LAUSR

Abstract Rising peak demand is a major cause for high emissions from the electricity sector. In this study, we investigate how different combinations of distributed energy technologies affect peak grid load, energy consumption from the grid, and emissions in the residential sector under time-varying prices. To do so, we develop an optimization framework in which households with varied amalgamations of distributed energy technologies minimize electricity costs, amortized capital, and operational costs over a year, with marginally increasing penalties for deviating from room temperature set-points. The four technologies we consider are: solar panels, lithium-ion batteries, ice cold thermal energy storage, and smart thermostats. The study also incorporates a one-parameter thermal model of the home, so that the discomfort penalties can apply to the room temperature rather than the total appliance load. Based on empirical energy consumption profiles and solar generation data from 25 homes in Austin, we find that residential customers would keep overall annual expenditure and environmental footprint low by investing in solar panels and smart thermostats. The capital costs of both storage systems are still too high to make them economically profitable investments for typical residential customers. Additionally, the Value of Solar policy disincentivizes solar customer investment in storage systems. The study also shows that, while the energetic effect of the two storage systems can be favorable or detrimental depending upon the pricing structure and the household load profile, lithium-ion batteries are the main instruments to avoid high demand charges. Thus, we recommend that, as an effective peak load control mechanism, electric utilities should offer significant rebates to encourage residential customer investment in storage systems in addition to subjecting them to demand charges.