Fault Detection Based on Hierarchical Cluster Analysis in Wide Area Backup Protection System

In wide area backup protection of electric power systems, the prerequisite of protection device's accurate, fast and reliable performance is its corresponding fault type and fault location can be discriminated quickly and defined exactly. In our study, global information will be introduced into the backup protection system. By analyzing and computing real-time PMU measurements, basing on cluster analysis theory, we are using mainly hierarchical cluster analysis to search after the statistical laws of electrical quantities' marked changes. Then we carry out fast and exact detection of fault components and fault sections, and finally accomplish fault isolation. The facts show that the fault detection of fault component (fault section) can be performed successfully by hierarchical cluster analysis and calculation. The results of hierarchical cluster analysis are accurate and reliable, and the dendrograms of hierarchical cluster analysis are in intuition.

Fault Diagnosis Based on Graph Theory and Linear Discriminant Principle in Electric Power Network

In this paper, we adopt a novel topological approach to fault diagnosis. In our researches, global information will be introduced into electric power network, we are using mainly BFS of graph theory algorithms and linear discriminant principle to resolve fast and exact analysis of faulty components and faulty sections, and finally accomplish fault diagnosis. The results of BFS and linear discriminant are identical. The main technical contributions and innovations in this paper include, introducing global information into electric power network, developing a novel topological analysis to fault diagnosis. Graph theory algorithms can be used to model many different physical and abstract systems such as transportation and communication networks, models for business administration, political science, and psychology and so on. And the linear discriminant is a procedure used to classify an object into one of several a priori groupings dependent on the individual characteristics of the object. In the study of fault diagnosis in electric power network, graph theory algorithms and linear discriminant technology must also have a good prospect of application.

Applications of Data Mining Theory in Electrical Engineering

In this paper, we adopt a novel applied approach to fault analysis based on data mining theory. In our researches, global information will be introduced into the electric power system, we are using mainly cluster analysis technology of data mining theory to resolve quickly and exactly detection of fault components and fault sections, and finally accomplish fault analysis. The main technical contributions and innovations in this paper include, introducing global information into electrical engineering, developing a new application to fault analysis in electrical engineering. Data mining theory is defined as the process of automatically extracting valid, novel, potentially useful and ultimately comprehensive information from large databases. It has been widely utilized in both academic and applied scientific researches in which the data sets are generated by experiments. Data mining theory will contribute a lot in the study of electrical engineering.

Framework for Preventive Control of Power Systems to Defend Against Extreme Events

Enhancing power system resilience against extreme events is becoming increasingly critical. This paper discusses a unified framework for preventive control of power systems to enhance system resilience, which includes three parts: resilience assessment, resilience grading, and resilience enhancement. First, the resilience assessment contains facility-level and system-level resilience assessment. The concept of fragility curve is used in the facility-level resilience assessment. Various resilience indices are developed in system-level resilience assessment to roundly depict the impacts of extreme events on power systems and determine the system resilience. On this basis, the resilience is divided into different levels by resilience grading strategy, which can efficiently quantify the severity of the impact of extreme events and provide decision-making for the resilience enhancement strategies. Then, control strategies for enhancing power system resilience are also divided according to different resilience levels. A controlled islanding based preventive control is proposed to enhance system resilience, which aims to strengthen the first defensive line of power systems to deal with extreme events. Finally, taking the typhoon disaster in extreme events as an example, two tests carried out with two typhoons demonstrate the efficiency of the proposed method.

Coordinated Modulation Strategy Considering Multi-HVDC Emergency for Enhancing Transient Stability of Hybrid AC/DC Power Systems

This paper presents a multi-HVDC emergency coordinated modulating strategy to enhance the transient stability of hybrid AC/DC power systems.First,the main factors that affect the unbalanced energy distribution during a fault are analyzed,and the dominant generators are determined online.Next,considering the influence on both generators in the sending and receiving ends,the assessment index that evaluates the effects of DC power support is established.On the basis of this,a dynamic DC power support strategy is put forward,and the DC support sequence table is promptly updated by the changing dominant generators.The AC/DC hybrid power system with multi-DC lines is built and used as a test system.The simulation results of different scenarios demonstrate that the proposed method could follow the dominant generator dynamically and adjust the DC participating in modulation to enhance the transient stability effectively and quickly.