Machine learning and deep learning in energy systems: A review
With population increases and a vital need for energy, energy systems play an important
and decisive role in all of the sectors of society. To accelerate the process and improve the …
and decisive role in all of the sectors of society. To accelerate the process and improve the …
[HTML][HTML] Artificial intelligence powered large-scale renewable integrations in multi-energy systems for carbon neutrality transition: Challenges and future perspectives
The vigorous expansion of renewable energy as a substitute for fossil energy is the
predominant route of action to achieve worldwide carbon neutrality. However, clean energy …
predominant route of action to achieve worldwide carbon neutrality. However, clean energy …
Uncertainty quantification in machine learning for engineering design and health prognostics: A tutorial
On top of machine learning (ML) models, uncertainty quantification (UQ) functions as an
essential layer of safety assurance that could lead to more principled decision making by …
essential layer of safety assurance that could lead to more principled decision making by …
[HTML][HTML] Advances of machine learning in multi-energy district communities‒mechanisms, applications and perspectives
Y Zhou - Energy and AI, 2022 - Elsevier
Energy paradigm transition towards the carbon neutrality requires combined and continuous
efforts in cleaner power production, advanced energy storages, flexible district energy …
efforts in cleaner power production, advanced energy storages, flexible district energy …
[HTML][HTML] Artificial intelligence in renewable systems for transformation towards intelligent buildings
Y Zhou - Energy and AI, 2022 - Elsevier
Carbon-neutrality transition in building sectors requires combinations of renewable systems
and artificial intelligence (AI) for robustness, reliability, automation, and flexibility. In this …
and artificial intelligence (AI) for robustness, reliability, automation, and flexibility. In this …
An innovative optimal 4E solar-biomass waste polygeneration system for power, methanol, and freshwater production
Modern polygeneration systems have increased the flexibility of production in energy
systems. In this paper, a polygeneration system for producing power, freshwater, and …
systems. In this paper, a polygeneration system for producing power, freshwater, and …
[HTML][HTML] GIScience can facilitate the development of solar cities for energy transition
The energy transition is increasingly being discussed and implemented to cope with the
growing environmental crisis. However, great challenges remain for effectively harvesting …
growing environmental crisis. However, great challenges remain for effectively harvesting …
An efficient data-driven optimal sizing framework for photovoltaics-battery-based electric vehicle charging microgrid
The rapid growth of electric vehicles (EV) in cities has led to the development of microgrids
(MGs) combined with photovoltaics (PV) and the energy storage system (ESS) as charging …
(MGs) combined with photovoltaics (PV) and the energy storage system (ESS) as charging …
Development of an ANN-based building energy model for information-poor buildings using transfer learning
Accurate building energy prediction is vital to develop optimal control strategies to enhance
building energy efficiency and energy flexibility. In recent years, the data-driven approach …
building energy efficiency and energy flexibility. In recent years, the data-driven approach …
Towards climate resilient urban energy systems: a review
Climate change and increased urban population are two major concerns for society. Moving
towards more sustainable energy solutions in the urban context by integrating renewable …
towards more sustainable energy solutions in the urban context by integrating renewable …