Human Behavior Based Optimization Algorithm for Optimal Power Flow Problem with Discrete and Continuous Control Variables

Abstract

In this work, the most challenging problem of the modern power system named optimal power flow (OPF) is optimized using the novel meta-heuristic optimisation algorithm Human Behavior- Based Optimization (HBBO). HBBO is inspired by human behavior in different field. HBBO has a fast convergence rate due to a use of roulette wheel selection method. So as to resolve the optimal power flow problem, the IEEE-30 busstandard system is used. HBBO is implemented for the solution of suggested problem. The problems considered in the OPF problem are Fuel Cost Reduction, Active Power Losses Minimization, Reactive Power Losses Minimization, Voltage Profile Improvement and Voltage Stability Enhancement. The outcomesachieved by HBBO is compared with Flower Pollination Algorithm (FPA), Particle Swarm Optimization (PSO) and other well-known techniques. Results show that HBBO gives better optimisation values as compared with FPA and PSO that confirms the success of the suggested algorithm.