Method of power grid fault diagnosis using intuitionistic fuzzy Petri nets

Zhang, Xu; Yue, Shuai; Zha, Xiaobing

doi:10.1049/iet-gtd.2017.0471

Cited by 55 publications

(29 citation statements)

References 19 publications

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“…Identification Value Data. This paper uses the statistical probability data of long-term actual operation, provided by study [24]. The data are weighted by the timing confidence to assign values to the protection place and the circuit breaker place.…”

Section: Settings Of Simulation Parametersmentioning

confidence: 99%

“…(3) Learning from study [24], it must be ensured that the model's fault-tolerant transition threshold is set to a value (0.2, 0.7).…”

Section: Setting the Model Network Parametersmentioning

confidence: 99%

“…The obtained data results are compared with study [24] in relation to the same faulty case. As shown in Table 1, the failure probability value of the component that should be faulted is significantly increased, and the failure probability value of the nonfaulty component is significantly reduced.…”

Section: Numbermentioning

confidence: 99%

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Power Grid Fault Diagnosis Method Using Intuitionistic Fuzzy Petri Nets Based on Time Series Matching

Tan

Chen

et al. 2019

Complexity

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To improve the reliability of power grid fault diagnosis by enhancing the processing ability of uncertain information and adequately utilizing the alarm information about power grids, a fault diagnosis method using intuitionistic fuzzy Petri Nets based on time series matching is proposed in this paper. First, the alarm hypothesis sequence and the real alarm sequence are constructed using the alarm information and the general grid protection configuration model, and the similarity of the two sequences is used to calculate the timing confidence. Then, an intuitionistic fuzzy Petri Nets fault diagnosis model, with an excellent ability to process uncertain information from intuitionistic fuzzy sets, is constructed, and the initial place value of the model is corrected by the timing confidence. Finally, an application of the fault diagnosis model for the actual grid is established to analyze and verify the diagnostic results of the new method. The results for some test cases show that the new method can improve the accuracy and fault tolerance of fault diagnosis, and, furthermore, the abnormal state of the component can be inferred.

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Section: Settings Of Simulation Parametersmentioning

confidence: 99%

“…(3) Learning from study [24], it must be ensured that the model's fault-tolerant transition threshold is set to a value (0.2, 0.7).…”

Section: Setting the Model Network Parametersmentioning

confidence: 99%

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Power Grid Fault Diagnosis Method Using Intuitionistic Fuzzy Petri Nets Based on Time Series Matching

Tan

Chen

et al. 2019

Complexity

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“…At present, there are three kinds of techniques, which are theoretically mature: Expert system (ES), analytic model, and artificial neural network (ANN). In addition, rough set (RS) [1,2], Petri net [3][4][5], Bayesian network [6][7][8], and fuzzy set (FS) [9][10][11] have also been successfully applied in the intelligent identification and alarm of power systems. Expert system identifies through expert knowledge representation and logical reasoning mechanisms.…”

Section: Introductionmentioning

confidence: 99%

Identification Technology of Grid Monitoring Alarm Event Based on Natural Language Processing and Deep Learning in China

et al. 2019

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Power dispatching systems currently receive massive, complicated, and irregular monitoring alarms during their operation, which prevents the controllers from making accurate judgments on the alarm events that occur within a short period of time. In view of the current situation with the low efficiency of monitoring alarm information, this paper proposes a method based on natural language processing (NLP) and a hybrid model that combines long short-term memory (LSTM) and convolutional neural network (CNN) for the identification of grid monitoring alarm events. Firstly, the characteristics of the alarm information text were analyzed and induced and then preprocessed. Then, the monitoring alarm information was vectorized based on the Word2vec model. Finally, a monitoring alarm event identification model based on a combination of LSTM and CNN was established for the characteristics of the alarm information. The feasibility and effectiveness of the method in this paper were verified by comparison with multiple identification models.

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“…To deal with the fault diagnosis problem, many kinds of methods have been proposed, such as the approaches based on expert system [2][3][4], artificial neural network [5][6][7], fuzzy theory [8,9], rough sets [10,11], Bayesian network [12][13][14], Petri nets [15][16][17] and analytic model [18][19][20][21]. Although these methods have advantages in some respects, they have their own disadvantages.…”

Section: Introductionmentioning

confidence: 99%

An Analytic Method for Power System Fault Diagnosis Employing Topology Description

Yin

et al. 2019

Energies

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When a fault occurs in a power system, fault section estimation is the primary premise for troubleshooting and power recovery, and an effective fault diagnosis system will play a big role in decision making. However, the topology information is not well employed in existing fault diagnosis methods, and it is complex and time consuming to analyze the relationship between the protective devices and the sections. In this paper, a novel analytic method which employs topology description is proposed for fault diagnosis. The topology descriptions of the sections and the protective devices are firstly established according to the network structure, and based on which the operating logic and the cooperative relationship of the protective devices can be easily analyzed by matrix operation. Considering the factors of logic error and communication error, the fault diagnosis problem is formulated as an integer programming problem and can be solved by intelligent algorithm. The case studies of different power systems show that the proposed method can quickly identify the fault section, even with the abnormal operation or error alarm of protective devices.

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Method of power grid fault diagnosis using intuitionistic fuzzy Petri nets

Cited by 55 publications

References 19 publications

Power Grid Fault Diagnosis Method Using Intuitionistic Fuzzy Petri Nets Based on Time Series Matching

Power Grid Fault Diagnosis Method Using Intuitionistic Fuzzy Petri Nets Based on Time Series Matching

Identification Technology of Grid Monitoring Alarm Event Based on Natural Language Processing and Deep Learning in China

An Analytic Method for Power System Fault Diagnosis Employing Topology Description

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