“Can I Pay You to Take My Excess Energy…Please”
In a stunning event last month (at least, to me), Ontario had to pay Quebec and the US more than $1.5M to have them take excess energy that was produced. The extreme “warm” weather was blamed for the over-production and reduced demand of energy in Ontario. Really, what are we doing? This $1.5M of our tax payer’s money could have been put to better use in education, healthcare, or even energy reform.
Clearly, once again, this demonstrates that the system is broken; both the supply and the demand side. Why was the system not able to anticipate the change in consumption? Consequently, why was the production of energy not adjusted to take this reduction into consideration and thus only produce what we actually need?
You would think that all the information one needs to make such decisions is readily available. There is weather information (we knew it would warm up); there is consumption and demand information (we have trending data of the buildings and others that use energy—at least, so you’d think); aren’t there analytics out there smart enough to see the correlation and trigger a signal to the producers of energy? Of course there are.
Surely, this is a topic that warrants many conversations—so let’s just focus on the demand side. The buildings that we build and occupy consume their fair share of energy, more than 40% of all consumption to be precise. They’re also known to be not effective in optimizing its energy performance. It won’t be the first time that we seen baseboard heaters trying to heat up a space while at the same time air-conditioning systems are trying to balance it out in order to make for a comfortable environment. This (among much other inefficiency) is proving to waste 20% to 30% of our energy in buildings. Now, if we would like to control this, we need to monitor it 24/7, thus measure it in real-time, and consequently we will need to have ubiquitous access to energy and usage information in our buildings.
Convergence and integration allows us to tap into the wealth of information that is currently being stored in disparate systems that make our buildings work. Once we have consistent access to all this information (regardless of its source and regardless of its protocols) we can add analytics to the opportunity in front of us. It is this intelligence that makes our buildings smarter and more dynamic part of its environment. Building information can correlate with data from the weather channel as well as real-time utilization data. Combined, we can add policy to our built environment that will automatically optimize the energy performance and productivity of the building and the people and systems in it.
Turn lights off if nobody is using the space and adjust the thermostat accordingly. Lower blinds if the sun glares into a floor and results air-conditioning to work overtime. Optimize lighting levels based on day-light harvesting and the appropriate temperature levels based on occupant preferences. Inform the users of the space of their individual contribution to the buildings’ energy consumption and consequently trigger behavioral change that will even further reduce the energy demand. All this and more can be reactive as well as pro-active. Predictive modeling can actually recommend environmental settings that will even further drive optimization in the built environment.
All this, and much more is possible if people, systems, and devices become connected over one open and common infrastructure: the building information network, or the ‘fourth utility’. Let’s have them all speak the same language and give them the ability to interact with one another as they collectively contribute to the optimization and productivity of our spaces.
Now, how does this resolve the problem that Ontario faced last month: having to “beg” our neighboring provinces and country to buy our excess energy? Well…simple: you make the demand side of the equation smart enough that it can intelligently inform the supply side as to when and how much energy needs to be delivered to meet its performance requirements. The capabilities and technologies that enable this two-way communication are largely available today. Then, what is it that prevents this from happening?
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Smart Grid technologies could help too.