District cooling system control for providing regulation services based on safe reinforcement learning with barrier functions

• Published in: Applied energy Vol. 347; p. 121396
• Main Authors: Yu, Peipei, Zhang, Hongcai, Song, Yonghua
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.10.2023
• Subjects: Control barrier function; control methods; District cooling system; dynamic models; energy; energy use and consumption; Frequency regulation service; Safe deep reinforcement learning; temperature; District cooling system; Safe deep reinforcement learning; Frequency regulation service; Control barrier function

Thermostatically controlled loads (TCLs) in buildings are ideal resources to provide regulation services for power systems. As large-scale and centralized TCLs with high efficiency and large regulation capacity, district cooling systems (DCSs) have attracted great research attention for minimizing e...