Nonconvex Economic Dispatch by Integrated Artificial Intelligence

This paper presents a new algorithm by integrating evolutionary programming (EP), tabu search (TS), and quadratic programming (QP) methods to solve the nonconvex economic dispatch problem (NED). A hybrid EP and TS were used for quality control and the Fletcher's quadratic programming technique was used for solving. EP and TS determine the segment of a cost curve used, which is piecewise quadratic natured. Operation constraints are modeled as linear equality or inequality equations, resulting in a typical QP problem. Fletcher's QP was chosen to enhance the performance. The fitness function is constructed from priorities without penalty terms. Numerical results show that the proposed method is more effective than other previously developed evolutionary computation algorithms.