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Energy and AI is a peer-reviewed journal published by Elsevier, covering Energy Load and Power Forecasting, Smart Grid Energy Management, Advanced Battery Technologies Research.
| Publisher | Elsevier |
|---|---|
| Reference style | Numbered (Elsevier) Numbered — [1], [2] in the text [1] A. Smith, B. Jones, C. Lee, A representative article title, Energy and AI 12 (2023) 45–58.
Formats any DOI in Energy and AI style. No sign-up. |
| Publishes research in | Energy Load and Power Forecasting Smart Grid Energy Management Advanced Battery Technologies Research Building Energy and Comfort Optimization Solar Radiation and Photovoltaics |
| ISSN | 2666-5468 |
| Citation impact (2-yr) | 8.01 |
| h-index | 65 |
| i10-index | 391 |
| Total citations | 19,375 |
| Article processing charge | $3,000 |
| Open access | Yes |
| Top institutions publishing here | Tianjin University |
| Journal website | www.journals.elsevier.com |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
Polymer electrolyte membrane (PEM) fuel cells are electrochemical devices that directly convert the chemical energy stored in fuel into electrical energy with a practical conversion efficiency as high as 65%. In the past years, significant progress has been made in PEM fuel cell commercialization. By 2019, there were over 19,000 fuel cell electric vehicles (FCEV)…
Despite widespread adoption and outstanding performance, machine learning models are considered as “black boxes”, since it is very difficult to understand how such models operate in practice. Therefore, in the power systems field, which requires a high level of accountability, it is hard for experts to trust and justify decisions and recommendations made by these…
Information technologies involving artificial Intelligence, big data, Internet of Things devices and blockchain have been developed and implemented in many engineering fields worldwide. Existing review articles focus on developments and characteristics of individual topics and the associated deployment in the energy sector. These technologies, all based on communication, information, and data analysis, are naturally coherent…
Effective management of lithium-ion batteries is a key enabler for a low carbon future, with applications including electric vehicles and grid scale energy storage. The lifetime of these devices depends greatly on the materials used, the system design and the operating conditions. This complexity has therefore made real-world control of battery systems challenging. However, with…
Lithium-ion batteries are fuelling the advancing renewable-energy based world. At the core of transformational developments in battery design, modelling and management is data. In this work, the datasets associated with lithium batteries in the public domain are summarised. We review the data by mode of experimental testing, giving particular attention to test variables and data…
