Hybrid Self-adaptive Differential Evolution Method with Augmented Lagrange Multiplier for Power Economic Dispatch of Units with Valve-Point Effects and Multiple Fuels

This paper presents an efficient method for solving power economic dispatch problems using a hybrid self-adaptive differential evolution method with augmented Lagrange multiplier (SADE_ALM). Treated as additional control variables, two strategic parameters called the mutation factor (F) and the crossover constant (CR) are dynamically self-adaptive throughout the evolutionary process. Since tuning of the parameters is a tedious task due to complex relationship among parameters, the optimal parameter settings may never be found, and possibly leads to a local optimal solution. An augmented Lagrange multiplier method (ALM) is applied to handle equality/inequality constraints. With the developed algorithm, both the valve-point effects and multiple fuels can be simultaneously considered. To demonstrate the effectiveness of the proposed algorithm, two test cases are conducted and compared with other methods e.g. differential evolution (DE) based methods, improved evolutionary programming (IEP), improved genetic algorithm with multiplier updating (IGA_MU) etc. The results show that the proposed SADE_ALM is very effective and promising for solving the power economic dispatch problem