UC San Diego

Management of demand side resources can play a significant role in enabling renewable energy integration and decarbonizing the electric grid. Plug loads constitute a major portion of energy consumption of commercial buildings. They can be turned off using smart plugs when not in use. Smart plugs can also infer building occupancy from energy consumption measurements of plug loads.Therefore, plug load control can conserve energy and provide load flexibility to the grid for frequency regulation. This work focuses on a distributed control algorithm, distributed approximate Newton algorithm (DANA). DANA uses local information to optimize a network of nodes to track a reference signal using only agent-to-agent communication. Moreover, the power consumption of loads can be used as inputs to the algorithm in the form of box constraints to account for load usage. In this work, DANA is implemented on a real-life system that consists of computers, a TV monitor, and a printer. The objective of this work was to show that DANA could be used on a system of plug loads to track a reference signal while conserving energy. Experimental results show that DANA can be used to switch off idle plug loads to conserve energy. In an office space with high occupancy the DANA implementation reduced energy consumption by 33% over one hour. Including a battery in the system can reduce the average tracking percent error to less that 1% and can therefore be used to provide frequency regulation services.