Using Technology, Artificial Intelligence, and Economics to Induce Smart Demand Response

One of the most important climate and energy challenges is how to achieve reliable energy access to a broader population without imposing increases in pollution and pressure on the electricity grid. Smart demand response—an approach that uses technology to help consumers to use energy efficiently—is promising to address this challenging problem, but evidence from academic research is still very limited. To address this question, the researchers have recently established a full partnership with Optiwatt, a company that helps consumers to engage in smart charging for electric vehicles (EVs) and smart use of AC (air conditioning) to conduct a series of randomized controlled trials (RCTs). The experiments aim to test how we can use automation, AI, and economic theory to enhance smart use of energy in the context of EV charging and peak-hour electricity usage for AC. The researchers first theoretically show that it is ambiguous which of the three methods (automation, AI, and allocation based on economic theory) best enhances consumer and social welfare. Then, they conduct two field experiments with over 65,000 customers, one for EV and another for smart AC, to empirically test our theoretical predictions. The project is unique in that the researchers have already established partnership with the partner company and developed detailed experimental designs to test their hypothesis.

“We will conduct a series of randomized controlled trials to explore how technology, artificial intelligence, and economics can drive smart demand response and expand energy access to a broader population while minimizing pollution and reducing pressure on the electricity grid.”

Koichiro Ito, Harris School of Public Policy