基于COA-EO混合算法的含DG的配电网Pareto最优规划

Pareto Optimal Planning Model of Distribution Network with DG Based on COA-EO Hybrid Algorithm

含DG的配电网规划是一种复杂的组合优化问题,随着智能配电网的发展以及波动性可再生能源的接入,对优化模型的效率提出了更高的要求。该文提出了基于混沌优化算法(chaos optimization algorithm,COA)和极值动力学优化算法(extreme dynamics optimization algorithm,EO)相互结合的多目标问题求解模型。通过算例验证,结果表明COA-EO优化算法同时利用COA算法和EO算法的优点,从而成功避免了各自缺陷,使得普通EO算法跳出局部最优,避免了算法的早熟现象,从而得到了全局最优结果。另外,为得到更好的多目标优化结果,引入Pareto最优解,并利用所提出的COA-EO算法求解Pareto最优解。计算结果亦表明COA-EO算法的优化性能优于EO算法、遗传(genetic algorithm,GA)算法、蚁群(ant colony optimization,ACO)算法、ACO-EO算法和GA-EO算法,说明COA-EO算法是解决含DG配电网规划问题的有效工具。

Distribution network planning with DG is a complex combinatorial optimization problem. Along with the development of smart distribution network and fluctuant renewable energy access,it puts forward higher requirements on the efficiency of optimization model. This paper proposed COA-EO algorithm which combined chaos optimization algorithm（ COA） and extreme dynamics optimization algorithm（ EO） to solve the multi-objective optimization problem. The example verification results showthat COA-EO optimization algorithm can take advantage of both COA and EO and manage to avoid the shortcomings,so that it can make ordinary EO escape from local optimal solution,avoid the premature phenomenon of the algorithm,and eventually obtain the globally optimal solution. In addition,in order to get a better multi-objective optimizationresult,this paper introduced the Pareto optimal solution,and used the proposed COA-EO algorithm to solve the Pareto optimal solution. The calculation results showthat the optimization performance of COA-EO algorithm is superior to EO,genetic algorithm（ GA）,ant colony optimization（ ACO）,ACO-EO algorithm and GA-EO algorithm,which indicates that COA-EO algorithm is effective for distribution network planning with DG.