Energy priority control strategy and reward allocation mechanism for thermostatically controlled loads based on leaky storage model

Abstract

The aggregated thermostatically controlled loads (TCLs) can be used as energy storage to provide various ancillary services for smart grid. This paper presents an energy priority control method and a reward allocation mechanism, which aims to avoid TCLs always concentrating on the temperature boundaries and encourage users to improve adjustment capacity. Firstly, the energy to be charged and the residual energy are determined based on leaky storage model. Then when loads need to be turned on, the loads in the off state will be sorted in descending order according to the energy to be charged. Conversely, when loads need to be turned off, the loads in the on state will be sorted in descending order according to the residual energy. In order to encourage users to increase the temperature adjustment range, the energy provision index (EPI) is defined based on the energy capacity of loads. The simulation results show that this method can improve the tracking accuracy from 4.34% to 0.13% and reduce the switching frequency from 7.1 times per hour to 5.7 times per hour. In addition, with the increase of EPI, the reward of each load will increase, which indicates that this mechanism can improve the regulation ability.