The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Optimisation of demand response in electric power systems, a review
Abstract
Abstract Demand response programs offer efficient solutions for many power system problems, such as high generation cost, high demand’s peak to average ratio, high emissions, reliability issues and congestion in generation, transmission and distribution systems. Their main function is to assist power systems during peak demand hours and also during contingencies. They are a subcategory of the family of demand side management (DSM) strategies. DR programs are classified into two broad categories; price-based DR programs and incentive-based DR programs. In order to exploit their full potential, DR programs must be implemented optimally. Such a problem, which here is referred to as “DR optimisation problem”, is a hot research topic and has been frequently researched in the literature. This paper aims to review different research works on DR optimisation problems. Based on the conducted review, some directions for future research are proposed.
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Citations
Cites
Demand side management in smart grid using heuristic optimization
Logenthiran, T., Srinivasan, D., & Shun, T. Z. (2012) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2012.2195686 · Cited by 1,229
Rethinking real-time electricity pricing
Allcott, H. (2011) · Resource and Energy Economics · doi:10.1016/j.reseneeco.2011.06.003 · Cited by 441
The long-run efficiency of real-time electricity pricing
Borenstein, S. (2005) · The Energy Journal · doi:10.5547/issn0195-6574-ej-vol26-no3-5.bertsekas · Cited by 233
Zhu, Z., Tang, J., Lambotharan, S., Chin, W. H., & Fan, Z. (2011) · 2011 IEEE GLOBECOM Workshops (GC Wkshps) · doi:10.1109/glocomw.2011.6162372 · Cited by 157
Cited by
Antonopoulos, I., Robu, V., Couraud, B., Kirli, D., Norbu, S., Kiprakis, A., Flynn, D., Elizondo-Gonzalez, S., & Wattam, S. (2020) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2020.109899 · Cited by 656
Tang, H., Wang, S., & Li, H. (2021) · Energy · doi:10.1016/j.energy.2020.119598 · Cited by 259
Metadata
- Authors
- Jordehi, A. R.
- Venue
- Renewable and Sustainable Energy Reviews
- Publisher
- Elsevier BV
- Published
- 2019-04
- Volume
- 103
- Pages
- 308-319
- ISSN
- 1364-0321 (ISSN-L)
- OpenAlex
- W2908571787
- Cited by
- 498
- References
- 4
- FWCI
- 22.21
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
