Rupp Carriveau is director of the University of Windsor’s Environmental Energy Institute.
In 2021, more than 4.5 million homes in Texas lost power for several days as operators dealt with gas assets that could not cope with extreme cold weather. Just last month, Texas was in the spotlight again for narrowly avoiding blackouts under intense pressure from a heat wave.
But this isn’t just a problem for Texas. It could come for us in Canada, too.
After 100 years of little change, energy grids are evolving like never before. Wind and solar are taking up increasingly prominent roles, and the intermittent nature of their supply requires that storage is added to the grid in many forms: Flywheels, compressed air and electrochemical batteries are just a handful of examples. Additional strain will also come from the rising connectivity between the electric and gas grids, as electricity is used to drive electrolytic production of hydrogen and other clean fuels.
But moving even faster than these changes are the new demand patterns driven by consumers. Passenger electric vehicles (EVs) are putting new loads on the grid, often in locations where connections cannot yet support it. Long-haul EVs (LHEVs) or “electric big rigs,” which are just beginning to appear, will roll with batteries five to seven times the size of passenger EVs and will also be looking to plug in.
This is to say nothing of the larger electrification movement in all modes of transport and many forms of residential, commercial and industrial heating applications. This rush to energy cleantech is driven by a climate emergency that is progressing quicker than the evolution of the grid or consumer preference.
Meanwhile, the first generation of utility-scale wind and solar renewables is reaching service life limits – in some cases much earlier than expected. As we try to maintain, replace and expand clean energy generation, inflation has added significantly to development price tags. Compounding this is a climate emergency that is exposing our energy systems to unprecedented weather events not foreseen in the original infrastructure design models.
So how do we design a system that is cost-optimized for sophisticated everyday operation but is also hardened against extreme climate events? We design for resiliency.
Consumers are already helping the grid on their own. EVs plugged in at home can provide backup power to the house, and can also be a storage asset in a neighbourhood microgrid that may also include rooftop solar panels across the street and the local high school’s solar carports.
Commercial and industrial microgrids are on the rise. These installations have the capacity to provide important ancillary services back to the central grid – helping prop up slumping power supply during high demand to avoid service interruptions. These types of interactions between central and distributed microgrids require detailed co-ordination – something called interoperability. This ability to better distribute power to places and times when it’s needed can increase central grid flexibility and reliability.
“All models are wrong, but some are useful,” is what statistician George Box said. The increasing complexity of the grid is making the job of modelling it more challenging. Enter the robots. Artificial intelligence has been increasingly leveraged in recent years to help improve modelling of many energy system elements, including energy demand, as well as the health and costs of the assets themselves.
But the scale at which we are deploying any of these tools is not enough. Things need to be ramped up.
Sure, there have been changes to the North American grid that have bumped up energy bills before. However, the current situation is unlike one we’ve ever seen. We are now trying to fuel the most expansive transition in the history of the grid in the most uncharted and daunting operational conditions. This transition won’t be cheap or easy.