POWER FACTOR CORRECTION BASED ON MACHINE LEARNING FOR ELECTRICAL DISTRIBUTION SYSTEMS

摘要

The disclosed embodiments relate to a system that performs power factor correction in an electrical distribution system. During operation, the system receives electrical usage data specifying both reactive and resistive loads from a set of smart meters, wherein each smart meter in the set gathers electrical usage data from a customer location in the electrical distribution system. The system also receives weather forecast data for a region served by the electrical distribution system. The system then feeds the electrical usage data and the weather forecast data into a machine-learning model, which was previously trained on historic electrical usage data and historic weather data, to generate predictions for reactive and resistive loads in the electrical distribution system. Finally, the system adjusts capacitive elements in distribution feeds of the electrical distribution system based on the predicted reactive and resistive loads to maintain near-unity power factors for customers of the electrical distribution system.