Rahul Dubey

Adaptive Distance Relaying Scheme for Transmission Network Connecting Wind Farms

Abstract This article presents an adaptive distance relay setting for a power transmission network connecting more than one wind farm. The ideal trip characteristics of the distance relay is greatly affected in the presence of complex mutual coupling of transmission lines, as the apparent impedance is significantly affected. Similarly, the reach setting of the relay for the lines connecting wind farms is significantly affected, as the relaying voltage fluctuates continuously. Thus, the proposed study focuses on developing an adaptive relay setting for a transmission network including more than one wind farm and considering variations in operating conditions of wind farms and mutual coupling of transmission lines together. The proposed relay algorithm is extensively tested on two-terminal as well as multi-terminal power networks with wide variations in operating parameters. The performance testing of the proposed adaptive relay characteristics for faults and faults during power swing indicates the potential ability of the approach in handling distance relaying in a transmission system.

Extreme Learning Machine Based Adaptive Distance Relaying Scheme for Static Synchronous Series Compensator Based Transmission Lines

Abstract This article presents an extreme learning machine based fast and accurate adaptive distance relaying scheme for transmission lines in the presence of a static synchronous series compensator. The ideal trip characteristics of the distance relay is greatly affected by pre-fault system conditions, ground fault resistance, and zero-sequence voltage. The proposed research develops an extreme learning machine based adaptive distance relaying scheme for two-terminal transmission networks with static synchronous series compensators when a single-line-to-ground fault situation is most likely to occur. The study includes an analytical approach, including a steady-state model of static synchronous series compensator with detailed simulation on MATLAB/Simulink (The MathWorks, Natick, Massachusetts, USA) and open real-time simulation software with MATLAB (OPAL-RT) platform (OPAL-RT Technologies, Montreal, Quebec, Canada). The proposed extreme learning machine based adaptive distance relaying scheme is extensively validated on the two terminal transmission lines with static synchronous series compensators, and the performance is compared with the existing radial basis feed-forward neural network based adaptive distance relaying scheme. The results on simulation and real-time platform show significant improvements in the performance indices, such as speed, selectivity, and reliability of the digital relay.

Koopman Analysis Based Wide-Area Back-Up Protection and Faulted Line Identification for Series-Compensated Power Network

The paper presents wide-area back-up protection (WABP) and faulted line identification (FLI) scheme for series-compensated power transmission network. The proposed scheme uses the Koopman mode technique on fault current data obtained from phasor measurement units for WABP and FLI. The main advantage of the proposed scheme is that it is based on spatiotemporal information system (STIS). As we know that in real-world applications, often time and space exist together, and hence, dealing with spatial aspect without considering temporal aspect is of limited use. Similarly, the introduction of series compensation in a power transmission network is common nowadays due to many technical benefits. The FLI in a power network with series-compensation is more complicated due to complex transients produced by series capacitor and the metal–oxide varistor. The proposed scheme is developed using STIS for WABP and FLI under stressed conditions including power swing and load encroachment. The New England 39 bus system is used as the test system, which is developed on Dig-Silent power factory commercial software (PF4C) platform for evaluating the performance of the proposed technique. Further, the efficacy of the proposed scheme is also tested for other critical situations such as symmetrical fault during power swing and multievent detection and found to work effectively.

Artificial intelligence based approach for secured protection during stressed conditions

Maloperation of distance relays due to stressed conditions have caused a number of blackouts in the history of Power System protection. Limitations of the present blocking schemes have encouraged computational intelligent techniques to be used for assisting the conventional distance relay. For this purpose two of the most popular techniques have been employed namely Support Vector Machine (SVM) and Decision Tree (DT). SVM being a black-box model has limitations in interpreting the results obtained. While DT is a transparent method that not only makes the process comprehensible but also provides with the dominant features participating in the technique. A two level classifier scheme is built using both the models SVM and DT for distinguishing fault from stressed conditions and further differentiating the stressed conditions to be either Power Swing or Voltage Instability. It has been tested on WSCC 9 bus system with Dig SILENT Power Factory as the simulation software.

On-line Adaptive and Intelligent Distance Relaying Scheme for Power Network

Abstract The paper presents an on-line sequential extreme learning machine (OS-ELM) based fast and accurate adaptive distance relaying scheme (ADRS) for transmission line protection. The proposed method develops an adaptive relay characteristics suitable to the changes in the physical conditions of the power systems. This can efficiently update the trained model on-line by partial training on the new data to reduce the model updating time whenever a new special case occurs. The effectiveness of the proposed method is validated on simulation platform for test system with two terminal parallel transmission lines with complex mutual coupling. The test results, considering wide variations in operating conditions of the faulted power network, indicate that the proposed adaptive relay setting provides significant improvement in the relay performance.