Data-driven Modelling

COOLER at Stanford

To enable low-carbon, electrified community energy systems using Stanford campus as a real-life testbed.

AMiDine in the UK

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.

Quantifying Uncertainty in Aggregate Energy Flexibility of Building Clusters

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.

MPC of Variable-speed ACs for Demand Response in Smart Grids

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.

MPC of Floor Heating Systems in Denmark

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.