The DOI matches its Crossref record; 77 of the 77 references it cites were found in a registry or an index.
Review and classification of barriers and enablers of demand response in the smart grid
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Cites
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Cramming More Components onto Integrated Circuits (1965)
Moore, G. (2021) · Ideas That Created the Future · doi:10.7551/mitpress/12274.003.0027 · Cited by 6,241
Cramming More Components Onto Integrated Circuits
Moore, G. E. (1998) · Proceedings of the IEEE · doi:10.1109/jproc.1998.658762 · Cited by 5,926
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Farhangi, H. (2010) · IEEE Power and Energy Magazine · doi:10.1109/mpe.2009.934876 · Cited by 2,870
Mohsenian-Rad, A.-H., Wong, V. W. S., Jatskevich, J., Schober, R., & Leon-Garcia, A. (2010) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2010.2089069 · Cited by 2,744
Smart Grid Technologies: Communication Technologies and Standards
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Demand 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
Democracy Barometer. Methodology. Version 4.
Merkel, W., Bochsler, D., Bousbah, K., Bühlmann, M., Giebler, H., Hänni, M., Heyne, L., Müller, L., Ruth, S., & Weßels, B. (2004) · Intellectum (Universidad de La Sabana) · doi:10.1007/s13398-014-0173-7.2 · Cited by 2,331
Cited by
Mikalef, P., Krogstie, J., Pappas, I. O., & Pavlou, P. (2020) · Information & Management · doi:10.1016/j.im.2019.05.004 · Cited by 1,373
“…highlights that realizing technological capability improvements in any industry, including energy and infrastructure, requires employees with the appropriate technical and business skill-set [102], as well as a data-driven culture and an orientation toward organizational learning [103].”
BackgroundUsing peer-to-peer energy-trading platforms to incentivize prosumers to form federated power plants
Morstyn, T., Farrell, N., Darby, S. J., & McCulloch, M. D. (2018) · Nature Energy · doi:10.1038/s41560-017-0075-y · Cited by 831
Artificial Intelligence Enabled Demand Response: Prospects and Challenges in Smart Grid Environment
Khan, M. A., Saleh, A. M., Waseem, M., & Sajjad, I. A. (2023) · IEEE Access · doi:10.1109/access.2022.3231444 · Cited by 179
Correia, A. F. M., Moura, P., & de Almeida, A. T. (2022) · Energies · doi:10.3390/en15238905 · Cited by 27
Multi-Agent Decision Support Tool to Enable Interoperability among Heterogeneous Energy Systems
Teixeira, B., Pinto, T., Silva, F., Santos, G., Praça, I., & Vale, Z. (2018) · Applied Sciences · doi:10.3390/app8030328 · Cited by 26
Metadata
- Authors
- Good, N., Ellis, K. A., & Mancarella, P.
- Venue
- Renewable and Sustainable Energy Reviews
- Publisher
- Elsevier BV
- Published
- 2017-05
- Volume
- 72
- Pages
- 57-72
- ISSN
- 1364-0321 (ISSN-L)
- OpenAlex
- W2578882176
- Cited by
- 284
- References
- 77
- FWCI
- 12.75
- Type
- journal article
- Language
- en
- Open access
- green
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- Good, N., Ellis, K. A., & Mancarella, P. (2017). Review and classification of barriers and enablers of demand response in the smart grid. Renewable and Sustainable Energy Reviews. https://doi.org/10.1016/j.rser.2017.01.043
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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.
