【摘要】 提出了一种用于求解一股形式的非连续、非凸、非线性约束优化问题的改进粒子群算法,用于求解复杂的非凸、非线性电力系统经济负荷分配问题。基于随机分析理论,证明了该算法依概率收敛至全局最优,且收敛性与粒子群的初始分布无关,并提出一个收敛的充分条件。多个算例的仿真结果表明:文中提出的算法有效、可行,可望应用于更广泛的优化问题更多还原

【Abstract】 A new versatile optimization called enhanced particle swarm optimization algorithm (EPSO) is presented. The algorithm can be used to solve the discontinuous, nonconvex, nonlinear constrained optimization problems. The economic dispatch (ED) problem of power system is solved by this algorithm. The convergence property of the EPSO is discussed based on the stochastic analysis theory, and the results prove that the enhanced particle swarm optimization algorithm has global convergence property and the convergence property is independent of the initialization distribution. Moreover, a sufficient condition for convergence is presented. The algorithm is tested and validated in two cases. The results show that the EPSO for ED problem is versatile and efficient.更多还原