Cost‐effective control strategy for thermostatically controlled loads based on tracking differentiator in smart grid. Issue 24 (14th November 2019)

• Record Type: Journal Article
• Authors: Ma, Kai; Dong, Yaoyao; Liu, Shihao; Wang, Huaibao; Yang, Jie; Zhang, Dongli
• Is Part Of: IET generation, transmission & distribution. Volume 13:Issue 24(2019)
• Page Start: 5569
• Page End: 5576
• Publication Date: 2019-11-14
• Subjects: mean square error methods -- optimisation -- power consumption -- power distribution control -- smart power grids -- minimisation -- load regulation -- power generation control -- thermostats -- control system synthesis; weighting coefficient -- tracking error -- TCLs -- cost‐effective control strategy -- thermostatically controlled loads -- tracking differentiator -- smart grid -- automatic generation control signal -- temperature setpoint -- costs minimisation problem -- demand‐side energy management -- supply -- tracking‐differentiator -- costs optimisation -- root‐mean‐square error; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2018.5848
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : In this study, the thermostatically controlled loads (TCLs) are employed to track automatic generation control signal through changing the temperature setpoint offset in smart grid. The costs minimisation problem is formulated for the power company in demand‐side energy management. The costs are caused by the imbalance of supply and demand and consumer discomfort, which achieve a tradeoff by using a weighting coefficient. The forward method and the tracking‐differentiator are applied to achieve the costs optimisation. In the simulation, the root‐mean‐square error (RMSE) and the costs are measured by changing the weighting coefficient. Simulation results demonstrate that the RMSE and the costs of the power company are increased with the weighting coefficient and the tracking error can be reduced. Further, the impact of dividing TCLs into clusters on RMSE and costs is considered. It is shown that the RMSE and the costs are increased with the number of groups.