Many cities and communities are thinking of enrolling all their electric accounts (municipal, residential, commercial) in renewable energy sources with the goal to get to 100% renewable. From all available data it looks as if the best time to implement such programs and recruit participants is at roll out. Once the program is up and running and power has been purchased via medium and long term contracts, it’s not so easy to make that transition to 100% renewable.
Existing Community Choice Aggregation programs (CCAs) striving for a 100% renewable product have options for customers to enroll in by “opting up” for a small premium (usually about $0.01/kWh) but so far the opt up rates have been small – generally about 2-3%. Marin Clean Energy is doing a bit better because they have convinced most of their municipal customers to opt up. MCE’s opt up rate is about 5%.
The reason many customers don’t opt up is because of inertia. And because it’s so time consuming to get customers to opt up, most CCAs invest very little time and energy on getting people to opt up. On the other hand, when a big commercial account has made a commitment to clean energy, the programs will work with them to get them to the 100% renewable product. This has been the case with Facebook and Salesforce.
Is there a better way? Perhaps by creating an app that was offered to all CCA customers that might give them an easy way to review their energy consumption (and cost) for example, which could also embed an “opt up” element that would simply require them to click on a single link or icon to allow them to enroll. It seems likely that more people would opt up if they could do so easily from their phones rather than calling the 800 number or going on line.
PV panels already generate electricity, but they also have valuable warm air building up behind them even in winter. Make a low cost controller that can activate a fan to harvest that warm air whenever it’s warmer than it’s destination. Might perform a function similar to differential thermostats that control solar water heating system pumps.
To enable electrification of different end uses without requiring main service line upsizing, make a controller that coordinates competing new electric devices in a home ( 20 Amp water heater, 20 Amp space heater, 30 Amp electric vehicle charger) so their combined load does not trip a 40 Amp circuit breaker.
The electric grid needs a way to balance loads and resources on a 5 second basis. Make a controller for an electric resistance heater that varies its consumption by up to a factor of 2 to respond in a way that tends to balance the grid. ( could use grid intentional signals or system voltage or system frequency as input signal )
Make a controller that responds to statewide California Independent System Operator, every-15-minute market prices to control electric space heaters or water heaters, or other devices. Download free app “ISO Today” to see the price map tab and its 15 minute market option.
Make a water heater controller that guides a water heater to hit a defined temperature target by a deadline for the lowest cost of energy varying at 15 minute intervals from the ISO Today app. e.g. starting from 90 F at 8 PM, get a 50 gallon, 3-kW-resistance water heater to 120 F by 7 AM with the lowest cost wholesale priced energy in the fluctuating 15 minute market.
Design an interface that lets an EV driver tell their charger how many miles of range they want by 7 AM while minimizing the cost of charging in the 15 minute wholesale market (from ISO Today App) How does it deal with high prices?
Design a thermostat that tells the user what the cost will be for maintaining the set temperature for the next hour, second hour, third, etc. given weather forecast, or other load influence and retail time of use rate schedule. Have it also show the cost of running one degree cooler, etc.
Design a thermostat that lets user tell it they want the most comfort (least discomfort) they can get for the next X hours for a given budget e.g. $D. Thermostat could use weather forecast, learned home heat loss per degree warmer than outside, and retail time of use rates, etc.
Design a thermostat that tracks fuel consumed (run time?) to estimate when user would enter higher cost energy tier consumption. This lets user plan to use all their low cost allowance and minimize use of higher cost tier energy. Could show forecasted bill if temperature settings are held for balance of month remaining.
Design a thermostat that lets user input a “spreadsheet type” of cents per hour values they would be willing to pay to stay above selected temperatures (e.g for 7 AM I’m willing to pay 90 cents/hour to stay above 62 and 105 cents/hour to stay above 66 F. Then when I’m gone at 8 AM I’m willing to pay 25 cents to stay above 55 and 30 cents to stay above 60. At 5 PM I’m willing to pay 75 cents to stay above 65 and 80 cents to stay above 68. The thermostat should integrate forward temperature models including weather, rates, and preferences to optimize cumulative comfort provided per cumulative dollar. Thermostat starts storing heat in the house by preheating in low cost hours to decrease high cost period energy purchases while still providing comfort.