Delivering affordable clean energy to consumers

There are several examples of major electricity providers that are beginning to test programs with some of the characteristics we are describing. PG&E, a large provider in the Pacific Northwest has a Smart Thermostat program (SmartAC), which allows PG&E, the utility, to adjust residential thermostat settings during peak hours. Similarly, Duke Energy’s Power Manager program allows Duke Energy to adjust residential thermostats.

Burkhardt et al. (2023) use some of the data from the same experiment run by Pecan Street, but they do not evaluate the NEST group, include a survey, or run a decarbonization simulation, as they focus on estimating the impact of information and pricing treatments.

The consumer survey results revealed a positive coefficient of conservative (vs. liberal) ideology for WTP, which contrasts with prior political ideology findings. Two factors could help with the interpretation of these results. First, conservatives more strongly endorse the free market (Jost et al., 2003) that encourages and values providers’ initiative, entrepreneurship, and market orientation. Since the development of smart technologies such as NEST, personalized customer feedback, and automation can be tied to firms’ customer orientation and initiative in consumers’ minds, conservatives’ higher WTP for these offerings could reflect their perception and appreciation of firms that create these offerings. It may not necessarily reflect their greater interest in actually procuring and consuming these offerings themselves, as evidenced by the lack of a similar positive effect of conservative ideology on willingness to opt in to these offerings (the coefficient of ideology was negative for NEST and automated solution, and it was non-significant for personalized feedback). It will be interesting to delve deeper into the role of segment characteristics such as political ideology in determining the effectiveness of various 4 P components in driving clean energy adoption.

We drop negative electricity use and use above 10 kWh/minute.

Our triple differences include the critical peak days relative to non-critical peak days, the critical peaks hours during the treatment period (4PM-7PM on critical peak days) relative to non-critical peak hours, and the treatment groups relative to the control group.

Note, the supply curve represents fossil fuel supply and does not include wind or solar.

ERCOT fossil fuel capacity was 96,730 MW in 2020.