Research

PhD Research Topic

Decentralized Coordination of Inverter Air-Conditioners for Virtual Energy Storage

The integration of intermittent renewable energy sources, such as solar and wind, poses significant challenges for modern power grids due to the unpredictable, time-varying nature of their generation. Mitigating the intermittency of renewables typically requires energy storage solutions, such as batteries, flywheels, or pumped hydro systems, which are often constrained by high capital costs, geographic limitations, and, in some cases, environmental hazards.
An alternative solution that is being intensively researched is Virtual Energy Storage (VES). VES utilizes the flexibility of various electrical loads, such as air conditioners (ACs), water heaters, and refrigeration systems. By using a building's thermal inertia, the power consumption of an AC can be shifted without a noticeable change in occupant comfort. Coordinating a large population of such flexible loads can significantly change aggregate demand, helping the grid manage the intermittency of renewables. Previous studies have mostly focused on ON/OFF ACs common in Western countries. However, inverter ACs are becoming more popular. Unlike their ON/OFF counterparts, inverter ACs use variable-frequency compressors, which present unique control challenges and opportunities for continuous power adjustment. Most coordination strategies for inverter ACs are either centralized or use direct compressor frequency control, which are not suitable for a scalable solution. They also rely heavily on thermal models, which are difficult to obtain.
This research proposal focuses on coordination of inverter air conditioners to provide VES. The primary objective of this proposal is to develop and validate a decentralized coordination architecture to ensure that the aggregate power demand tracks a desired aggregated demand. In a decentralized architecture, a coordinator broadcasts a low-dimensional signal to a collection of ACs. Based on this signal, each AC's local controller independently controls high-level variables, such as temperature set points or operating bands. The local controller maintains the user's Quality of Service (QoS) by keeping indoor temperatures within comfortable bounds.