Automation of Electric Power SystemsVol. 40, Issue 16, Pages: 132-137(2016)
作者机构:
华北电力大学电气与电子工程学院,北京市,102206
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Published:2016
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LIU Chunming. [J]. Automation of electric power systems, 2016, 40(16): 132-137.
DOI:
LIU Chunming. [J]. Automation of electric power systems, 2016, 40(16): 132-137.DOI:
抑制变压器地磁感应电流的电容隔直装置安装位置优化
摘要
磁暴在电网中引起的地磁感应电流(GIC)导致变压器直流偏磁
对电力系统产生不利影响。在中性点安装电容隔直装置是治理变压器直流偏磁的常用方法
但由于GIC在电网中的流通路径复杂
在某个变压器安装隔直装置时
如不经充分考虑
往往会引起相邻变压器直流偏磁更加严重
因此文中研究电容隔直装置的安装位置优化问题。考虑自耦变压器接线和电网拓扑结构
引入变压器有效GIC来描述地磁暴对变压器的影响
分析了隔直装置的安装对变压器有效GIC分布造成的变化
提出了优化方法
在保证所有变压器的有效GIC小于允许限值的条件下
以隔直装置的安装数量最少作为优化的目标
并应用遗传算法求解。以甘肃主电网为例
构建包含47个变电站、101个节点的GIC等效模型
根据约束条件与优化目标
计算了隔直装置安装的数量和位置
并与未经优化的治理方案进行比较
验证了所提方法的可行性和优越性。
Abstract
Capacitor DC blocking devices are usually used for suppressing DC-bias of transformers. If there is no full consideration before installation
owing to the complex flow routes of geomagnetically induced currents(GIC)
the blocking device installed at the neutral point of a certain transformer may lead to more severe DC bias on adjacent transformers. Therefore the optimal position of installation for the capacitor blocking device is studied. This paper introduces the transformer effective GIC to describe the effect of geomagnetic storms on transformers by considering the wiring of autotransformers and the topology of power networks. After investigating the influence of DC blocking devices on transformer effective GIC
this paper proposes an optimization method of all transformers effective GIC being less than the allowable limiting value
with the least quantity of DC blocking devices as optimization objective
and the genetic algorithm to solve the problem. As an example
the GIC equivalent model of Gansu main power grid is built
which includes 47 substations and 101 nodes. Based on the model
the optimal quantity and installing location of DC blocking devices are calculated with the optimization method and genetic algorithm
and the outcome is compared with that derived from the un-optimized method. The results of calculation and comparison have verified the feasibility and superiority of optimization methods proposed in this paper. This work is supported by National Natural Science Foundation of China(No. 51177045)and National High Technology Research and Development Program of China(863 Program)(No. 2012AA121005).