首页> 外文会议>2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe >Self-adaptive protection strategies for distribution system with DGs and FCLs based on data mining and neural network
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Self-adaptive protection strategies for distribution system with DGs and FCLs based on data mining and neural network

机译:基于数据挖掘和神经网络的配电网和配电箱自适应配电系统保护策略

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摘要

Owing to development of renewable energy and environmental protection issues, distributed generations (DGs) have become a trend. In addition, fault current limiters (FCLs) may be installed to prevent the short circuit current from exceeding the capacity of the power apparatus. Nevertheless, some issues appear, simultaneously, the most important among which is the mis-coordination of the protection system. This paper proposes overcurrent protection strategies for distribution systems with DGs and FCLs. Via the proposed approach, the relays with communication ability can determine their own operating states from the operation setting decision tree and topology-adaptive Neural Network model based on the data processed by Fast Fourier Transformer (FFT). The performance and effectiveness of the proposed protection strategies are verified via the simulation results obtained from different system topologies with/without DGs, FCLs, and load variation.
机译:由于可再生能源的发展和环境保护问题,分布式发电已成为一种趋势。此外,可以安装故障电流限制器(FCL),以防止短路电流超过功率设备的容量。然而,同时出现了一些问题,其中最重要的是保护系统的不协调。本文提出了具有DG和FCL的配电系统的过电流保护策略。通过所提出的方法,具有通信能力的继电器可以基于快速傅立叶变压器(FFT)处理的数据,从操作设置决策树和拓扑自适应神经网络模型中确定自己的操作状态。通过从具有/不具有DG,FCL和负载变化的不同系统拓扑获得的仿真结果,验证了所提出保护策略的性能和有效性。

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