Distributed Consensus-Based Model Predictive Control of Inverter Air Conditioners for Voltage Regulation in Distribution Systems

Distribution system voltage violation problems are receiving more attention due to the high penetration of fluctuating distributed renewable energies. With the development of Internet of Things technologies, demand response is becoming promising to stabilize the distribution system voltage with local demand-side resources. Inverter air conditioners (IACs) account for a large share in demand-side power consumption, which has been widely considered as appropriate resources to provide voltage regulation services for the distribution system by temporally adjusting the power consumption. However, it remains a challenge to schedule large-scale distributed IACs to participate in voltage regulation services considering their complex operation characteristics with both active and reactive powers. To address this problem, this paper proposes a distributed consensus-based model predictive control (DCMPC) algorithm to coordinate the active and reactive power of IACs to participate in voltage regulation. Distributed consensus-based processing allows the IACs to be appropriately scheduled to respond to the regulation signals. The proposed DCMPC algorithm is validated by the realistic IACs aggregated regulation system and hardware-in-the-loop experiments. The experimental results show that the DCMPC algorithm can effectively schedule IACs to keep the voltage operating within the security range and achieve good thermal comfort for customers during voltage regulation.