Energy Demand Forecast System for Cities

Background:

We will develop an energy demand forecasting tool that will provide significant advantages over traditional methods, by serving operational, dynamically changing weather and building energy demands for a whole city. Traditional methods often rely either on single weather stations (historical) or single building energy modeling based on climatological inputs, which can prove inadequate during rapidly changing weather events. Due to the coupled nature of the highly heterogeneous urban environment-building envelope system, high resolution weather data can be useful to not only quantify building energy demand for heating and cooling, but also to study load management strategies.

Industry Relevance:

The range of commercial users of this product will be very large and include utilities, building energy managers, and energy traders.

Objectives:

1. Test city scale the energy forecast tool using aggregated energy data from publicly available records.

2. Adapt the city scale forecast tool for single large buildings using local data.

3. Develop a user-friendly interface to deliver the forecasted data to potential users and 4. to demonstrate benefits to selected users based on demand response events prevented.