论文标题
比较元式电源系统计划
Comparison of Meta-Heuristics for the Planning of Meshed Power Systems
论文作者
论文摘要
电源系统计划任务是组合优化问题。目标函数可最大程度地减少受一系列技术和运营约束的经济成本。荟萃术通常用作优化策略，通过结合切换，线条加固或新线条测量，以找到解决此问题的解决方案。常见的启发式方法是GA，PSO，HC，ILS或GWO或FWA等新方法。在本文中，我们将这些算法在同一框架中进行比较。我们在8个不同的测试网格上测试了每种算法，范围为73至9421辆。对于每个网格和算法，我们开始50次运行，最长运行时间为1小时。结果表明，算法的性能取决于初始网格状态，网格大小和度量量。在大多数情况下，ILS方法非常健壮。在较大的测试网格中，例如GA和PSO，可以在较短的运行时间找到解决方案。
The power system planning task is a combinatorial optimization problem. The objective function minimizes the economic costs subject to a set of technical and operational constraints. Meta-heuristics are often used as optimization strategies to find solutions to this problem by combining switching, line reinforcement or new line measures. Common heuristics are GA, PSO, HC, ILS or newer methods such as GWO or FWA. In this paper, we compare these algorithms within the same framework. We test each algorithm on 8 different test grids ranging from 73 to 9421 buses. For each grid and algorithm, we start 50 runs with a maximum run time of 1 hour. The results show that the performance of an algorithm depends on the initial grid state, grid size and amount of measures. The ILS method is very robust in most cases. In the larger test grids, more exploratory heuristics, e.g., GA and PSO, find solutions in shorter run times.
