The off-grid solar solutions were targeted to replace expensive diesel generators and provide a greener, cheaper and reliable option. They were also exploring a new commercial model move from capital expenditure to charging for energy consumed.
Three key aspects needed to be addressed for the new commercial model to be successful:
1. Since, remote healthcare units were one of the target customers, accurate forecasting of energy production was critical. Because loss of power means loss of lives
2. Over-engineering the panel size was to making it economically nonviable
3. Poor battery performance was a showstopper to provide reliable product, thus impacting customer satisfaction
How Cerebra solved the problem?
Cerebra ingested the following key parameters every minute from the off-grid solar solution
Ã¯â€šÂ· Solar Panel Parameters – Solar Panel Voltage, Solar Panel Current, Solar Panel Power, Solar Panel Energy
Ã¯â€šÂ· Battery Parameters – Battery Voltage, Battery Current, Battery Power, Battery Energy +ve & -ve
Ã¯â€šÂ· Streaming sensor data such as irradiance sensor and panel temperature sensor
Ã¯â€šÂ· Weather data such as temperature, humidity, and rainfall
Using the raw data, several rich vectors were generated such as Solar Irradiance Efficiency, Discharge Velocity, Survival probability. Arimax Forecasting Algorithms were implemented to forecast accurate energy production. A combination of regression models was implemented to monitor and diagnose asset related health.
Impact on outcome
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