To enable low-carbon, electrified community energy systems using Stanford campus as a real-life testbed.
To devise analytics that link point measurement to whole system to address the increasingly problematic management of electrical load on distribution networks as the UK transitions to a low carbon energy system.
To quantify the uncertainty in the aggregate energy flexibility of residential building clusters using a data-driven stochastic occupancy model that can capture the stochasticity of occupancy patterns.
To directly control the operating frequency of ACs in response to high-granularity electricity price signals, i.e., 5-minute real-time electricity prices,in smart grids using MPC method.
To develop model predictive control for floor heating systems to provide energy flexibiltiy. The proposed MPC can simultaneously consider all the influential variables including weather conditions, occupancy and dynamic electricity prices.