In real estate, “location, location, location” is a common mantra. In energy and technology, some could make a case for “timing, timing, timing.” Timing for energy refers to the timing and balance of supply and demand, especially with increasing renewables. Timing for technology centers around getting timing right for the ecosystem of products to work in a functional and convenient way. 

Many of us know the evolution of the smartphone, which began with basic text messages and mobile email capabilities on Nokia phones (remember T9 predictive text?), then evolved to personal digital assistants with touch screens on PalmPilots and Blackberry devices. Next, the iPhone pulled together features that helped it become useful in both personal and professional life (who knew that we wanted a camera that could also make phone calls and browse TikTok?). Certainly, Steve Jobs takes the headlines in this story, but it took an ecosystem of sleek hardware, communications capabilities and a convenient user interface to scale to the billions of people that have not only transitioned from mobile phones to smartphones but away from connected LAN lines to connected mobile functions — no matter where they go. The point being an iPhone or Android smartphone wouldn’t be as ubiquitous today if these devices didn’t have just one of the following: functionality at the right price, a fast communications network and user acceptance of apps, etc.

The ecosystem of energy technologies for smart homes has never been stronger. 

  • The vast majority of homes (90% according to Pew Research) now have broadband access, which enables a convenient way to connect devices from anywhere in the home and access them from anywhere there’s a Wi-Fi connection. 
  • Smart devices from thermostats to smart speakers are increasing in popularity. (Statista expects adoption to almost double from 32.2% in 2020 to reach 56.9% by 2025). 
  • Coordination of these devices has started and is only going to expand more. Most smart home platforms have options to set routines/scenes between multiple devices and voice automation makes it easy for consumers to initiate controls and settings. 
  • Access to real-time data combined with machine learning algorithms help to engage consumers with relevant insights for comfort, convenience and conservation.

Each of these is important, but the clincher is utilities need to tap into the demand side to align with the supply side that is increasingly made up of clean/renewable energy. Dynamic utility rates and demand-side management programs increasingly provide the consumer incentive to manage energy consumption. Smart devices help make that easy. It just takes a swipe of a finger to turn off an air conditioner with a smart thermostat or sometimes the utility controls it for you. 

The next iteration, which is right around the corner, is coordination between multiple smart devices to help utilities manage demand while reducing any sacrifice of comfort or convenience for consumers. For example, using an air conditioner, water heater, clothes dryer and EV charger at one time can total more than 15 kW of instantaneous demand. However, there is rarely a consumer need to use all of that energy at once. Air conditioning may be important when it’s hot out, and a water heater usually has enough stored hot water to support household needs once or twice before reheating. Plus, unless the EV battery is drained and at home on a hot afternoon, charging can usually wait until later that evening. Some days or nights, a utility might actually want to increase demand because excess solar or wind energy have made their way onto the grid. 

Of course, these changes may happen from minute to minute each day. Identifying the aggregate demand of a home with real-time energy data can help inform the best way to coordinate the appliances to create a flexible load. Not only will this help reduce demand on peak days, but it can also fill energy gaps from excess supply for a more balanced grid on a daily basis. 

All said and done, as the electric grid gets even more complex while consumer preferences around the energy-driven smart home evolve, it pays to simplify where you can. The importance of time when balancing supply and demand will only increase. But very few consumers will spend every minute looking at that balance. Using technology that is available today, such as machine learning, to deliver personalized notifications and automate energy demand with connected devices based on real-time energy data can help achieve simplicity while continuing to deliver on the lofty goals of providing safe, reliable, affordable and increasingly clean energy.