Design of a model predictive control methodology for integration of retrofitted air‐based PV/T system in school buildings

Abstract

This paper presents a model predictive control (MPC) methodology for integrating air-based photovoltaic/thermal (PV/T) systems in school buildings. The methodology is developed based on a case study for an archetype fully electric school building in Québec, Canada. A data‐driven grey‐box model for the classrooms is calibrated with measured data, and a PV/T model is developed. These models are integrated to apply MPC to the school building using the established dynamic tariffs for morning and evening peaks. Three scenarios are investigated and compared: (1) A reference case without a PV or PV/T system, (2) Integration of a PV system and MPC, and (3) Integration of a PV/T system and MPC under a demand response scenario. Results show that using the MPC with PV/T integration can reduce peak demand by up to 100% during high-demand periods for the grid. This methodology is scalable and can be transferable to other institutional buildings.

Abbreviations: PV: Photovoltaics system; BIPV/T: Building integrated photovoltaic and thermal system; COP: Coefficient of performance; CV-RMSE: Root-mean-square error; DR: Demand response; DSM: Demand-side management; HRV: Heat recovery ventilator; HVAC: Heating ventilation and air conditioning; IEQ: Indoor environmental quality; MPC: Model predictive control; RC model: Resistance-capacitance model; RES: Renewable energy sources

KEYWORDS:

• Model-based predictive control
• PV/T system model
• grey-box model
• energy flexibility
• school building

Acknowledgment

Technical support from Hydro-Québec Laboratoire des Technologies de l’énergie Shawinigan research centre under NSERC/Hydro-Québec Industrial Research Chair is gratefully acknowledged. Also, technical support provided by Regulvar and Centre de services scolaire des Mille-Îles (CSSMI) is acknowledged with thanks. The authors would like to acknowledge the support from the NSERC/Hydro-Québec Industrial Research Chair (‘Optimized operation and energy efficiency: towards high performance buildings’) held by Dr. Athienitis. Navid Morovat would like to acknowledge the financial support received from Fonds de Recherche du Québec – Nature et Technologies (FRQNT) in the form of a Doctoral Research Scholarship (B2X 319748). The comments of our colleagues at CanmetENERGY are gratefully appreciated.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are subject to third party restrictions and were used under license for this study. Data are therefore available from the authors with the permission of the third party.

Additional information

Funding

This work was supported by Fonds de recherche du Québec – Nature et technologies: [Grant Number B2X 319748].