Flower Pollination Algorithm Based on Adaptive Dual Differential Evolution and its application in Smart Grid

Flower pollination algorithm is widely applied for optimization problem in smart power industry. It is easy to fall into local optimum that lead to the shortcoming performance of convergence speed and searching accuracy. Flower Pollination Algorithm Based on Adaptive Dual Differential Evolution (FPA-DE) is designed to enhance the searching ability in local and global process. Two differential evolution strategy is used to improve the exploration and development of optimization ability. Meanwhile, two type adaptive searching weight to decrease the deviation of random value of scaling factors. Benchmark functions are applied to evaluate the performance of FPA-DE, the simulation verifies that proposed algorithm can maintain higher performance and convergence speed. And FPA-DE is used to demonstrate the optimization in clustering for smart grid, and it can performs better in clustering index.