A Novel Method of Optimizing Lifetime and Reduction in Power Consumption in Wireless Sensor Network

Optimal power flow (OPF) problem has already been attempted as a static, optimization problem by adopting gradient based methods and more recently, no conventional ones, such as evolutionary algorithms. However, as the loads, generation capacities and network connections in a power system are always in a changing status, these static methods are of limited use. This paper presents a new algorithm dynamic bacterial forging optimization, for solving the optimal power flow problem in wireless networks in which the systems load changes. The simulation results show that the proposed algorithm can more rapidly adapt to load changes, and more closely adapt to load changes, and more closely trace the global optimum of the system fuel cost.