基于改进粒子群优化算法的最优潮流计算

提出应用粒子群优化算法（PSO）求解最优潮流问题（OPF），并结合动态调整罚函数法将最优潮流问题转化成一个无约束求极值问题，有效提高了PSO算法的全局收敛能力和计算精度。应用此算法对标准IEEE30节点系统进行潮流计算，并与线性规划算法和遗传算法进行了比较，结果表明，该算法能够更好地获得全局最优解，具有实用意义。

Improved Particle Swam Optimization Algorithm for Optimal Power Flow Problems

A new algorithm is presented to solve OPF problem using PSO technique in this paper. The main goal of this paper is to verify the viability of using PSO to solve the OPF problem composed by different objective functions. Incorporation of non-stationary multi-stage assignment penalty function in solving OPF problem can significantly improve the convergence and accuracy of PSO. The proposed PSO method is demonstrated and compared with LP approach and GA approach on the standard IEEE 30-bus system. The investigations reveal that the proposed PSO method is capable of obtaining higher quality solutions efficiently in OPF problem.