Paper Conference

2020 Building Performance Analysis Conference and SimBuild co-organized by ASHRAE and IBPSA-USA

     

Data-Driven Predictive Control for Commercial Buildings with Multiple Energy Flexibility Sources

Anjukan Kathirgamanathan, Mattia De Rosa, Eleni Mangina, Donal P. Finn
School of Mechanical and Materials Engineering, University College Dublin, Ireland
UCD Energy Institute, O’Brien Centre for Science, University College Dublin, Ireland
School of Computer Science, University College Dublin, Ireland

Abstract: Data-Driven Predictive Control, representing the building as a cyber-physical system, shows promising potential in harnessing energy flexibility for demand side management, where the efforts in developing a physics-based model can be significant. Here, predictive control using random forests is applied in a case study closed-loop simulation of a large office building with multiple energy flexibility sources, thereby testing the suitability of the technique for such buildings. Further, consideration is given to the feature selection and feature engineering process. The results show that the data-driven predictive control, under a dynamic grid signal, is capable of minimising energy consumption or energy cost.
Pages: 9 - 18
Paper:
simbuild2020_C002