Storing energy is not cost-effective, so utilities and power generators need to forecast future power consumption so that they can efficiently balance the supply with the demand. During peak hours, short supply can result in power outages. Conversely, too much supply can result in waste of resources. Advanced demand forecasting techniques detail hourly demand and peak hours for a particular day, allowing an energy provider to optimize the power generation process. This report focuses on demand forecasting within the energy sector. The report provides region level energy usage status and forecast of future usage for optimizing the operations.
The ‘Energy Solution Status Summary’ page shows the overall status of energy demand of each region. User can select a single region by clicking the filter on the left to investigate each region's status.
The ‘Energy Solution Forecast’ page shows the demand forecast results from Azure Machine Learning model and different error metrics for user to identify the quality of the model. Temperature and its forecasts are used as a feature in the machine learning model.
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