Systematic review on deep reinforcement learning-based energy management for different building types
Owing to the high energy demand of buildings, which accounted for 36% of the global share
in 2020, they are one of the core targets for energy-efficiency research and regulations …
in 2020, they are one of the core targets for energy-efficiency research and regulations …
MERLIN: Multi-agent offline and transfer learning for occupant-centric operation of grid-interactive communities
Building and power generation decarbonization present new challenges in electric grid
reliability as a result of renewable energy source intermittency and increase in grid load …
reliability as a result of renewable energy source intermittency and increase in grid load …
[HTML][HTML] Real-world challenges for multi-agent reinforcement learning in grid-interactive buildings
Building upon prior research that highlighted the need for standardizing environments for
building control research, and inspired by recently introduced challenges for real life …
building control research, and inspired by recently introduced challenges for real life …
A review on simulation platforms for agent-based modeling in electrified transportation
As the use of combustion engine vehicles plays a deciding role in global warming, we can
observe a trend to replace them with electric vehicles (EV) driven by new environmentally …
observe a trend to replace them with electric vehicles (EV) driven by new environmentally …
CityLearn v2: Energy-flexible, resilient, occupant-centric, and carbon-aware management of grid-interactive communities
As more distributed energy resources become part of the demand-side infrastructure,
quantifying their energy flexibility on a community scale is crucial. CityLearn v1 provided an …
quantifying their energy flexibility on a community scale is crucial. CityLearn v1 provided an …
[PDF][PDF] MERLIN: Multi-agent offline and transfer learning for occupant-centric energy flexible operation of grid-interactive communities using smart meter data and …
The decarbonization of buildings presents new challenges for the reliability of the electrical
grid as a result of the intermittency of renewable energy sources and increase in grid load …
grid as a result of the intermittency of renewable energy sources and increase in grid load …
PV-Optimized Heat Pump Control in Multi-Family Buildings Using a Reinforcement Learning Approach
M Bachseitz, M Sheryar, D Schmitt, T Summ, C Trinkl… - Energies, 2024 - mdpi.com
For the energy transition in the residential sector, heat pumps are a core technology for
decarbonizing thermal energy production for space heating and domestic hot water …
decarbonizing thermal energy production for space heating and domestic hot water …
Autonomous Micro-Grids: A Reinforcement Learning-Based Energy Management Model in Smart Cities
The growing electricity consumption of communities has raised concerns about the
environmental impact of traditional energy sources. To mitigate these concerns …
environmental impact of traditional energy sources. To mitigate these concerns …
[HTML][HTML] Algorithmic Innovations in Multi-Agent Reinforcement Learning: A Pathway for Smart Cities
I Agbossou - 2023 - intechopen.com
The concept of smart cities has emerged as an instrumental solution to tackle the intricate
challenges associated with urbanization in the twenty-first century. Among the myriad of …
challenges associated with urbanization in the twenty-first century. Among the myriad of …
Multi-Agent Hierarchical Graph Attention Reinforcement Learning for Grid-Aware Energy Management
The increasing adoption of renewable energy has posed challenges for voltage regulation
in power distribution networks. Grid-aware energy management, which includes the control …
in power distribution networks. Grid-aware energy management, which includes the control …