Self-adaptive Differential Evolution Based Optimal Power Flow for Units with Non-smooth Fuel Cost Functions

This paper presents a self-adaptive differential evolution with augmented Lagrange multiplier method (SADE_ALM) for solving optimal power flow (OPF) problems with non-smooth generator fuel cost curves. The SADE_ALM is a modified version of conventional differential evolution (DE) by integrating mutation factor (F ) and crossover constant (CR ) as additional control variables.An augmented Lagrange multiplier method (ALM) is applied to handle inequality constraints instead of traditional penalty function method, whereas the sum of the violated constraint (SVC ) index is employed to ensure that the final result is the feasible global or quasi-global optimum.The proposed algorithm has been tested with the IEEE 30-bus system with different fuel cost characteristics, i.e. 1) quadratic cost curve model, and 2) quadratic cost curve with rectified sine component model (valve-point effects). Numerical results show that the SADE_ALM provides very impressive results compared with the previous reports.