PROACTIVE ENERGY MANAGEMENT FOR NEXT-GENERATION BUILDING SYSTEMS

We present a proactive energy management framework that integrates predictive dynamic building models and day-ahead forecasts of disturbances affecting efficiency and costs. This enables an efficient management of re- sources and an accurate prediction of the daily electricity demand profile. The strategy is based on the on-line solu- tion of mixed-integer nonlinear programming problems. The framework is able to integrate forecasts of weather conditions, fuel prices, heat gains, and utility demands. We claim that a large adoption level of this proactive tech- nology can improve the predictability of the overall elec- tricity demand at high-level power grid operations.

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