Appliance manufacturers are moving beyond energy pain points to energy collisions. Utility-based energy standards are stuck on energy pain. Energy collisions can offer much more benefits to smart grids than can pain points; they can offer still more to the off-grid or near grid building. Collisions are part of a wide variety of autonomous energy behaviors we will see in the near future—if only the energy suppliers will stop blocking them.
Too many energy suppliers are stuck on models of direct control. When they accept using prices, they want to use them to create direct control. (There is a name for this in Economics—drop me a line or comment if you know what it is…). To use a cartoon version of this approach, if I knew that when the yellow light comes on, I will be charged $1000 / minute to run the air conditioning, that yellow light is as good as an on / off switch. This mechanistic approach, seeking only for the right price that will achieve direct control, will not get any better results than the direct control of the 1980’s
The appliance manufacturers have a more engaging vision, in which they can compete as to how well they engage the consumer in better energy decisions. Most appliances can run in high and in low energy modes. The low energy mode may use half the energy but take three times as long. If time is money, this approach asks the question, “But how much?” Do you want that shirt clean and ready in 30 minutes [high energy mode]? Is it OK if it takes 90 minutes [low energy mode]? Is it OK to wait for 10 minutes until the energy price drops? How about 45 minutes? How about seven hours to get the overnight energy prices—or the wind-sourced energy?
The appliance manufacturers know how to do this already. They are starved for information. They want not only information about the price now, but predictions about price in the future. They want to compete on how well they can communicate energy decisions to the consumer.
This model of autonomous response can reach past the relatively low energy appliances. The intelligent thermostat may want to cool more now to in anticipation of higher prices later. The Plug-In Electric Vehicle (PEV) must support the household schedule while deciding when to charge.
There is renewed focus within the autonomous appliance community on energy profiles to support this model. Energy profiles as defined by Open Smart Grid efforts or by ZigBee have a simple model of energy use, low energy mode, turn off mode and ramp time. Building systems and appliances have a more complex mode. That washing machine may use no energy while filling, and then plenty while agitating the clothes. If an appliance understands its own energy profile, it may start filling its tank five minutes before the price drops—and time its final spin to complete before energy prices step up.
And then they began talking about systems working together to avoid energy spikes…
One of the foundational approaches in networking is collision sensing and detection (CSMA/CD) on a shared bus. Nodes on a network can transmit message whenever they want. Each is responsible for detecting when another node is transmitting at the same time, called a collision. When a collision is detected, each node waits a random period of time and then re-transmits. You may recognize this pattern as what humans do in conversation.
Today’s appliance manufacturers are talking about comparing energy profiles avoid the spin cycle and the refrigerator’s compressor cycle from running at the same time. With almost no degradation of performance, these autonomous systems can begin to shape the overall load profile of a building—or of the green neighborhood.
This approach can provide a smoother, more predictable load to the utilities. When combined with price responsiveness. It could produce a very predictable market. It really becomes interesting, however, when it applies to off grid buildings, and something that I call near-grid buildings.
If a building is running on site-generated energy, it has very distinct energy budget. That budget is not merely aggregate energy over 15 minutes, but hard, clear limits on maximum energy use at any moment. That upper limit may be continuously varying as, say, the speed of the wind changes. Continuous autonomous load shaping, based upon detailed energy profiles, may be critical to a distributed energy future.
To get there, we must get beyond price as a proxy for direct control. To paraphrase General Honore, don’t get stuck on pain.