基于广义蚁群算法的电力系统经济负荷分配

ECONOMIC DISPATCH OF POWER SYSTEMS BASED ON GENERALIZED ANT COLONY OPTIMIZATION METHOD

提出了一种可用于求解一般形式的非凸、非线性约束优化问题的广义蚁群算法, 以用于求解复杂的非凸、非线性电力系统经济负荷分配问题。与用于组合优化的蚁群算法类似,该算法运用了正反馈、分布式计算和贪婪式启发搜索。基于不动点理论,给出了该算法收敛的充分条件。多个算例结果表明,文中提出的算法是有效可行的。

A new versatile optimization algorithm called generalized ant colony optimization (GACO) is presented. The economic dispatch (ED) problem of power systems be solved by the algorithm. The GACO is based on the concepts of ant colony optimization for combinatorial optimization problems. The positive feedback, distributed computation, and the constructive greedy heuristic are used in the algorithm to solve the discontinuous, nonconvex, nonlinear constrained optimization problems. The convergence property of the GACO is discussed based on the fixed-point theory on a complete metric space. Several sufficient conditions for convergence are presented. The algorithm is tested and validated in several cases. In these cases, the GACO can provide accurate dispatch solutions in reasonable time. The results show that the GACO for the ED problem is versatile, robust and efficient.