Carbon-Aware Demand Response for Residential Smart Buildings

Abstract

The stability and reliability of a smart grid are challenged by the inherent intermittency and unpredictability of renewable energy as its integration into the smart grid increases. This places enormous pressure on the smart grid to manage high loads and volatility. To effectively mitigate the impact of new energy integration on smart grids, demand response (DR) can be altered to the demand-side burdens. Using residential smart buildings (RSBs) in Shanghai, this study proposes a carbon-aware demand response (CADR) model that is predicated on the coordination of power carbon intensity and real-time electricity prices. In order to accomplish a more comprehensive reduction in overall electricity consumption costs, we conducted real-time scheduling of a building’s electrical devices using a greedy algorithm. In addition, a model of an optimal charging and discharging scheme for household electric vehicles was established, which is based on various charging modes, taking into account the electrification of the transportation sector. The cost of EV charging is reduced by an average of 23.18% and 33.2% under the two common charging modes, while the integrated cost of the total annual electricity consumption of household devices is reduced by 8.69%, as indicated by the simulation results.