基于PSO-GA混合算法的配电变压器检修优化

PSO-GA Hybrid Algorithm Based Maintenance Optimization for Power Distribution Transformer

针对当前流行的状态检修的概念,通过分析比较,确定了基于风险的配电网检修优化方法;并根据配电变压器历史故障概率数据通过威布尔分布拟合配电变压器的故障概率,并采用等效役龄对故障概率进行修正;计及设备检修时的检修风险和故障风险后,建立了以电网运行风险最小为目标的配电变压器检修优化模型;最后提出了一种以粒子群优化算法为主、遗传算法为辅的混合优化算法求解模型。该模型既能够降低搜索到局部最优解的概率,又能保证全局最优解的精度。算例验证表明了该方法的有效性。

In view of the current relatively popular conception of distribution network condition based on maintenance,the risk-based maintenance optimization is chosen through analysis and comparison.And considering the history data of the distribution transformer＇ s failure probability,a Weibull distribution is used to fit the distribution transformer＇ s failure probability.Then equivalent age is used to modify the failure probability.Taking the maintenance risk and failure risk into account,a distribution transformer maintenance optimization model is established basically.The objective function of the optimization model is the minimum of the risk of grid operation.A hybrid optimization algorithm is proposed to solve the optimized problem.The algorithm relies mainly on particle swarm optimization （PSO） with genetic algorithm （GA） as subsidiary.It can not only reduce the probability of local optima,but also ensure the accuracy of the global optimal solution.Finally using a case validates the effectiveness of this proposed method.