The term ‘Smart Grid’ means different things to different people. We think of smart grids as electricity grids that use information technology — sensing, communications, automation — to achieve various power systems goals such as reliability, security, minimizing costs, and minimizing environmental impacts. In collaboration with both Prof. Duncan Callaway’s Energy Modeling Analysis and Controls (EMAC) Laboratory and Lawrence Berkeley National Laboratory’s (LBNL) Demand Response Research Center (DRRC), our research in this area has focused on Demand Response (DR) — controlling buildings and appliances to help out the grid.
To reduce the environmental impact of electricity generation, many states and countries have proposed Renewable Portfolio Standards that require a certain percentage of electricity to be produced from renewables. Unlike traditional power plants, some renewable technologies such as wind and solar photovoltaics produce intermittent power, which is hard to predict and may not be available when customers need it. One way to solve this problem is to shift energy consumption to periods of high electricity production and away from periods of low production. Our work has focused on developing modeling, state estimation, and control strategies that allows us to intelligently control aggregations of residential appliances to balance short timescale (seconds to minutes) intermittency from renewables.