A novel approach for power system protection in high voltage power system at 132kv

Project Abstract

This research project proposes a novel approach for power system protection in high voltage power systems operating at 132kV. The aim of this study is to enhance the reliability and efficiency of protection systems in these critical infrastructure networks. The existing protection schemes for high voltage power systems face challenges in terms of response time, selectivity, and coordination. To address these issues, the proposed approach integrates advanced technologies such as phasor measurement units (PMUs), intelligent electronic devices (IEDs), and communication systems. The key focus of the novel approach is on improving fault detection and isolation capabilities in the power system. By leveraging the high-speed data acquisition capabilities of PMUs, the protection system can accurately detect and locate faults in real-time. This enables faster decision-making to isolate faulty sections and restore power to the healthy parts of the network promptly. The integration of IEDs with advanced signal processing algorithms further enhances the selectivity of the protection system, ensuring that only the faulty components are disconnected while maintaining continuity of service to the rest of the network. Furthermore, the communication infrastructure plays a crucial role in enabling seamless coordination among different protection devices distributed across the power system. By utilizing modern communication protocols and networking technologies, the proposed approach facilitates efficient information exchange between protection relays, enabling coordinated protection actions during fault conditions. This collaborative protection strategy minimizes the impact of faults and reduces the downtime of the power system, thereby improving overall system reliability. In addition to fault detection and isolation, the proposed approach also focuses on cybersecurity aspects to ensure the integrity and confidentiality of protection signals and data. By implementing robust encryption techniques and access control mechanisms, the protection system is safeguarded against cyber threats, ensuring the secure operation of the power network. Overall, the novel approach for power system protection in high voltage power systems at 132kV offers a comprehensive solution to enhance the reliability, efficiency, and cybersecurity of protection systems. By leveraging advanced technologies and communication systems, this approach enables faster fault detection, improved selectivity, coordinated protection actions, and enhanced cybersecurity measures, contributing to the overall resilience of high voltage power systems.

Project Overview

<p> In this thesis, a novel approach for the protection of transmission lines which utilizes only coefficient energy for both detection and classification is proposed. The fault current signals generated by workspace on MATLAB simulation model have been analyzed using Daubechie-4 (d4) mother wavelet at 7th level decomposition with the help of Wavelet Toolbox embedded in MATLAB. A case study of 132kV, 160km transmission line has been used to test the novel approach. The value of the coefficient energy of the current signals gives the indication of fault and no-fault conditions. The energy of the three phase current signal (A,B,C) at 7th level decomposition were calculated as 0.1559×10-5, &nbsp; 0.1328 x10-5, 0.1737 x10-5 (for normal condition), 6.4200 x10-5, 1.7730 x10-5, 1.6660 x10-5 (for A-G fault), 667.1000 x10-5, 700.9000 x10-5, 0.7860 x10-5 (for AB-G fault), 677.8000 x10-5, 689.9000 x10-5, 0.1740 x10-5(for A-B fault), 885.6000 x10-5, 898.3000 x10-5, 832.7000 x10-5(for ABC fault). Also, the coefficient energy ratios were calculated to help classify the faults. The total ratio of the coefficient energies of the three phases were found to be approximately 3.4819 (for normal condition), 5.9177 (for A-G fault), 1741.4580 (AB-G fault), 7861.3448 (for A-B fault), 3.1423 (for ABC fault). Like the coefficient energy, the ratio was found to be increasing as the severity of the fault increases, except for L-L-L fault. Hence, both coefficient energy and ratio were employed in fault classification. With the approach presented in this work, ten classes of fault (A-G, B-G, C-G, A-B, B-C, A-C, AB-G, BC-G, AC-G &amp; ABC) could be correctly identified and classified within fault duration of 0.085 seconds. The results therefore, demonstrate the proposed approach to be fast and reliable. <br></p>