An adaptive chaotic differential evolution for the short-term hydrothermal generation scheduling problem

The short-term hydrothermal generation scheduling (SHGS) is a complicated nonlinear optimization problem with a set of operational and hydraulic constraints. A new approach is presented in this paper for solving the short-term hydrothermal generation scheduling problem by using an adaptive chaotic differential evolution algorithm (ACDE). In the proposed method, an adaptive dynamic parameter adjusting strategy is adopted to obtain the parameter settings in differential evolution algorithm (DE), and a chaotic local search (CLS) operation is integrated with DE to avoid premature convergence effectively. Moreover, new heuristic constraint handling methods without any penalty factor settings are proposed in this paper for the proposed ACDE to deal with the complicated constraints effectively. The feasibility and effectiveness of the proposed ACDE method is demonstrated for two test hydrothermal power systems. The simulation results reveal that, compared with other established methods like NO and DE, the proposed ACDE appears to be the best in terms of convergence property, computational efficiency and solution accuracy. (C) 2010 Elsevier Ltd. All rights reserved.