Data analytics can be effectively leveraged to predict equipment failures and optimize maintenance schedules in a microgrid by identifying patterns and anomalies in the operational data that indicate impending failures. This approach shifts from traditional time-based maintenance to condition-based maintenance, reducing unnecessary maintenance activities and minimizing downtime. The process involves collecting data from various sensors and monitoring devices throughout the microgrid, including data from distributed generation (DG) units, energy storage systems (ESS), transformers, circuit breakers, and protective relays. This data can include parameters such as temperature, voltage, current, vibration, oil levels, and gas concentrations. The collected data is then analyzed using various data analytics tech....
Log in to view the answer
