Electric utilities are increasingly adopting Demand Response (DR) programs and Time-of-Use (TOU) rates to manage peak electricity demand and delay costly infrastructure upgrades. However, these strategies assume that households can shift usage or adopt enabling technologies. Many low-income households lack affordable access to smart thermostats, central air, or flexible schedules, limiting their ability to participate. These structural barriers shape who benefits and who bears the burden, raising core questions of energy justice and equity.

This project examines how DR and TOU program design affects household outcomes in 2 ways. A comparison of incentives offered by Holyoke Gas & Electric (HG&E) and Eversource reveals how both companies incentivize participants using different payout models. HG&E provides small recurring bill credits while Eversource gives a one-time larger payment (primarily including credit for applying to the program).

The second part focuses on using energy meter data collected from multiple census blocks in Holyoke, MA to analyze how different Time of Use (TOU) pricing structures affect households across income levels. Using excel calculations and R modeling, we analyze hourly data from neighborhoods in Holyoke to determine how the impact of TOU pricing varies with income.

Together, these findings demonstrate that DR and TOU policies are not merely technical tools but central equity issues. Fair program design must reflect the living realities of low-income households to ensure that all families benefit from a more resilient energy system.

Carbon capture (CC) is central to U.S. decarbonization strategies, yet its implications for co-pollutants and environmental justice remain uncertain. We evaluate how major federal policy instruments—including the Inflation Reduction Act’s 45Q subsidy, EPA CO₂ performance standards, the Good Neighbor Rule, and a carbon tax—shape investment, dispatch, emissions, and spatially resolved health damages in a networked power system with transmission constraints. Using an optimal power flow capacity-expansion model coupled to atmospheric transport and demographic data for case studies in Alabama and Texas, we show that CC subsidies drive retrofits and increased fossil generation, reducing CO₂ but raising total co-pollutant emissions above business-as-usual levels. Subsidies slightly lower aggregate health damages through sulfur dioxide reductions but perform substantially worse than standards or a carbon tax, which achieve the largest declines in both emissions and damages. Combining a carbon tax with 45Q produces the highest pollution and health burdens. Disparities between demographic groups are small relative to differences across policies. These results demonstrate that CC policy design must account for power-system dynamics and co-pollutant outcomes to achieve equitable decarbonization.