Report
On-line model predictive control of battery charging for a household with PV production
Center for Electric Power and Energy, Centers, Technical University of Denmark1
Energy Analytics and Markets, Center for Electric Power and Energy, Centers, Technical University of Denmark2
Department of Electrical Engineering, Technical University of Denmark3
Dynamical Systems, Department of Applied Mathematics and Computer Science, Technical University of Denmark4
Department of Applied Mathematics and Computer Science, Technical University of Denmark5
For the BIPVT-E projects1 an on-line smart control of the battery charging was designed. This report describes the steps taken in order to make this control run in real time. In addition, we will evaluate the quality of the designed mechanism, and highlight future research areas. The online model based control of the battery charging and discharging relies on the immediate and automatic availability of measurements.
Section 2 outlines the setup and components used in this project for ensuring this continuous flow of data. The measurements are used to predict the electricity production and consumption of the system, and update our model parameters. First, Chapter 3 discusses the method used to develop forecasting models, by introducing the general model type and model evaluation procedures.
Thereafter, the fitted forecasting models are presented and analyzed in Section 4 and 5. Finally, in Section 6, we discuss how the forecasts of electricity production and consumption are used in a model predictive control (MPC) setting. Combining our forecasts with externally obtained electricity pricing forecasts, we obtain an optimal charging and discharging schedule for a number of hours ahead.
Language: | English |
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Publisher: | Technical University of Denmark |
Year: | 2021 |
Series: | Dtu Compute Technical Report-2021 |
ISSN: | 16012321 |
Types: | Report |
ORCIDs: | Frölke, Linde and Bacher, Peder |