It is possible to reduce peak electricity consumption to almost nothing in schools and probably in other buildings heated entirely by electricity.
The secret to such an achievement lies in collecting the most precise and varied data possible in order to establish a “predictive model” of the heating needs of the establishment in question.
This was successfully demonstrated by researchers from Concordia and Sherbrooke universities, whose results were presented at the 13th Nordic Symposium on Building Physics, in Denmark, and published last December in the journal “Journal of Physics: Conference Series.”
“Most thermostats that are installed in buildings use what are called reactive controls, which means they react based on current conditions. If it is colder, they will increase the heat,” explains one of the authors of the study, Professor José Candanedo, from the department of civil and building engineering at the University of Sherbrooke.
Use multiple data
The work he carried out with his Concordia colleagues took place at Horizon-du-Lac primary school in Sainte-Marthe-sur-le-Lac. They collected a wealth of data such as weather forecasts, the expected occupancy in the different premises – the human presence having an impact on the temperature of a room – the natural capacity of the thermal envelope of the building, the heating passive solar energy represented by the presence or absence of the sun in order to establish their predictive model. Although it is possible to program thermostats, nothing comes close to the method they have developed.
It is this predictive model which allowed them, for example, during peak periods in extreme cold to start the heating at 2:30 a.m. to bring the temperature to the required comfort level at 6:00 a.m., to close the heating until 9:00 a.m. without causing any loss of comfort and restart it at that time. “By using predictive control, we can prepare in advance, we can start preheating the space and avoid or at least reduce electricity consumption at critical times,” explains the researcher.
A win-win result
However, this is where the benefits are twofold: on the one hand, this type of predictive model extended on a large scale would greatly reduce the pressure on electricity demand. “We often think of energy consumption as being the most important issue, but there is also the power demand, the demand for electricity in kilowatts, which is also important. In Quebec, several buildings use electricity and at certain times of the day, there will be a very high power demand which will contribute to the peak of the Hydro-Québec network,” argues Professor Candanedo.
On the other hand, in a dynamic pricing model where the consumer pays up to 15 times the price per kilowatt/hour during peak periods, the saving is major for the School Service Center which manages several schools. Also, still in terms of savings, continues Mr. Candanedo, “implementing new control strategies is less expensive than installing other equipment. We use systems that are already available. »
Hydro-Québec sets peaks between 6:00 a.m. and 9:00 a.m. in the morning and between 4:00 p.m. and 8:00 p.m. at the end of the day. So it stands to reason that a school can just as easily turn off its heating system at 4:00 p.m. and turn it back on at 8:00 p.m. From there, with the school empty, it can keep the temperature lower and start again the cycle in the middle of the night.
School as a starting point
The predictive model does not eliminate all electricity consumption since there are always needs for security and lighting, for example. “But we can reduce the power demand significantly during the peak period. It is possible to do it in a reasonable way because it allows us not to exceed the limits of comfort and safety of the occupants, which, in the case of schools, is really critical with students, children. »
The choice of a school to develop this predictive model is not by chance, explains José Cantanedo.
“School buildings constitute an interesting case study because they have the potential for scaling and reproducibility. Also, schools offer significant value as a technological showcase.
“The most complicated thing is creating a mathematical model and that takes someone to take care of it. Fortunately, we slowly gain time to automate the creation of models. The challenge is that the buildings are all different. »
Spread the idea
The good news, he says, is that the same model can be applied everywhere. “Our intention is to present solutions that could be deployed or adapted to several types of school buildings and, certainly, if we do it for a school building it could be done with other commercial and institutional buildings. »
And ultimately, he adds, we can also transpose the same principles to the residential sector. “Of course we can do this model in a house, predict when to turn on the heating, stop it,” he says, raising the hope of a consumption methodology that will be a winner both in relieving demand. energy at Hydro-Québec at the peak as well as for the portfolio of all of its customers.