基于混合粒子群算法的波浪能发电集群优化方法

Wave energy converter cluster optimization method based on hybrid particle swarm algorithm

对波浪能发电集群的优化控制有助于波浪能的有效利用,为此文章提出了基于混合粒子群算法的波浪能发电集群优化方法。以直驱式发电装置为研究对象,探讨其构成发电集群短期尺度下稳定状态的数学模型,由简至繁依次考虑波浪动态压力、装置间辐射影响和遮挡效应,以便更准确地模拟一定密集度的波浪能发电装置部署下的实际效果。以集群功率最大化为优化目标,根据装置运动和海域能量约束,提出混合粒子群算法求解集群的最优参数,在传统算法基础上设定自适应惯性权重并加入交叉和变异操作,以应对复杂集群方程解空间的多峰性问题。算例结果验证了所述集群优化方法的有效性,求解质量良好;同时表明波浪能发电集群规模越大,装置之间的辐射影响越复杂,遮挡效应越明显。

The optimal control of wave energy converter clusters helps to make full use of wave resources,for which a wave power cluster optimization method based on a hybrid particle swarm algorithm is proposed.Direct-driven wave power generators are taken as the research object to explore the mathematical model forthe short-term scale of the steady state of power generation clusters.Wave dynamic pressure,radiation influence among devices and shading effect among devices are considered in orderto simulate more accurately the actual effect ofdeploying a certain density of wave energy devices:With wave cluster power maximization as the optimization objective,a hybrid particle swarm algorithm is proposed to solve the optimal parametersof the power generation cluster taking into account the motion of the power generation devices and the energy constraints of the sea area.Crossover and mutation operations are added to the traditional algorithm to cope with the problem ofmulti-peakability in the solution spaceof the complex equations.The results of the algorithms verify the effectiveness of the cluster optimization method withgood solution quality.They also show that the larger the size of the wave power generation cluster,the more complex the radiative influence between the devices and the more obvious the shading effect.