Energy Management Optimization of Generators Using Modified Firefly Algorithm

In this study, the proposed microgrid system in island mode is consisting of a combination of conventional and renewable energy generating such as two diesel generators, two wind turbines, and three fuel cell plants. Using the artificial intelligence technology to manage its energy sources by optimization methods, to decide the scheduling of each generator’s optimum power output per hour over 24 hours at a minimum total generation cost using MATLAB software package. For management of the energy of the proposed microgrid in an hour-to-day, such data should be specified in advance, including the planned load demand, the wind forecast for the next day for each hour, and the cost coefficients of each generator. To investigate the optimum performance, each algorithm will be executed for 30 runs at each hour within 24 hours. The methods of optimization used in this microgrid system suggest modified of the firefly algorithm (IFA) by hybridizing it with the local search algorithm and then using IFA in this study to manage the energy sources. Eventually, the results obtained that the IFA method enhances the performance of the energy scheduling with minimise the total generation cost of microgrid compared to the other optimization methods presented in this study, which IFA method produced better results compared to the used FA.