Solution architecture: Forecast energy and power demand for utilities

Learn how Microsoft Azure can help accurately forecast spikes in demand for energy products and services to give your company a competitive advantage.

This solution is built on the Azure-managed services: Azure Stream Analytics, Event Hubs, Machine Learning Studio, Azure SQL Database and Data Factory. These services run in a high-availability environment that is patched and supported, allowing you to focus on your solution instead of the environment they run in.

Forecast energy and power demand for utilitiesLearn how Microsoft Azure can help accurately forecast spikes in demand for energy products and services to give your company a competitive advantage.Azure Data FactoryEnergy Demand Forecast(SQL)Energy Demand Forecast(Machine Learning)Geography Data(Blob Storage)Power BISample DataRaw event data queue(Event Hubs)Stream Analysis and Data Movement(Stream Analytics)

Implementation guidance

Products/Description Documentation

Azure Stream Analytics

Stream Analytics aggregates energy consumption data in near real-time to write to Power BI.

Event Hubs

Event Hubs ingests raw energy consumption data and passes it on to Stream Analytics.

Machine Learning Studio

Machine Learning forecasts the energy demand of a particular region given the inputs received.

Azure SQL Database

SQL Database stores the prediction results received from Azure Machine Learning. These results are then consumed in the Power BI dashboard.

Data Factory

Data Factory handles orchestration and scheduling of the hourly model retraining.

Power BI visualises energy consumption data from Stream Analytics, as well as predicted energy demand from SQL Database.

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