A review of power system protection and asset management with machine learning techniques

Aminifar, Farrokh; Abedini, Moein; Amraee, Turaj; Jafarian, Peyman; Samimi, Mohammad Hamed; Shahidehpour, Mohammad

doi:10.1007/s12667-021-00448-6

Cited by 33 publications

(17 citation statements)

References 150 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The research on intelligent control in the power system is from the brilliant controlling perspective. We hope to give "knowledge" and "judgment" to the computer to realize the wholeprocess intelligence of prevention, emergency disposal, and recovery of transient problem control (118). Therefore, introducing AI into the control field of transient problems, and taking advantage of AI in group intelligence, processing complex data relationships, and learning ability, can help to relieve the pressure of traditional control modes to cope with uncertain scene control.…”

Section: Diversification Of Transient Controlmentioning

confidence: 99%

AI-oriented Smart Power System Transient Stability: The Rationality, Applications, Challenges and Future Opportunities

Guo

Qureshi

Jarwar

et al. 2023

Sustainable Energy Technologies and Assessments

View full text Add to dashboard Cite

Section: Diversification Of Transient Controlmentioning

confidence: 99%

AI-oriented Smart Power System Transient Stability: The Rationality, Applications, Challenges and Future Opportunities

Guo

Qureshi

Jarwar

et al. 2023

Sustainable Energy Technologies and Assessments

View full text Add to dashboard Cite

“…Machine learning-based extended Kalman filter hybridized with a support vector machine is used to classify faults that cause false tripping of differential protection system in three-phase transformers [18]. An exhaustive review of machine learning techniques is provided for electrical asset management and protection [19]. A differential protection scheme using a support vector machine is proposed and the accuracy achieved in detecting internal faults and inrush current is provided [20].…”

Section: Literature Surveymentioning

confidence: 99%

Transformer Internal and Inrush Current Fault Detection Using Machine Learning

Vidhya¹,

Ranjan²,

Shanker³

2023

Intelligent Automation &Amp; Soft Computing

View full text Add to dashboard Cite

Preventive maintenance in the transformer is performed through a differential relay protection system, and it protects the transformer from internal and external faults. However, the Current Transformer (CT) in the differential protection system mal-operates during inrush currents. CT saturates due to magnetizing inrush currents and causes false tripping of the differential relays. Moreover, identification of tripping in protection relay either due to inrush current or internal faults needs to be diagnosed. For the above problem, continuous monitoring of transformer breather and CT terminals with thermal camera helps detect the tripping in relay due to inrush or internal fault. The transformer's internal fault leads to high breathing process in the transformer breather, never for inrush currents. During inrush currents, CT temperature is increased. Continuous monitoring of breather and CT of the transformer through thermal imaging and radiometric pixels detect the causes of CT saturation and differentiates maloperation. Hybrid wavelet threshold image analytics (HWT-IA) based radiometric pixels analysis of the transformer breather and CT after de-noising provides an accurate result of about 95% for identification of the false tripping of differential protection system of transformer.

show abstract

“…The front end adopts the EasyUI framework, and the page layout uses the layout controls of EasyUI to realize the design and review system design of power transmission and transformation engineering based on the SSH framework. The system functionality, system processing capacity and system response time are used as test indicators, and the method of reference [4], the method of reference [5] and the proposed method are used to compare the method to verify the performance of the proposed method design system.…”

Section: System Test 51 Setting System Test Environmentmentioning

confidence: 99%

“…This paper uses a black box testing technology to test each functional module of the system Arcuri (2020) and Agarwal et al (2020). By comparing the methods of reference [4], the methods of reference [5] and the proposed methods, the functional test results of the system designed by different methods are as Table 1. According to table 1, the planning management module, review management module, quality assessment module, archiving management module and engineering information base management module of the design system according to the method of reference [4] are in normal state, but the pre-trial management module, comprehensive query module and system management module of the design system according to the method of reference [4] are abnormal.…”

Section: System Functional Testmentioning

confidence: 99%

Design of power transmission and transformation engineering design review system based on spring struts hibernate framework

Zhang

Saren

Jiang

et al. 2023

International Conference on Intelligent Systems, Communications, and Computer Networks (ISCCN 2023)

View full text Add to dashboard Cite

For the current design of power transmission and transformation engineering design review system, there are some problems, such as poor functionality and processing capacity, and long system response time. The design review system of power transmission and Transformation Engineering Based on Spring + Struts + Hibernate (SSH) framework is designed. According to the definition and characteristics of SSH framework, this paper puts forward three classical frameworks: Struts, Spring and Hibernate, and integrates SSH framework. Through data cleaning, conversion and standardization, the evaluation data of transmission line engineering are simplified, and the evaluation data of transmission and transformation engineering are clustered by clustering algorithm. Analyze the overall requirements and functional requirements of the system, adopt SSH framework and design the overall system architecture in combination with specific business. Divide the system function structure from the user use type. Through the design of database structure and data table, the design of power transmission and transformation engineering design review system based on SSH framework is realized. The experimental results show that all functional modules of the system designed by the proposed method are in normal state, with an average throughput of 94.8mbps and a response time of only 17.2s. The proposed method has better functionality and processing capacity, and shorter system response time.

show abstract

A review of power system protection and asset management with machine learning techniques

Cited by 33 publications

References 150 publications

AI-oriented Smart Power System Transient Stability: The Rationality, Applications, Challenges and Future Opportunities

AI-oriented Smart Power System Transient Stability: The Rationality, Applications, Challenges and Future Opportunities

Transformer Internal and Inrush Current Fault Detection Using Machine Learning

Design of power transmission and transformation engineering design review system based on spring struts hibernate framework

Contact Info

Product

Resources

About