The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Achieving Controllability of Electric Loads
Abstract
This paper discusses conceptual frameworks for actively involving highly distributed loads in power system control actions. The context for load control is established by providing an overview of system control objectives, including economic dispatch, automatic generation control, and spinning reserve. The paper then reviews existing initiatives that seek to develop load control programs for the provision of power system services. We then discuss some of the challenges to achieving a load control scheme that balances device-level objectives with power system-level objectives. One of the central premises of the paper is that, in order to achieve full responsiveness, direct load control (as opposed to price response) is required to enable fast time scale, predictable control opportunities, especially for the provision of ancillary services such as regulation and contingency reserves. Centralized, hierarchical, and distributed control architectures are discussed along with benefits and disadvantages, especially in relation to integration with the legacy power system control architecture. Implications for the supporting communications infrastructure are also considered. Fully responsive load control is illustrated in the context of thermostatically controlled loads and plug-in electric vehicles.
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Cites
Demand side management: benefits and challenges
Strbac, G. (2008) · Energy Policy · doi:10.1016/j.enpol.2008.09.030 · Cited by 1,702
Demand response and electricity market efficiency
Spees, K., & Lave, L. B. (2007) · The Electricity Journal · doi:10.1016/j.tej.2007.01.006 · Cited by 235
Cited by
Cyber–Physical System Security for the Electric Power Grid
Sridhar, S., Hahn, A., & Govindarasu, M. (2012) · Proceedings of the IEEE · doi:10.1109/jproc.2011.2165269 · Cited by 1,208
Benefits and challenges of electrical demand response: a critical review
O׳Connell, N., Pinson, P., Madsen, H., & O׳Malley, M. (2014) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2014.07.098 · Cited by 636
A Survey of Algorithms for Distributed Charging Control of Electric Vehicles in Smart Grid
Nimalsiri, N. I., Mediwaththe, C. P., Ratnam, E. L., Shaw, M., Smith, D. B., & Halgamuge, S. K. (2020) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2019.2943620 · Cited by 271
The role of electric vehicles in smart grids
Galus, M. D., Vayá, M. G., Krause, T., & Andersson, G. (2013) · WIREs Energy and Environment · doi:10.1002/wene.56 · Cited by 129
Model development and identification for fast demand response in commercial HVAC systems
Goddard, G., Klose, J., & Backhaus, S. (2014) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2014.2312430 · Cited by 101
Metadata
- Authors
- Callaway, D. S., & Hiskens, I. A.
- Venue
- Proceedings of the IEEE
- Published
- 2011-01
- Volume
- 99
- Issue
- 1
- Pages
- 184-199
- ISSN
- 0018-9219 (ISSN-L)
- 1558-2256
- OpenAlex
- W2009022268
- Cited by
- 1,069
- References
- 2
- FWCI
- 39.62
- Type
- journal article
- Language
- en
- Open access
- closed
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- Callaway, D. S., & Hiskens, I. A. (2011). Achieving Controllability of Electric Loads. Proceedings of the IEEE. https://doi.org/10.1109/jproc.2010.2081652
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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.