Encouraging thermostatically controlled loads to provide frequency regulation for smart grid: A comfort-level trading mechanism

Abstract

This paper presents a comfort-level trading mechanism for thermostatically controlled loads (TCLs), aiming to incentivize customers to provide more frequency regulation service for smart grid. This mechanism firstly divides aggregators composed of TCLs into the leader layer and the follower layer according to comfort adjustment level produced by the fuzzy neural network controller (FNC). The aggregator at leader layer has a low regulation level, while aggregators at follower layer are high. Then we establish a Stackelberg game between leader layer and follower layer, which can optimize the customer utility. Meanwhile, we build a noncooperative game model among aggregators at follower layer, which can maximize the customer utility while supplying regulation capacity for leader layer. Finally, simulation results validate the effectiveness of FNC and the feasibility of trading mechanism. The FNC can improve tracking accuracy to 2.05%, reduce absolute tracking error to 208.4 kW, and decrease average switching times to 9 per hour. The trading mechanism can make the temperature setpoints of aggregators within their comfort range and improve the customer satisfaction.