The restoration process right after the wake of extreme weather has been a main concern for utilities. The unpredictability of power outages leaves utilities significantly less time to improve power storage along with a substantial amount of operating cost. This ultimately leads to customer dissatisfaction and is a major obstacle.
Predicting Outage uses available meteorological data and other forecasting expertise to develop machine learning predictive models and thus proactively prepares companies beforehand regarding weather anomalies. Thus this enhances electric system reliability and benefits utility customers. With the best arrangements, we are improving the functionality and reliability of the system by generating the most accurate predictions of power outages and better characterizing the confidence of weather forecasts.
Weather Forecast Based Proactive Resource Mobilization to prevent Site Outage Due to Long Term Power Outage. Next Day Weather Forecast Accuracy: 75-80%
Heavy Rainfall and Storm triggers Grid Power Outage and requires telecom sites to run on back up power. For prolonged outage Generator and addition power back up resources needs to be mobilized. Our solution identifies sites prone to high duration outage and informs on ground maintenance teams so that they can get prepared to handle long hour Grid Failure.
1 Year Grid Outage Data + 1 Year Weather Data with Multiple Parameters from public weather souce upto district level
Build Machine Learning Model to Predict Outage Based on Actual Weather Data
Validate Model Against Forecast Data and Actual Outage
Put the System in Practice- Send Predicted Outagelist to on-ground team everyday