Abstract:
Optimal power flows justify the whole operational planning and operation of power system. Optimal control settings as active power generations, Voltages of all generators, optimal setting of transformer and compensators with a view of minimization of one or more objective functions such as fuel cost, losses, etc. It is a constrained optimization problem statement; it can be solved by traditional mathematical techniques. These techniques grieve from the drawback of landing at sub-optimal solution and difficulties in handling non-differentiable and discontinuous functions. The development of Evolutionary algorithms such as GA, PSO, EP, etc. has tried to overcome the drawbacks. Recently, Flower Pollination Algorithm (FPA), a nature-intriguing algorithm works based on the characteristics off lowering plants. Its evolutionary characteristics can be utilized to determine a solution methodology for optimal power flow. This paper extends to develop a Flower Pollination Algorithm based methodology for solving Optimal Power Flow with a view to obtain the global best solution and presents the results on IEEE 30 bus system to display its effectiveness
