A Two-Archive Harris Hawk Optimization for Solving Many-Objective Optimal Power Flow Problems

To improve power system operation and management and accomplish modern power system requirements, a new algorithm named two-archive harris hawk optimization (TwoArchHHO) is proposed to solve many-objective optimal power flow (MaOOPF) problems in this work. For modern power systems, only single-objective and multiobjective (2-3 objectives) optimal power flow problems (MOOPF) are inadequate. So, the problems become many-objective (more than 3 objectives) optimal power flow problem which is more complicated to be solved. Although several metaheuristic algorithms have been proposed to solve MOOPF problems, very few algorithms have been introduced to solve MaOOPF problems and high-performance algorithms are still required to solve MaOOPF problems which are more complicated. To solve the complicated MaOOPF problems, TwoArchHHO is proposed by adding the two-archive concepts of the improved two-archive algorithm into the harris hawk optimization (HHO) in order to enhance the searchability and eventually provide superior solutions. The objective functions considered to be minimized include fuel cost, emission, transmission line loss, and voltage deviation to improve power systems in the economic, environmental, and secure aspects. Several sizes of IEEE standard systems, which are IEEE 30-, 57-, and 118-bus systems, are tested to evaluate the performance of the proposed TwoArchHHO. The simulation results comprise Pareto fronts, best-compromised solutions, and hypervolume analysis are generated and compared with results from several algorithms in the literature. The data provided by the experimental trials and the hypervolume performance metric were examined using statistical testing methods. The results indicate that the TwoArchHHO obtained better optimal solutions than those of the compared algorithms including its traditional algorithms, especially in large systems. Based on the best-compromised solutions, the TwoArchHHO provided one best objective aspect among the compared algorithm for most cases. Based on the hypervolume, the TwoArchHHO generated better hypervolume values than those of the compared algorithms around 33.96% to 99.59% in the tested systems.