The DOI matches its Crossref record; 63 of the 63 references it cites were found in a registry or an index.
A Review of Architectures and Concepts for Intelligence in Future Electric Energy Systems
Open accessAbstract
Renewable energy sources are one key enabler to decrease greenhouse gas emissions and to cope with the anthropogenic climate change. Their intermittent behavior and limited storage capabilities present a new challenge to power system operators to maintain power quality and reliability. Additional technical complexity arises from the large number of small distributed generation units and their allocation within the power system. Market liberalization and changing regulatory framework lead to additional organizational complexity. As a result, the design and operation of the future electric energy system have to be redefined. Sophisticated information and communication architectures, automation concepts, and control approaches are necessary in order to manage the higher complexity of so-called smart grids. This paper provides an overview of the state of the art and recent developments enabling higher intelligence in future smart grids. The integration of renewable sources and storage systems into the power grids is analyzed. Energy management and demand response methods and important automation paradigms and domain standards are also reviewed.
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
Multilevel inverters: a survey of topologies, controls, and applications
Rodriguez, J., Lai, J.-S., & Peng, F. Z. (2002) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2002.801052 · Cited by 6,715
Demand Side Management: Demand Response, Intelligent Energy Systems, and Smart Loads
Palensky, P., & Dietrich, D. (2011) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2011.2158841 · Cited by 2,927
Farhangi, H. (2010) · IEEE Power and Energy Magazine · doi:10.1109/mpe.2009.934876 · Cited by 2,870
Smart Grid Technologies: Communication Technologies and Standards
Gungor, V. C., Sahin, D., Kocak, T., Ergut, S., Buccella, C., Cecati, C., & Hancke, G. P. (2011) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2011.2166794 · Cited by 2,688
Self-citationDemand response and smart grids – a survey
Siano, P. (2014) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2013.10.022 · Cited by 2,411
Self-citationA Survey on Cascaded Multilevel Inverters
Malinowski, M., Gopakumar, K., Rodriguez, J., & Pérez, M. A. (2010) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2009.2030767 · Cited by 2,322
Koestler, A. (1968) · PubMed · Cited by 1,920
A Review on Basic Data-Driven Approaches for Industrial Process Monitoring
Yin, S., Ding, S. X., Xie, X., & Luo, H. (2014) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2014.2301773 · Cited by 1,716
Ipakchi, A., & Albuyeh, F. (2009) · IEEE Power and Energy Magazine · doi:10.1109/mpe.2008.931384 · Cited by 1,644
The Future Renewable Electric Energy Delivery and Management (FREEDM) System: The Energy Internet
Huang, A. Q., Crow, M. L., Heydt, G. T., Zheng, J. P., & Dale, S. J. (2011) · Proceedings of the IEEE · doi:10.1109/jproc.2010.2081330 · Cited by 1,463
Cited by
Smart Agents in Industrial Cyber–Physical Systems
Leitao, P., Karnouskos, S., Ribeiro, L., Lee, J., Strasser, T., & Colombo, A. W. (2016) · Proceedings of the IEEE · doi:10.1109/jproc.2016.2521931 · Cited by 462
Self-citationEnergetics Systems and artificial intelligence: Applications of industry 4.0
Ahmad, T., Zhu, H., Zhang, D., Tariq, R., Bassam, A., Ullah, F., AlGhamdi, A. S., & Alshamrani, S. S. (2022) · Energy Reports · doi:10.1016/j.egyr.2021.11.256 · Cited by 369
Microgrid clustering architectures
Bullich-Massagué, E., Díaz-González, F., Aragüés-Peñalba, M., Girbau-Llistuella, F., Olivella-Rosell, P., & Sumper, A. (2018) · Applied Energy · doi:10.1016/j.apenergy.2017.12.048 · Cited by 245
Metadata
- Authors
- Strasser, T., Andren, F., Kathan, J., Cecati, C., Buccella, C., Siano, P., Leitao, P., Zhabelova, G., Vyatkin, V., Vrba, P., & Marik, V.
- Venue
- IEEE Transactions on Industrial Electronics
- Published
- 2015-04
- Volume
- 62
- Issue
- 4
- Pages
- 2424-2438
- ISSN
- 0278-0046 (ISSN-L)
- 1557-9948
- OpenAlex
- W2025143619
- Cited by
- 572
- References
- 63
- FWCI
- 23.52
- Type
- journal article
- Language
- en
- Open access
- green
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: A Review of Architectures and Concepts for Intelligence in Future Electric Energy Systems. https://app.cochat.ai/papers/10.1109/tie.2014.2361486
- The paper
- Strasser, T., Andren, F., Kathan, J., Cecati, C., Buccella, C., Siano, P., Leitao, P., Zhabelova, G., Vyatkin, V., Vrba, P., & Marik, V. (2015). A Review of Architectures and Concepts for Intelligence in Future Electric Energy Systems. IEEE Transactions on Industrial Electronics. https://doi.org/10.1109/tie.2014.2361486
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.
