混沌改进粒子群算法及其在储能电站优化调度中的应用  

Chaos improved particle swarm optimization algorithm and its application in control of energy storage power station

作　　者：杨晓辉[1] 李瑞欣 姚凯 周越 YANG Xiaohui;LI Ruixin;YAO Kai;ZHOU Yue(School of Information Engineering,Nanchang University,Nanchang 330031,China)

机构地区：[1]南昌大学信息工程学院,江西南昌330031

出　　处：《南昌大学学报（理科版）》2020年第1期76-80,86,共6页Journal of Nanchang University(Natural Science)

基　　金：国家自然科学基金资助项目(51765042,61662044)。

摘　　要：储能电站能够提高风电并网效益,减少弃风具有良好的发展前景。在储能电站调度策略中,粒子群算法具有较好的适应性与便捷性,但存在容易陷入局部最优的缺点。针对这一缺点,本文提出将混沌改进的粒子群算法应用到储能电站的控制之中。由于混沌具有随机性、遍历性、规律性和敏感性的特点,将混沌融入到粒子群运动过程中,可以达到粒子群稳定与混沌不断交替进行变动,从而达到全局寻优的特点。最后通过具体算例将算法改进前后进行对比,验证改进的可行性与算法的实际应用性。Energy storage generators can improve wind power grid-connected benefits and reduce abandoned wind,which has good development prospects.In the control strategy of energy storage station,particle swarm optimization has better adaptability and convenience,but it has the disadvantage of being easy to fall into local optimum.In view of this shortcoming,the chaos improved particle swarm optimization(PSO)algorithm is applied to the control of energy storage power station.Because of the characteristics of chaotic randomness,ergodicity,regularity and the sensitivity of the chaotic particle swarm into motion process,can achieve stable and continuous chaotic particle swarm changes alternately,so as to reach the global optimization.Finally,a specific example is given to compare the improved algorithm before and after the algorithm is improved to verify the feasibility and practical application of the algorithm.

关 键 词：储能电站 粒子群算法 LOGISTIC混沌序列 目标优化 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]