Optimum Fuel Cost in Load Flow Analysis of Smart Grid by Using Artificial Bee Colony Algorithm

Smart grids have a structure that can feel overloads with real-time communication infrastructure, regulate energy flow directions, optimize the use of renewable energy sources and reduce user costs. The smart grid vision aims to develop the power system towards a network that is well integrated with advanced measurement technologies, wide area communication, and automatic controls. The benefits include fast decision making, high controllability, and system reliability. Various optimization methods are used to reduce the optimum fuel cost in the load flow analysis in smart grids. The classical optimization methods that have been used before have now been replaced by intuitive and herd based algorithms. One of the herd based algorithms is the artificial bee colony algorithm. The use of an artificial bee colony algorithm is often preferred in smart grids since it is flexible and the number of parameters is less than other algorithms and the online run time is low. In this study, an artificial bee colony algorithm is mentioned from herd based algorithms to obtain optimum fuel cost in the smart grid. The program written in the MATLAB environment was applied to the IEEE30 test busbar system and the results were compared to other heuristic algorithms.