Theme IV - 4.1

Smart building operating strategies for net zero energy homes and small buildings

Project Leader

  • A. Athienitis


Optimal combinations of energy efficient building envelopes, active and passive solar systems and cogeneration systems may be employed to design NZEBs. Generally, residential buildings in cold climates experience two daily peaks in electricity demand during the winter months. These winter peaks usually occur (a) in the early morning, due to space and domestic hot water (DHW) heating (in Québec, for example, both are associated with heat pumps or other forms of electric heating), and (b) in the evening, due to appliances, lighting and DHW. Through optimal control and storage of the energy flows in a NZEB, these peaks can be reduced and shifted in time to reduce utility demand peaks. 

Implementation of solar electric and thermal systems, or BIPV and BIPV/T systems may result in a net electricity supply to the grid for several hours around solar noon, particularly when passive solar gains satisfy daytime space heating needs. The electric grid is currently not designed for high penetration rates of unpredictable renewable energy sources. Research is underway by institutes around the world to develop smart grids that will communicate with building systems to adjust their power demand; however, there is a need for smart building systems that will communicate with a smart grid to optimize electricity flows from/to NZEBs (Holmberg & Bushby, 2009). One step in managing peak electricity supply from/to a solar home is to predict up to a day ahead the approximate electricity demand and generation. 

Solar electricity generation can be relatively well predicted for clear days usually one day before, and clear days are the most important because this is when the maximum electricity is produced (Candanedo & Athienitis, 2010; Candanedo et al., 2011). Similarly, peak-heating loads on clear cold nights can be predicted once a building model is developed and calibrated through system identification techniques. 

Through predictive control based on one-day ahead weather forecasting and a combination of passive and active thermal storage, electricity demand associated with space and DHW can be predicted. In addition, the increasing availability of PHEVs in the near future will enable their use for storage of electricity from a house (if the car is at home during daytime) and feeding back electricity to the house as needed (e.g. emergency power). 

This project will follow an integrated approach to net-zero energy home design and operation. Optimized net-zero energy buildings need to be designed based on anticipated operation so as to have a largely predictable and manageable impact on the grid. Smart buildings optimally linked with smart grids will enable a dramatic reduction in the need to build new power plants. 

This project aims to develop operating strategies to reduce and shift the peak net electricity supplied to or drawn from the grid in a largely predictable manner for optimally designed net-zero energy homes. It is expected that the strategies, with some modification will also be applicable to small commercial buildings. Optimal control of solar buildings based on weather forecasts and predicted loads will contribute to improving the performance of the mechanical system and to enhancing thermal comfort (Kummert et al., 2001; Candanedo et al., 2011). Different strategies will be considered such as: 

1. Development of optimal strategies for thermal space control that combine charging/discharging of passive and active thermal storage and link to building design; optimal utilization of solar gains (passive and active) while satisfying comfort requirements. 

2. Study of strategies for reducing demand peaks due to appliances. 

3. Development of optimal strategies for utilizing electric/PHEVs as electric storage attached to a solar house (e.g. car at home during the daytime / or part of it) to reduce net electricity supply peaks to the grid, while reducing the peak demand due to lighting and appliances.


  • 4.1a  Development of optimal strategies for model-based supervisory control of a NZE solar home 
  • 4.1b  Strategies for reducing electrical demand due to appliances
  • 4.1c  Electric/PHEV utilization for electrical storage for a solar house


Back to Theme IV : Smart Building Operating Strategies