The DOI matches its Crossref record; 161 of the 161 references it cites were found in a registry or an index.
Energetics Systems and artificial intelligence: Applications of industry 4.0
Open accessAbstract
Industrial development with the growth, strengthening, stability, technical advancement, reliability, selection, and dynamic response of the power system is essential. Governments and companies invest billions of dollars in technologies to convert, harvest, rising demand, changing demand and supply patterns, efficiency, lack of analytics required for optimal energy planning, and store energy. In this scenario, artificial intelligence (AI) is starting to play a major role in the energy market. Recognizing the importance of AI, this study was conducted on seven different energetics systems and their variety of applications, including: i) electricity production; ii) power delivery; iii) electric distribution networks; iv) energy storage; v) energy saving, new energy materials, and devices; vi) energy efficiency and nanotechnology; and vii) energy policy, and economics. The main drivers are the four key techniques used in current AI technologies, including: i) fuzzy logic systems; ii) artificial neural networks; iii) genetic algorithms; and iv) expert systems. In developed countries, the power industry has started using AI to connect with smart meters, smart grids, and the Internet of Things devices. These AI technologies will lead to the improvement of efficiency, energy management, transparency, and the usage of renewable energies. In recent decades/years, new AI technology has brought significant improvements to how power system devices monitor data, communicate with the system, analyze input–output, and display data in unprecedented ways. New applications in the energy system become feasible when these new AI developments are incorporated into the energy industry. But on the contrary, much more investment is needed in global research into AI and data-driven models. In terms of power supply, AI can help utilities provide customers with renewable and affordable electricity from complex sources in a secure manner, while at the same time providing these customers with the opportunity to use their own energy more efficiently. Moreover, policy recommendations, research opportunities, and how industry 4.0 will improve sustainability have been briefly described.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Commentary: The Materials Project: A materials genome approach to accelerating materials innovation
Jain, A., Ong, S. P., Hautier, G., Chen, W., Richards, W. D., Dacek, S., Cholia, S., Gunter, D., Skinner, D., Ceder, G., et al. (2013) · APL Materials · doi:10.1063/1.4812323 · Cited by 13,094
Challenges for Rechargeable Li Batteries
Goodenough, J. B., & Kim, Y. (2010) · Chemistry of Materials · doi:10.1021/cm901452z · Cited by 10,943
The path towards sustainable energy
Chu, S., Cui, Y., & Liu, N. (2017) · Nature Materials · doi:10.1038/nmat4834 · Cited by 4,791
The role of artificial intelligence in achieving the Sustainable Development Goals
Vinuesa, R., Azizpour, H., Leite, I., Balaam, M., Dignum, V., Domisch, S., Felländer, A., Langhans, S. D., Tegmark, M., & Fuso Nerini, F. (2020) · Nature Communications · doi:10.1038/s41467-019-14108-y · Cited by 3,294
Blockchain technology in the energy sector: a systematic review of challenges and opportunities
Andoni, M., Robu, V., Flynn, D., Abram, S., Geach, D., Jenkins, D., McCallum, P., & Peacock, A. (2019) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2018.10.014 · Cited by 2,426
Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems
del Valle, Y., Venayagamoorthy, G. K., Mohagheghi, S., Hernandez, J.-C., & Harley, R. G. (2008) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2007.896686 · Cited by 2,277
The high-throughput highway to computational materials design
Curtarolo, S., Hart, G. L. W., Nardelli, M. B., Mingo, N., Sanvito, S., & Levy, O. (2013) · Nature Materials · doi:10.1038/nmat3568 · Cited by 2,053
Enhanced electrocatalytic CO2 reduction via field-induced reagent concentration
Liu, M., Pang, Y., Zhang, B., De Luna, P., Voznyy, O., Xu, J., Zheng, X., Dinh, C. T., Fan, F., Cao, C., et al. (2016) · Nature · doi:10.1038/nature19060 · Cited by 2,000
Toward a smart grid: power delivery for the 21st century
Massoud Amin, S., & Wollenberg, B. F. (2005) · IEEE Power and Energy Magazine · doi:10.1109/mpae.2005.1507024 · Cited by 1,630
A metal-free organic–inorganic aqueous flow battery
Huskinson, B., Marshak, M. P., Suh, C., Er, S., Gerhardt, M. R., Galvin, C. J., Chen, X., Aspuru-Guzik, A., Gordon, R. G., & Aziz, M. J. (2014) · Nature · doi:10.1038/nature12909 · Cited by 1,585
Cited by
Liu, Z., Sun, Y., Xing, C., Liu, J., He, Y., Zhou, Y., & Zhang, G. (2022) · Energy and AI · doi:10.1016/j.egyai.2022.100195 · Cited by 288
Strielkowski, W., Vlasov, A., Selivanov, K., Muraviev, K., & Shakhnov, V. (2023) · Energies · doi:10.3390/en16104025 · Cited by 237
Nguyen, V. N., Tarełko, W., Sharma, P., El-Shafay, A. S., Chen, W.-H., Nguyen, P. Q. P., Nguyen, X. P., & Hoang, A. T. (2024) · Energy & Fuels · doi:10.1021/acs.energyfuels.3c04343 · Cited by 130
Leveraging Artificial Intelligence to Bolster the Energy Sector in Smart Cities: A Literature Review
Camacho, J. D. J., Aguirre, B., Ponce, P., Anthony, B., & Molina, A. (2024) · Energies · doi:10.3390/en17020353 · Cited by 42
Alayed, H. M., & Awamleh, F. T. (2025) · ECONOMICS · doi:10.2478/eoik-2025-0094 · Cited by 3
Metadata
- Authors
- Ahmad, T., Zhu, H., Zhang, D., Tariq, R., Bassam, A., Ullah, F., AlGhamdi, A. S., & Alshamrani, S. S.
- Venue
- Energy Reports
- Publisher
- Elsevier BV
- Published
- 2022-11
- Volume
- 8
- Pages
- 334-361
- ISSN
- 2352-4847 (ISSN-L)
- OpenAlex
- W4200609187
- Cited by
- 369
- References
- 161
- FWCI
- 14.47
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Energetics Systems and artificial intelligence: Applications of industry 4.0. https://app.cochat.ai/papers/10.1016/j.egyr.2021.11.256
- The paper
- Ahmad, T., Zhu, H., Zhang, D., Tariq, R., Bassam, A., Ullah, F., AlGhamdi, A. S., & Alshamrani, S. S. (2022). Energetics Systems and artificial intelligence: Applications of industry 4.0. Energy Reports. https://doi.org/10.1016/j.egyr.2021.11.256
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.