The DOI matches its Crossref record; 79 of the 79 references it cites were found in a registry or an index.
A review on the selected applications of forecasting models in renewable power systems
Abstract
This paper presents a literature review on the selected applications of renewable resource and power forecasting models to facilitate the optimal integration of renewable energy (RE) in power systems. This review is drafted on the basis of the selected high quality research publications from the past decade. Although the development of forecast models for RE generation, i.e., wind and solar energy, is a well-researched area, however, the performance of these models is usually evaluated using statistical error metrics. With regard to application, determining the optimality of accurate forecasts in terms of system economics and major planning aspects is an emerging phenomenon, that chalks out the main subject area of this survey. Specifically, the application domains include: 1) optimal power system dispatch (unit commitment, generation scheduling, economic dispatch), 2) optimal sizing of energy storage system, 3) energy market policies and profit maximization of market participants, 4) reliability assessment, and 5) optimal reserve size determination in power systems. The application-oriented review on these vital areas can be used by the power sector for familiarization with the recent trends and for analyzing the impact of forecasting improvement on optimal power system design and operation.
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Cites
Machine learning methods for solar radiation forecasting: A review
Voyant, C., Notton, G., Kalogirou, S., Nivet, M.-L., Paoli, C., Motte, F., & Fouilloy, A. (2017) · Renewable Energy · doi:10.1016/j.renene.2016.12.095 · Cited by 1,836
Optimal Renewable Resources Mix for Distribution System Energy Loss Minimization
Atwa, Y. M., El-Saadany, E. F., Salama, M. M. A., & Seethapathy, R. (2010) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2009.2030276 · Cited by 1,387
Review of photovoltaic power forecasting
Antonanzas, J., Osorio, N., Escobar, R., Urraca, R., Martinez-de-Pison, F. J., & Antonanzas-Torres, F. (2016) · Solar Energy · doi:10.1016/j.solener.2016.06.069 · Cited by 1,343
A review on the forecasting of wind speed and generated power
Lei, M., Shiyan, L., Chuanwen, J., Hongling, L., & Yan, Z. (2009) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2008.02.002 · Cited by 1,156
Solar forecasting methods for renewable energy integration
Inman, R. H., Pedro, H. T. C., & Coimbra, C. F. M. (2013) · Progress in Energy and Combustion Science · doi:10.1016/j.pecs.2013.06.002 · Cited by 1,062
Day-ahead wind speed forecasting using f-ARIMA models
Kavasseri, R. G., & Seetharaman, K. (2009) · Renewable Energy · doi:10.1016/j.renene.2008.09.006 · Cited by 951
Tso, G. K. F., & Yau, K. K. W. (2007) · Energy · doi:10.1016/j.energy.2006.11.010 · Cited by 933
Sizing of Energy Storage for Microgrids
Chen, S. X., Gooi, H. B., & Wang, M. Q. (2012) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2011.2160745 · Cited by 916
Review of solar irradiance forecasting methods and a proposition for small-scale insular grids
Diagne, M., David, M., Lauret, P., Boland, J. W., & Schmutz, N. (2013) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2013.06.042 · Cited by 808
Environmental/economic power dispatch using multiobjective evolutionary algorithms
Abido, M. A. (2003) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2003.818693 · Cited by 725
Cited by
Ahmed, R., Sreeram, V., Mishra, Y., & Arif, M. D. (2020) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2020.109792 · Cited by 1,259
Pinheiro, M. G., Madeira, S. C., & Francisco, A. P. (2023) · Applied Energy · doi:10.1016/j.apenergy.2022.120493 · Cited by 119
Metadata
- Authors
- Ahmed, A., & Khalid, M.
- Venue
- Renewable and Sustainable Energy Reviews
- Publisher
- Elsevier BV
- Published
- 2019-02
- Volume
- 100
- Pages
- 9-21
- ISSN
- 1364-0321 (ISSN-L)
- OpenAlex
- W2898515673
- Cited by
- 325
- References
- 79
- FWCI
- 7.62
- 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.