Solving optimum power flow in dynamic environments to minimize tracking errors using dynamic bacterial foraging algorithm

In this paper, a new optimization algorithm is presented for solving an optimal power flow problem with dynamic condition. Many artificial intelligence techniques have been developed for solving steady state environment of power system problems. In that, Bacterial Foraging Algorithm is one of the evolutionary algorithms which can be used to tackle the OPF problem for static environment. In real time scenario, the power flow in a power system has never been in a static state, as there always are changes in loads and system topology. Hence results using static environment cannot be trusted for dynamic environments. Based on the original BFA, Dynamic Bacterial Foraging Algorithm has been studied for the problem of OPF with dynamic loads and some modifications have been done to make this modified DBFA technique simple and efficient. This approach has been examined and evaluated on standard IEEE 30 Bus Test system. The simulation studies offer a range of changes in dynamic environment and results show that modified DBFA can adapt to various environmental changes which occur in different scenario, than using BFA and PSO.