An improved differential evolution based approach for emission constrained optimal power flow

This paper presents a Differential Evolution (DE) based approach for solving Multi Objective Optimal Power Flow (MO-OPF) problems. Differential Evolution (DE) is one of stochastic- population based algorithm which is well suited for solving multi -objective optimization problems involving several, often conflicting objectives. However, in order to improve DE algorithm´s optimized performance, a Double Best Mutation Operator (DBMO) is proposed to obtain a good convergence rate. Generator active power output, Voltage magnitude of generator buses, Transformer tap position and Reactive power generation of capacitor banks are taken as the control variables. The proposed approach has been evaluated on the standard IEEE -30 bus test system with cost minimization objective, environmental pollution minimization objective and with voltage stability improvement. Simulation results show the effectiveness of the proposed approach in solving the OPF problem.