求解电力系统多目标环境经济调度的帕累托最优MFO算法

Multi-objective economic-environmental dispatch based on Pareto optimal moth-flame optimization algorithm

本文提出了一种利用MFO算法解决电力系统环境经济调度的新方法,该算法利用飞蛾扑火原理对设定目标进行螺旋式搜索,并在目标位置进行重复检索。MFO算法对于大规模非线性规划问题具有较强的适应性和有效性。在求解环境经济调度问题中,结合实际发电系统运行过程中应满足的功率平衡约束和容量约束等,以总燃料成本和污染排放最低为目标建立多目标规划数学模型。运用帕累托最优前沿求取帕累托非劣性最优解,得到帕累托最优配置方案,在可行域中搜索出全局最优解。在MATLAB仿真平台对含40台发电机组系统进行仿真计算,结果表明本文提出算法在求解电力系统环境经济调度中具有较高的收敛性和较强的适应性。

This paper proposed a new method to solve economic-environmental dispatch of power system problem by using moth-flame optimization（ MFO） algorithm. The algorithm searchs the setting goals for spiral deeply by using moth-flame principle,and repeats to search in the target location. Moth-flame optimization algorithm has strong adaptability and effectiveness for large-scale nonlinear programming problems. In the process of solving the economic-environmental dispatch problem,with the power balance constraints and capacity constraints in the actual process of the electricity generation and operation,fuel costs and emissions of polluting gases are regarded as optimization objectives of the multi-objective programming model. The Pareto-optimal frontier can obtain the non-inferiority optimal solution,then the optimal allocation scheme is obtained and the global optimal scheduling scheme is searched in the feasible region. In the MATLAB simulation platform,the simulation calculation is carried out for 40 generating sets,and the results show that the algorithm proposed in this paper has high convergence and adaptability in solving the environmental economic dispatch of power system.