Frequency regulation capacity offering of district cooling system: An intrinsic-motivated reinforcement learning method
District cooling system (DCS), a type of large-capacity air conditioning system that supplies
cooling for multiple buildings, is an ideal resource to provide frequency regulation services …
cooling for multiple buildings, is an ideal resource to provide frequency regulation services …
District cooling system control for providing operating reserve based on safe deep reinforcement learning
Heating, ventilation, and air conditioning (HVAC) systems are well proved to be capable to
provide operating reserve for power systems. As a type of large-capacity and energy …
provide operating reserve for power systems. As a type of large-capacity and energy …
District cooling system control for providing regulation services based on safe reinforcement learning with barrier functions
Thermostatically controlled loads (TCLs) in buildings are ideal resources to provide
regulation services for power systems. As large-scale and centralized TCLs with high …
regulation services for power systems. As large-scale and centralized TCLs with high …
Adaptive Tie-Line Power Smoothing With Renewable Generation Based on Risk-Aware Reinforcement Learning
The district cooling system (DCS) is a promising resource to smooth tie-line power
fluctuations in a grid-connected microgrid with high-penetration renewable generation …
fluctuations in a grid-connected microgrid with high-penetration renewable generation …
Optimal frequency regulation based on characterizing the air conditioning cluster by online deep learning
The air conditioning cluster (ACC) is a potential candidate to provide frequency regulation
reserves. However, the effective assessment of the ACC willing reserve capacity is often an …
reserves. However, the effective assessment of the ACC willing reserve capacity is often an …
Predictive control optimization of chiller plants based on deep reinforcement learning
K He, Q Fu, Y Lu, Y Wang, J Luo, H Wu… - Journal of Building …, 2023 - Elsevier
The energy consumption of HVAC systems is enormous, with chiller plants accounting for
more than 50% of it. To improve energy efficiency, chiller systems are typically optimized at …
more than 50% of it. To improve energy efficiency, chiller systems are typically optimized at …
Electricity pricing aware deep reinforcement learning based intelligent hvac control
K Kurte, J Munk, K Amasyali, O Kotevska… - Proceedings of the 1st …, 2020 - dl.acm.org
Recently, deep reinforcement learning (DRL) based intelligent control of Heating,
Ventilation, and Air Conditioning (HVAC) has gained a lot of attention due to DRL's ability to …
Ventilation, and Air Conditioning (HVAC) has gained a lot of attention due to DRL's ability to …
Data Center HVAC Control Harnessing Flexibility Potential via Real-Time Pricing Cost Optimization Using Reinforcement Learning
With increasing electricity prices, cost savings through load shifting are becoming
increasingly important for energy end users. While dynamic pricing encourages customers …
increasingly important for energy end users. While dynamic pricing encourages customers …
A Multi-Agent Deep Constrained Q-Learning Method for Smart Building Energy Management Under Uncertainties
Data-driven energy management with flexible appliances in smart buildings is a key towards
power system operational intelligence. However, the low efficiency of existing deep …
power system operational intelligence. However, the low efficiency of existing deep …
Online microgrid energy management based on safe deep reinforcement learning
Microgrids provide power systems with an effective manner to integrate distributed energy
resources, increase power supply reliability, and reduce operational cost. However …
resources, increase power supply reliability, and reduce operational cost. However …