Application of Dingo Optimizer Algorithm for Optimal Power Flow Problems Solving

This paper introduces a newly developed metaheuristic optimization algorithm inspired by the natural behavior of the dingo to tackle optimal power flow problems in the power system. The Dingo Optimizer (DOA) is a nature-inspired algorithm that mimics dingoes’ foraging behavior, which includes exploration, encirclement, and exploitation. Optimal power flow (OPF) is the essential strategy for effective and economical power system operation and future planning. This proposed dingo optimizer is used to address the problem of optimal power flow by determining the optimal settings for the control variables in the power system without violating operational and physical limitations. Moreover, the objective function of the proposed method is loss minimization, while the control parameters are active and imaginary power injections, transformer tap-changers, and magnitudes of voltage. Utilizing the IEEE 30-bus system, the performance and efficacy of this were verified. Moreover, the findings are compared to those of three well-known methods, namely the genetic algorithm (GA), particle swarm optimization (PSO), and whale optimization algorithm (WOA). The results exhibit that DOA achieves substantially more than the comparatively faster methods.