Hybrid integer coded differential evolution – dynamic programming approach for economic load dispatch with multiple fuel options

This paper presents a novel and efficient approach through a hybrid integer coded differential evolution – dynamic programming (ICDEDP) scheme to solve the economic dispatch (ED) problem with multiple fuel options. A dynamic programming (DP) based simplified recursive algorithm is developed for optimal scheduling of the generating units in the ED problem. The proposed hybrid scheme is developed in such a way that an integer coded differential evolution (ICDE) is acting as a main optimizer to identify the optimal fuel options, and the DP is used to find the fitness of each agent in the population of the ICDE, which makes a quick decision to direct the search towards the optimal region. The hybrid ICDEDP decision vector consists of a sequence of integer numbers representing the fuel options of each unit to optimize quality of search and computation time. A gene swap operator is introduced in the proposed algorithm to improve its convergence characteristics. In order to show the efficiency and effectiveness, the proposed hybrid ICDEDP approach has been examined and tested with numerical results using the ten generation unit economic dispatch problem with multiple fuel options. The test result shows that the proposed hybrid ICDEDP algorithm has high quality solution, superior convergence characteristics and shorter computation time.