Optimalno pozicioniranje sinhrofazorskih jedinica primenom genetičkog algoritma

Katarina Obradović, Goran Dobrić
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Abstract

Energy transition implies a larger share of the intermittent renewable energy sources connected to the power grid. These utilities can change their production within a short period of time, thus, significantly affecting the voltage conditions and load flows in the grid. This adds to the complexity in achieving required reliability and stability of the system. Proper and timely insight into the grid parameters plays an important role in regulation of such power system. Implementation of Phasor Measurement Units (PMUs) provides information about electrical parameters of the grid with as much as microsecond precision. Therefore, possible occurring dynamical processes could also be observed and regulated in a proper manner. Considering PMU can give information regarding voltage phasor as well as currents of adjacent branches, the observability of the system can be achieved even if some nodes are not equipped with their own PMU. Furthermore, installation of PMU in every node is not economical solution considering the size of the power grid and the number of PMUs accordingly. One should assess the sufficient number of PMUs cautiously and locate them carefully in order to maintain observability, but also to reduce expenses as much as possible. In the grid topology with a vast number of nodes and branches, the usage of metaheuristic optimization algorithms with adequate criteria function and limiting conditions could reduce the computing time compared to the linear and non-linear programming algorithms. In addition, the quality of such solution is also preserved. In this paper, the usage of genetic algorithm is proposed in order to determine the number and position of PMUs for several different grid samples.
能源转型意味着更大比例的间歇性可再生能源接入电网。这些公用事业公司可以在短时间内改变其生产,从而显著影响电网中的电压条件和负载流。这增加了实现系统所需的可靠性和稳定性的复杂性。正确、及时地了解电网参数对该类电力系统的调节具有重要作用。相量测量单元(pmu)的实现提供了有关电网电气参数的信息,精度高达微秒。因此,可能发生的动态过程也可以以适当的方式观察和调节。由于PMU可以给出相邻支路的电压相量和电流信息,因此即使某些节点没有配备PMU,也可以实现系统的可观察性。此外,考虑到电网的规模和相应的PMU数量,在每个节点上安装PMU并不是经济的解决方案。人们应该谨慎地评估pmu的足够数量,并仔细地定位它们,以保持可观察性,同时也尽可能地减少费用。在具有大量节点和分支的网格拓扑结构中,与线性和非线性规划算法相比,使用具有适当准则函数和限制条件的元启发式优化算法可以减少计算时间。此外,这种溶液的质量也得到了保证。本文提出了利用遗传算法来确定不同网格样本中pmu的数量和位置。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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