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首页> 外文期刊>American journal of applied sciences >A GA Based Transmission Network Expansion Planning Considering Voltage Level, Network Losses and Number of Bundle Lines | Science Publications
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A GA Based Transmission Network Expansion Planning Considering Voltage Level, Network Losses and Number of Bundle Lines | Science Publications

机译:考虑电压水平,网络损耗和束线数的基于遗传算法的输电网络扩展规划科学出版物

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> Transmission Network Expansion Planning (TNEP) was studied considering voltage level, network losses and number of bundle lines using decimal codification based genetic algorithm (DCGA). TNEP determines the characteristic and performance of the future electric power network and directly influences the operation of power system. Up till now, various methods have been presented for the solution of the Static Transmission Network Expansion Planning (STNEP) problem. However, in all of these methods, STNEP problem has been solved regardless of voltage level of transmission lines. For this reason and according to various voltage levels and different number of bundle lines used in real transmission network which caused different annual losses, STNEP was studied considering voltage level, network losses and number of bundle lines using genetic algorithm. Genetic Algorithms (GAs) have demonstrated the ability to deal with non-convex, nonlinear, mixed-integer optimization problems, like the TNEP problem, better than a number of mathematical methodologies. The proposed method was tested on an actual transmission network of the Azerbaijan regional electric company, Iran, to illustrate its robust performance. The results were shown that considering the network losses in a network with different voltage levels and the number of bundle lines considerably decreased the operational costs and the network can be satisfied the requirement of delivering electric power more safely and reliably to load centers.
机译: >使用基于十进制编码的遗传算法(DCGA),考虑了电压水平,网络损耗和束线数,对传输网络扩展规划(TNEP)进行了研究。 TNEP决定了未来电网的特性和性能,并直接影响电力系统的运行。到目前为止,已经提出了解决静态传输网络扩展规划(STNEP)问题的各种方法。然而,在所有这些方法中,无论传输线的电压电平如何,都已解决了STNEP问题。因此,针对实际输电网络中使用的各种电压水平和不同数量的束线,造成每年的损失,使用遗传算法研究了STNEP,考虑了电压水平,网络损耗和束线数。遗传算法(GA)证明了处理非凸,非线性,混合整数优化问题(如TNEP问题)的能力优于许多数学方法。在伊朗阿塞拜疆地区电力公司的实际传输网络上对提出的方法进行了测试,以说明其强大的性能。结果表明,考虑到具有不同电压水平的网络中的网络损耗和束线的数量,大大降低了运营成本,并且可以满足网络向负载中心更安全可靠地供电的要求。

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