An improved genetic algorithm based economic dispatch with nonsmooth fuel cost function

This paper presents an efficient method for solving the economic dispatch (ED) problems with valve-point effect by improved genetic algorithm (IGA). In the ED problems, the inclusion of valve-point loading effects makes the modelling of the fuel cost functions of generating units more practical. However, this increases the nonlinearity as well as number of local optima in the solution space. Also the solution procedure can easily trap in the local optima in the vicinity of optimal value. A genetic algorithm (GA) equipped with the improved evolutionary direction operator (IEDO) and gene swap operator called the improved genetic algorithm(IGA) is proposed, which can efficiently search and explore solution. To demonstrate the effectiveness of the proposed method, the numerical studies have been performed for two test systems consisting of 13 and 40 thermal units whose incremental fuel cost function takes into account the valve-point loading effects. The results obtained through the proposed method are compared with those reported in the literature.