1. Evaluating the Impact of Data Availability on Machine Learning-augmented MPC for a Building Energy Management System
- Author
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Engel, Jens, Schmitt, Thomas, Rodemann, Tobias, and Adamy, Jürgen
- Subjects
Electrical Engineering and Systems Science - Systems and Control - Abstract
A major challenge in the development of Model Predictive Control (MPC)-based energy management systems (EMSs) for buildings is the availability of an accurate model. One approach to address this is to augment an existing gray-box model with data-driven residual estimators. The efficacy of such estimators, and hence the performance of the EMS, relies on the availability of sufficient and suitable training data. In this work, we evaluate how different data availability scenarios affect estimator and controller performance. To do this, we perform software-in-the-loop (SiL) simulation with a physics-based digital twin using real measurement data. Simulation results show that acceptable estimation and control performance can already be achieved with limited available data, and we confirm that leveraging historical data for pretraining boosts efficacy., Comment: 5 pages, 4 figures. To be published in 2024 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE) proceedings
- Published
- 2024