Adaptive prediction model accuracy in the control of residential energy resources

Abstract

Abstract-With the increasing use of distributed energy resources and intelligence in the electricity infrastructure, the possibilities for minimizing costs of household energy consumption increase. Technology is moving toward a situation in which automated energy management systems could control domestic energy generation, storage, and consumption. In previous work we have proposed a controller based on model predictive control for controlling an individual household using a micro combined heat and power plant in combination with heat and electricity storages. Although the controller provides adequate performance in computer simulations, the computational time required to determine which actions to take can be significant, due to the precise predictions made over a long prediction horizon. In this paper we propose to make the computations less time consuming by coarsening the quality of the predictions made over the prediction horizon by decreasing their time resolution. In simulation studies we illustrate the performance of the proposed approach.

Modular model building for vehicular traffic systems with macroscopic dynamics*

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Conception and Validation of Smart Building Energy Management System BEMS Using the Discrete Event System Specification DEVS

“…Most recent developments in BEMSs use the concept of predictive control. This control uses a model with measured data in order to predict the strategy of the optimal control of implementation [13]. The predictive control is used, an error of forecasting short-term (10-20 min) or long term (one day) to control the temperature or the humidity.…”

Predictive control for reliable microgrid energy management under uncertainties

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