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Adaptive Fuzzy System for Discrimination of Fault from Non-fault Switching in Over-current Protection

机译:过电流保护中非故障切换故障判别的自适应模糊系统

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Power systems switching lead to short duration transients in the voltage and current. These transients have the potential to affect end-user equipment and it may equally affect the correct operation of protection relays close to the component being switched. In the case of non-fault switching events, such transients should not lead to over-current relays operation; therefore, a reliable relay response becomes a critical matter. Meanwhile, proper techniques must be used to prevent mal-trip of such relays, due to transient currents in the power system. In this article, a method is presented to discriminate fault from non-fault events using features extracted from current signal. The proposed method is designed based on extracting the fundamental frequency damping and ratio of the amplitude of the 2nd harmonic to amplitude of the fundamental harmonic and feeding them to an adaptive network-based fuzzy inference system (ANFIS) for discriminating fault from non-fault switching. The performance of this algorithm is demonstrated by simulation of different faults and switching conditions on a power system using EMTDC /PSCAD software.
机译:电力系统的切换导致电压和电流的短时瞬变。这些瞬变可能会影响最终用户设备,并且可能同样会影响靠近要开关组件的保护继电器的正确操作。在发生非故障切换事件的情况下,此类瞬变不应导致过电流继电器工作;因此,可靠的继电器响应变得至关重要。同时,由于电力系统中的瞬变电流,必须使用适当的技术来防止此类继电器误跳闸。在本文中,提出了一种使用从电流信号中提取的特征来将故障与非故障事件区分开的方法。在提取基本频率阻尼和二次谐波幅度与基本谐波幅度之比并将其馈入基于自适应网络的模糊推理系统(ANFIS)来区分非故障切换故障的基础上,设计了该方法。通过使用EMTDC / PSCAD软件对电力系统上的不同故障和开关条件进行仿真,证明了该算法的性能。

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