[HTML][HTML] A taxonomy of machine learning applications for virtual power plants and home/building energy management systems
A Virtual power plant is defined as an information and communications technology system
with the following primary functionalities: enhancing renewable power generation …
with the following primary functionalities: enhancing renewable power generation …
Achieving better indoor air quality with IoT systems for future buildings: Opportunities and challenges
With the development of IoT technology and low-cost indoor air quality (IAQ) sensors, the IoT-
based IAQ monitoring platform has garnered significant research interest and demonstrated …
based IAQ monitoring platform has garnered significant research interest and demonstrated …
Deep reinforcement learning optimal control strategy for temperature setpoint real-time reset in multi-zone building HVAC system
X Fang, G Gong, G Li, L Chun, P Peng, W Li… - Applied Thermal …, 2022 - Elsevier
Determining a proper trade-off between energy consumption and indoor thermal comfort is
important for HVAC system control. Deep Q-learning (DQN) based multi-objective optimal …
important for HVAC system control. Deep Q-learning (DQN) based multi-objective optimal …
Multi-agent deep reinforcement learning optimization framework for building energy system with renewable energy
R Shen, S Zhong, X Wen, Q An, R Zheng, Y Li, J Zhao - Applied Energy, 2022 - Elsevier
Under the background of high global building energy consumption, meeting the ever-
growing energy consumption demand of building energy system (BES) through renewable …
growing energy consumption demand of building energy system (BES) through renewable …
Cross temporal-spatial transferability investigation of deep reinforcement learning control strategy in the building HVAC system level
X Fang, G Gong, G Li, L Chun, P Peng, W Li, X Shi - Energy, 2023 - Elsevier
Abstract Model free based DRL control strategies have achieved positive effects on the
HVAC system optimal control. However, developing deep reinforcement learning (DRL) …
HVAC system optimal control. However, developing deep reinforcement learning (DRL) …
Comparison of reinforcement learning and model predictive control for building energy system optimization
Advanced controls could enhance buildings' energy efficiency and operational flexibility
while guaranteeing the indoor comfort. The control performance of reinforcement learning …
while guaranteeing the indoor comfort. The control performance of reinforcement learning …
[HTML][HTML] Evaluation of advanced control strategies for building energy systems
Advanced building control strategies like model predictive control and reinforcement
learning can consider forecasts for weather, occupancy, and energy prices. Combined with …
learning can consider forecasts for weather, occupancy, and energy prices. Combined with …
Data-driven stochastic energy management of multi energy system using deep reinforcement learning
Y Zhou, Z Ma, J Zhang, S Zou - Energy, 2022 - Elsevier
The multi energy system (MES) is promising in the process of carbon neutrality, such that
multi energy resources are utilized comprehensively to reduce the operation cost. Another …
multi energy resources are utilized comprehensively to reduce the operation cost. Another …
Dynamics analysis of a novel hybrid deep clustering for unsupervised learning by reinforcement of multi-agent to energy saving in intelligent buildings
The heating, ventilating and air conditioning (HVAC) systems energy demand can be
reduced by manipulating indoor conditions within the comfort range, which relates to control …
reduced by manipulating indoor conditions within the comfort range, which relates to control …
A zoned group control of indoor temperature based on MPC for a space heating building
The traditional regulation of district heating (DH) system are mainly based on the central
control in heat plants and/or in the substations. But the end-user control is becoming …
control in heat plants and/or in the substations. But the end-user control is becoming …