基于混合模糊Petri网的电力系统故障暂态识别方法

提出一种基于混合模糊Petri网(hybrid fuzzy Petrinets,HFPN)的电力系统故障暂态信号识别新方法。该方法将小波变换特征提取、模糊逻辑和模糊Petri网相结合构成混合模糊Petri网,有效解决了单一的模糊Petri网无法识别故障暂态信号的缺陷,也改善了原有识别方法推理过程不容易被人理解的不足。对故障发生后1/4个周期内的三相电流和零序电流,应用小波变换提取小波能量,再经过模糊推理系统得到模糊值作为特征量,最后应用模糊Petri网进行识别。大量PSCAD/EMTDC仿真试验结果表明:该故障识别方法能快速准确地识别各类故障暂态信号,识别速度快,并且以概率的形式给出发生各种故障的可能性;基于HFPN的图形化表示方法清晰直观,不受故障时刻、过渡电阻、故障位置等因素的影响,对噪声信号和不同线路都具有较好的适应性。

Study on Recognition of Fault Transients Using Hybrid Fuzzy Petri Net

A new hybrid fuzzy Petri net(HFPN) based method to recognize fault transient signals in power system is proposed.In the proposed method,the feature extraction of wavelet transform and fuzzy logic are integrated with fuzzy Petri net to constitute a HFPN to effectively solve the problem that a single fuzzy Petri net cannot recognize fault transient signals,and the defect of existing recognizing methods that the reasoning process is not easy to be understood is remedied.Using wavelet transform,the wavelet energy is extracted from three-phase current and zero-sequence current within the quarter period after the occurrence of the fault;then through fuzzy reasoning the obtained fuzzy value is taken as the characteristic quantity;finally the recognition is performed by fuzzy Petri net.Results from a lot of PSCAD/EMTDC based simulation show that the proposed fault classification method can recognize various fault transient signals rapidly and accurately,and the occurrence possibilities of various faults are given in the form of probability.The HFPN based graphical representation is clear and intuitionistic and is not affected by the factors such as moment when the fault occurs,transition resistance and fault position,thus it possesses good adaptability to the signals containing noise and various transmission lines.