Research On Improved Pigeon Flock Optimization Algorithm And Its Application

Pigeon swarm optimization algorithm is a new swarm intelligence optimization algorithm proposed by Professor Duan Haibin.The structure is inspired by the homing behavior of pigeons,and simulates the flight process of pigeons when they return to their nests using factors such as the sun,magnetic field and terrain in nature.The algorithm has the advantages of easy implementation,clear structure,easy to understand and strong searching ability,and has been widely used in many fields such as robot path planning,discrete shop scheduling,image segmentation and UAV task allocation.With the deepening of the research,the shortcomings of pigeon swarm optimization algorithm are gradually found,such as easy to fall into the local optimal,slow convergence speed,poor stability and so on.In this paper,from multiple perspectives,aiming at the shortcomings of pigeon swarm optimization algorithm,three different improved pigeon swarm optimization algorithms are put forward,and the problems of function optimization,economic scheduling of power system and capacity optimization of hybrid energy storage system are solved,which make a certain contribution to the expansion of the application field of pigeon swarm optimization algorithm and the improvement of basic theory.The details are as follows:(1)In order to improve the optimization accuracy and convergence speed of the basic pigeon swarm optimization algorithm,a discoverer strategy was introduced and a pigeon swarm optimization algorithm based on discoverer strategy was proposed.Using 23 reference functions as test objects and 7 other heuristic optimization algorithms as comparison algorithms,the experimental results show that the discoverer strategy based pigeon flock optimization algorithm has strong optimization ability in function optimization problems.(2)In order to effectively reduce the minimum cost of economic dispatch of power system,a pigeon swarm optimization algorithm based on chaos initialization and Gaussian variation is proposed by introducing cubic chaotic mapping,Gaussian variation and decline factor from multiple perspectives.The improved pigeon swarm optimization algorithm is applied to solve the economic dispatching problem of power system.The experimental results show that the algorithm can effectively reduce the economic cost of power system considering the valve point effect,and provide a new method for solving the economic dispatching problem of power system.(3)In order to expand the application field of pigeon flock optimization algorithm,a pigeon flock optimization algorithm based on grey Wolf predation strategy was introduced in the early stage of the iteration of pigeon flock optimization algorithm,and the algorithm was applied to the capacity optimization of hybrid energy storage system.Through the actual case analysis,compared with the other 5 swarm intelligence optimization algorithms,the pigeon swarm optimization algorithm based on grey Wolf predation strategy is more suitable for solving the capacity optimization problem of hybrid energy storage system.