The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
A Weather-Based Hybrid Method for 1-Day Ahead Hourly Forecasting of PV Power Output
Abstract
To improve real-time control performance and reduce possible negative impacts of photovoltaic (PV) systems, an accurate forecasting of PV output is required, which is an important function in the operation of an energy management system (EMS) for distributed energy resources. In this paper, a weather-based hybrid method for 1-day ahead hourly forecasting of PV power output is presented. The proposed approach comprises classification, training, and forecasting stages. In the classification stage, the self-organizing map (SOM) and learning vector quantization (LVQ) networks are used to classify the collected historical data of PV power output. The training stage employs the support vector regression (SVR) to train the input/output data sets for temperature, probability of precipitation, and solar irradiance of defined similar hours. In the forecasting stage, the fuzzy inference method is used to select an adequate trained model for accurate forecast, according to the weather information collected from Taiwan Central Weather Bureau (TCWB). The proposed approach is applied to a practical PV power generation system. Numerical results show that the proposed approach achieves better prediction accuracy than the simple SVR and traditional ANN methods.
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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
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
Forecasting of photovoltaic power generation and model optimization: a review
Das, U. K., Tey, K. S., Seyedmahmoudian, M., Mekhilef, S., Idris, M. Y. I., Van Deventer, W., Horan, B., & Stojcevski, A. (2018) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2017.08.017 · Cited by 1,211
Solar photovoltaic generation forecasting methods: A review
Sobri, S., Koohi-Kamali, S., & Rahim, N. A. (2018) · Energy Conversion and Management · doi:10.1016/j.enconman.2017.11.019 · Cited by 990
Photovoltaic and solar power forecasting for smart grid energy management
Wan, C., Zhao, J., Song, Y., Xu, Z., Lin, J., & Hu, Z. (2015) · CSEE Journal of Power and Energy Systems · doi:10.17775/cseejpes.2015.00046 · Cited by 654
Metadata
- Authors
- Yang, H.-T., Huang, C.-M., Huang, Y.-C., & Pai, Y.-S.
- Venue
- IEEE Transactions on Sustainable Energy
- Published
- 2014-07
- Volume
- 5
- Issue
- 3
- Pages
- 917-926
- ISSN
- 1949-3029 (ISSN-L)
- 1949-3037
- OpenAlex
- W2115294291
- Cited by
- 469
- References
- 16
- FWCI
- 31.69
- Type
- journal article
- Language
- en
- Open access
- closed
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- Yang, H.-T., Huang, C.-M., Huang, Y.-C., & Pai, Y.-S. (2014). A Weather-Based Hybrid Method for 1-Day Ahead Hourly Forecasting of PV Power Output. IEEE Transactions on Sustainable Energy. https://doi.org/10.1109/tste.2014.2313600
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