Branko Stojanović, Tomislav Rajić, Darko Šošić
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引用次数: 1

摘要

本文提出了在风力发电机存在的情况下,用模拟退火(SA)方法对电容器同时切换的配电网进行重构。所分析的测试网络有69个节点,包括松弛节点和73个分支,所有节点都可以交换。假设:节点内负荷按高斯分布变化,风力发电机功率为威布尔分布,每小时变化一次,则各有两台最大功率为200kw的风力发电机(占总标称有功负荷的10%),可分配给除闲置节点外的任何节点。这同样适用于电容器组的分配。这种切换逻辑是不现实的。在此基础上,采用蒙特卡洛图解法,给出了风电机组和电容器组(最常访问的节点)分配的固定节点。输入功率因数大于0.85,这在开始配置时(从一开始)不满足,因此电容器组的分配是强制性的。另一个限制是网络不应该被过度补偿。研究了四种现实情景。在第一个模型中,只分析了带有风力发电机的网络,其余的用于所有可能的调节组合。该程序自动显示配置价格、生成库、输入数据(有功和无功负载、风力发电机的功率和位置)以及每小时变化的节余。风力发电机按节点均匀分布(对于不太现实的场景),只产生符合威布尔分布的有功功率。给出了1000小时运行的图形结果(1000小时运行,每小时不同),并对1000小时工作进行了分析。该方法表明,在已配置的风力发电机上同时应用重构方法和电容器切换可以实现相当大的节省。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rekonfiguracija distributivne mreže i otočna kompenzacija uz prisustvo vetro generatora
In this paper, the distribution network reconfiguration with simultaneous capacitor switching, in the presence of wind generators, by Simulated Annealing (SA) is presented. Analysed test network has 69 nodes including the slack one and 73 branches, all of which can commutate. Following assumptions are made: load in nodes is changed according to Gauss distribution and wind generator power with Weibull one, every hour, then there are two wind generators of 200 kW maximum power each (10% of total, nominal active power load) and they can be allocated to any node but the slack one. The same is valid for the capacitor banks regarding allocation. This switching logic is unrealistic. On its basis more realistic one was issued with fixed nodes for allocation of wind generators and capacitor banks (the most frequently visited nodes), by Monte Carlo graphical method. Input power factor is to be greater than 0.85 which is not fulfilled with commencing configuration (from the start) so that allocation of capacitor banks is mandatory. Another constraint is that the network should not be overcompensated. Four realistic scenarios are investigated. In the first one only network with wind generators is analysed and the rest are dedicated to all possible combinations of the regulation. The programme is automated indicating the price of configuration, generated banks, input data (active and reactive load, power and location of wind generators) and savings which change on an hourly basis. The wind generators are uniformly distributed in accordance to nodes (for the less realistic scenario) and generate only active power complying with Weibull distribution. The graphical results are presented for a 1000-hour operation (operation in one thousand hours, every hour different) and the analysis is done for a thousand-hour work. The presented method shows that considerable savings can be achieved by simultaneous application of reconfiguration method and capacitor switching with already allocated wind generators.
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