AI for Energy Forecasting

Inaccurate forecasts of annual energy demand results in wastage of energy, supply and demand mismatch, downtime due to unplanned power outages, and overall disruption of a facility.

Zasti proposes to analyze behavior patterns and data sources such as real time data from electricity meters, BAS, utility bills, weather data, benchmarking data from publicly available datasets, and simulated data of HVAC systems. Using artificial neural networks, Zasti forecasts energy consumption. helping to inform power supply and demand.

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