Optimal VAR control for real power loss minimization using differential evolution algorithm

• A differential evolution technique with various mutation strategies is used to solve the reactive power dispatch problem.
• The methodology has been tested on the IEEE 14-bus, 30-bus and the equivalent Algerian power system network 114-bus.
• DE algorithm is a robust and efficient method for solving the ORPD problem.
• Simulation results confirm the superiority of DE algorithm over PSO, IPM and other methods in the literature.

Differential evolution algorithm (DEA) is an efficient and powerful population-based stochastic search technique for solving optimization problems over continuous space, which has been proved to be a promising evolutionary algorithm for solving the ORPD problem and many engineering problems. However, the success of DEA in solving a specific problem crucially depends on appropriately choosing trial vector generation strategies (mutation strategies) and their associated control parameter values. This paper presents a differential evolution technique with various trial vector generation strategies based on optimal reactive power dispatch for real power loss minimization in power system. The proposed methodology determines control variable settings such as generator terminal voltages, tap positions and the number of shunts compensator to be switched, for real power loss minimization in the transmission systems. The DE method has been examined and tested on the IEEE 14-bus, 30-bus and the equivalent Algerian electric 114-bus power system. The obtained results are compared with two other methods, namely, interior point method (IPM), Particle Swarm Optimization (PSO) and other methods in the literature. The comparison study demonstrates the potential of the proposed approach and shows its effectiveness and robustness to solve the ORPD problem.