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Set it and Forget it with Demand Response for TOU Rates

By Crystal Leaver on

Working from Home

More utilities are offering time of use (TOU) rates, but these new rate structures can leave customers confused and frustrated–especially if they result in a higher bill. These rates can even backfire on the utility, causing an average 10% drop in customer satisfaction with utility price. 

Most concerning is that TOU rates can fail to do that they are intended to do–shift load to a non-peak demand time. Customer behavior doesn’t go as planned and many need more help to understand and to act on their new rate. 

Many energy providers are already using demand response (DR) to shift load during high demand using customers’ smart thermostats. The same technology can also provide an effortless way for customers to optimize their energy usage with their TOU rate, without having to remember complicated rate time schedules.

With DR, energy rates can be automatically programmed and managed via smart thermostats, significantly lessening the need for individual intervention. For example, smart thermostats have the potential to shift load significantly by better controlling heating and cooling.

How does TOU Optimization work exactly? Once the customer installs their smart thermostat, it can run an optimization algorithm to simultaneously manage the rate and a customer’s comfort preferences, removing the need for the customer to directly configure their thermostat schedule or make additional behavioral changes. And algorithms can accommodate other loads and energy sources for co-optimization, such as water heating, electric vehicle charging or solar panels, to improve customers’ ability to manage their energy use and bill. These expanded capabilities can make TOU rates easier to benefit from, leading to increased adoption and customer satisfaction – a true win-win for customers and utilities alike.

TOU Optimization can be an effective piece of a program that empathizes, educates, and empowers customers to save energy. Download the eBook to learn more about how TOU Optimization with DR.


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