Real-time monitoring of partial discharge in air switchgear based on characteristic gases for insulation fault diagnosis

Аннотация

Partial discharge (PD) in electrical equipment, such as air switchgear, can lead to insulation degradation and, ultimately, equipment failure. Monitoring PD is crucial for preventing failures and ensuring the reliability of power systems. This study proposes an online monitoring method for PD in air switchgear based on characteristic gases generated by insulation defects. A novel gas detection system is developed that identifies gases released during partial discharge events. The system employs gas sensors to detect specific gases like acetylene (C2H2), methane (CH4), and ethylene (C2H4), which are associated with PD. The system's performance was evaluated in both laboratory conditions and in-field testing, showing that it successfully detected PD events with high accuracy. The research demonstrates the potential for real-time, non-invasive monitoring of PD to improve the reliability and safety of electrical switchgear. Keywords: Partial Discharge (PD) Detection, Air- insulated Switchgear (AIS), Real-time Monitoring, Insulation Fault Diagnosis, Characteristic Gas Analysis, Electrical Equipment Condition Monitoring, Gas Sensors for PD Detection, Power System Diagnostics, High-voltage Equipment Monitoring. Introduction: Air-insulated switchgear (AIS) is a critical component in power distribution systems, providing The American Journal of Applied Sciences 01 https://www.theamericanjournals.com/index.php/tajas The American Journal of Applied Sciences electrical protection and control. However, like all each gas in real-time and stored the data for further electrical equipment, AIS is susceptible to insulation analysis. defects, which can lead to partial discharge (PD). PD 4. Signal Processing: The raw data from the occurs when electrical discharges partially ionize the sensors were processed using a series of algorithms to insulation material, causing damage over time. This filter out noise and identify the characteristic gas damage can degrade the insulation and, in severe concentrations associated with PD. Machine learning cases, lead to equipment failure, resulting in costly algorithms, including regression models and support downtime and safety risks. vector machines (SVM), were applied to correlate the Traditional PD detection methods often involve offline gas concentrations with PD severity. measurements or invasive techniques, such as the use Experimental Setup: of ultrasonic sensors or high-voltage tests, which are The experimental setup consisted of a test chamber not always suitable for continuous monitoring in simulating the conditions of an air-insulated operational environments. Therefore, an online switchgear. The chamber contained an artificial monitoring system capable of detecting PD in real-time insulation defect, created by introducing a controlled is essential for proactive maintenance and ensuring partial discharge source. The system was tested under the reliability of electrical systems. various conditions, including different PD levels and Previous research has identified that certain gases are operating voltages, to evaluate its sensitivity and released during PD events, such as acetylene (C2H2), accuracy. methane (CH4), and ethylene (C2H4), which can serve In-field testing was conducted on several AIS units as indicators of insulation degradation. This study located at substations to assess the practical explores the use of these characteristic gases for online performance of the system. Gas samples were monitoring of PD in air switchgear. The detection of collected and analyzed in real-time, while the these gases can provide early warnings of insulation switchgear was in operation, to identify any changes in defects, allowing for timely intervention and gas concentration indicative of PD. preventing catastrophic failures. Gas Selection and PD Characterization: This paper presents a method for the online monitoring of PD in air switchgear based on The target gases for PD monitoring were selected characteristic gases. The research focuses on based on previous studies that identified specific gases developing a gas detection system that can identify generated during PD in air-insulated switchgear: and quantify these gases, offering an effective and • Acetylene (C2H2): This gas is commonly non-invasive solution for real-time monitoring of associated with PD and is an indicator of high-energy insulation health in AIS. discharges, often linked to insulation defects. METHODS • Methane (CH4): Methane is typically produced Gas Detection System Design: during low-energy PD events and is a reliable marker of early-stage insulation degradation. The gas detection system was designed to identify and quantify gases produced by PD events in air • Ethylene (C2H4): Ethylene is generated during switchgear. The system incorporated several key partial discharge and is another important gas used to components: characterize the severity of insulation defects. 1. Gas Sensors: Electrochemical and metal oxide T