Review on recent strategies for integrating energy storage systems in microgrids
Energy security and the resilience of electricity networks have recently gained critical
momentum as subjects of research. The challenges of meeting the increasing electrical …
momentum as subjects of research. The challenges of meeting the increasing electrical …
Strategies for controlling microgrid networks with energy storage systems: A review
M Al-Saadi, M Al-Greer, M Short - Energies, 2021 - mdpi.com
Distributed Energy Storage Systems are considered key enablers in the transition from the
traditional centralized power system to a smarter, autonomous, and decentralized system …
traditional centralized power system to a smarter, autonomous, and decentralized system …
Intelligent decision support for energy management: A methodology for tailored explainability of artificial intelligence analytics
This paper presents a novel development methodology for artificial intelligence (AI) analytics
in energy management that focuses on tailored explainability to overcome the “black box” …
in energy management that focuses on tailored explainability to overcome the “black box” …
Artificial intelligence and mathematical models of power grids driven by renewable energy sources: A survey
To face the impact of climate change in all dimensions of our society in the near future, the
European Union (EU) has established an ambitious target. Until 2050, the share of …
European Union (EU) has established an ambitious target. Until 2050, the share of …
[HTML][HTML] Effective estimation of the state-of-charge of latent heat thermal energy storage for heating and cooling systems using non-linear state observers
An effective quantification of the energy absorbed and supplied by latent heat thermal
energy storage (LHTES) units is critical to maximise their use within thermal systems. An …
energy storage (LHTES) units is critical to maximise their use within thermal systems. An …
[PDF][PDF] New insights into the emerging trends research of machine and deep learning applications in energy storage: a bibliometric analysis and publication trends
The publication trends and bibliometric analysis of the research landscape on the
applications of machine and deep learning in energy storage (MDLES) research were …
applications of machine and deep learning in energy storage (MDLES) research were …
Systematic review on deep reinforcement learning-based energy management for different building types
A Shaqour, A Hagishima - Energies, 2022 - mdpi.com
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 …
A review of reinforcement learning applications to control of heating, ventilation and air conditioning systems
Reinforcement learning has emerged as a potentially disruptive technology for control and
optimization of HVAC systems. A reinforcement learning agent takes actions, which can be …
optimization of HVAC systems. A reinforcement learning agent takes actions, which can be …
Deep reinforcement learning for autonomous water heater control
Electric water heaters represent 14% of the electricity consumption in residential buildings.
An average household in the United States (US) spends about USD 400–600 (0.45¢/L …
An average household in the United States (US) spends about USD 400–600 (0.45¢/L …
[HTML][HTML] Application of deep learning techniques to minimize the cost of operation of a hybrid solar-biomass system in a multi-family building
Concerns related to climate change put renewable energy at the centre of most of the
policies aimed at achieving a deep decarbonisation of the building sector. The combined …
policies aimed at achieving a deep decarbonisation of the building sector. The combined …