability, and eco-friendliness, has generated heightened interest in the field of power systems. As a result, there is an increasing tendency to incorporate renewable energy sources into the power grid. This study examines the modification of the standard IEEE-57 bus system through the integration of renewable energy sources as case examples. It concentrates on various solution methods, goal functions, constraints, and unique approaches to model the unpredictable behavior of renewable energy sources with probabilistic loads. This study also applies Whale Optimization Algorithm (WOA) as a key technique to solve the OPF problem and focuses on a rigorous comparative study, statistical analysis and simulation work to prove the effectiveness, efficiency and excellency of the proposed method. The results indicate that the proposed WOA method has got the tremendous potential in solving the said problem with impressive convergence rate, probability of success and handling nonlinear constrained optimization problem.