Demand Response Opportunities with Residential Appliances in Smart Grids

Supply-demand mismatch and demand peaks jeopardize the reliability of power systems and incur severe implications such as huge network investment, increased generation capacity and electricity cost to customers. The increased penetration of renewable energy in future will reduce the carbon footprint, however, their reduced inertia and variable output will make the power system vulnerable to disturbance, further exacerbating the problem by reducing controllability of generators. In the past, demand side management has shown great potential in reducing power mismatch as well as demand peaks. The potential of demand response in peak clipping, valley filling and reducing price volatility is already explored in the literature. Residential appliances such as refrigerators, air-conditioners, hot water systems (EWHs) have large thermal inertia, and therefore represent energy storage opportunities showing great demand response potential. However, increased penetration of renewables as well as high energy consuming residential appliances such as aircons and EWHs bring new challenges to demand response making it meaningful to discover novel demand control strategies. The thesis presents a detailed study of demand control approaches and peak demand drivers as well as their limitations. These are addressed by undertaking a study of centralized and decentralized control system topologies, modelling power network setup with conventional diesel and wind generation, modelling refrigerators as control loads for power balancing, studying large scale residential appliance level data from Australia’s largest network provider, Ausgrid and using the data to investigate major demand drivers in summer and winter demand peaks as well as studying demand response opportunities with them. Contributions of the thesis include introducing a novel hybrid control topology for supply-demand balancing by using domestic refrigerators as control loads in a hybrid power network setup, in addition to analysing Smart Grid Smart City data to study the actual contribution of aircons and other residential appliances. Clustered operational models combined with aircon load control strategies are used to study possible peak load reductions from aircons at the New South Wales state level. Also, winter and summer peak data are studied for many zone substations (ZS) and demand response opportunities with potential controllable loads at the ZS are investigated