ABSTRACT

Optimal power flow solutions are required for the cost-effective operation and control of an existing power system as well as for its future expansion planning. In this paper, a hybrid meta-heuristic Jaya-Powell’s Pattern Search method is proposed to solve the optimal power flow problem integrated with distributed generating units. Powell’s Pattern Search method has been incorporated into the Jaya algorithm in three different ways, resulting in three variants namely; Jaya-PPS1, Jaya-PPS2, and Jaya-PPS3. Performance of these variants are evaluated by solving optimal power flow in IEEE 30-bus, IEEE 57-bus, and IEEE 118-bus systems. In all the cases, Jaya-PPS1 is found to provide a lower objective function value with a smaller deviation over multiple runs than other algorithms. For example, the combined objective function found by Jaya-PPS1 for IEEE 30-bus system is 937.340, with a reduction of 2.86% of the original system. This benefit increases further with system size.

摘要

现有电力系统的经济高效运行和控制以及未来的扩展规划需要最佳潮流解决方案。在本文中，提出了一种混合元启发式Jaya-Powell模式搜索方法来解决分布式发电机组集成的最优潮流问题。Powell 的模式搜索方法以三种不同的方式并入 Jaya 算法中，从而产生了三种变体：Jaya-PPS1、Jaya-PPS2 和 Jaya-PPS3。通过求解 IEEE 30 总线、IEEE 57 总线和 IEEE 118 总线系统中的最佳功率流来评估这些变体的性能。在所有情况下，与其他算法相比，Jaya-PPS1 在多次运行中提供了更低的目标函数值和更小的偏差。例如，Jaya-PPS1 为 IEEE 30 总线系统找到的组合目标函数为 937.340，比原系统减少了 2.86%。随着系统规模的扩大，这种优势会进一步增加。