Аңдатпа
The object of the study is the automatic reclosing of 500 kV overhead transmission lines under technological disturbances and weather-related impacts. The problem addressed in the study is the insufficient reliability of conventional fixed-time reclosing algorithms when distinguishing transient faults from permanent faults caused by conductor damage, insulator failure, tower collapse, or severe external influences. The study analyzed emergency outage statistics and automatic reclosing performance in Kazakhstan’s power grids for the first nine months of 2023 and 2024, together with six representative incidents on 500 kV lines. The results showed that emergency outages increased from 193 to 233 cases, while successful automatic reclosing operations rose from 91 to 135 and their share increased from 47.2% to 57.9%. At the same time, unsuccessful reclosing attempts decreased from 102 to 98, and undelivered electricity fell from 666.92 to 274.08 thousand kWh. Natural impacts caused 65.6% of technological disturbances, which explains the need to include weather conditions in reclosing decision-making. The main result of the study is an adaptive fuzzy-logic decision-support model that jointly evaluates electrical indicators, relay protection signals, weather factors, signs of mechanical damage, and the result of the previous reclosing cycle. Its distinctive feature is an interpretable graded assessment of permanent-fault risk with three possible recommendations: allow reclosing, increase the delay, or block reclosing. The proposed model can be used as a supervisory module in relay protection and automation systems of backbone transmission networks, provided that disturbance records, protection data, weather information, and data on line-element damage are available