A New Wind Speed Scenario Generation Method Based on Principal Component and R-Vine Copula Theories
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Cited by:
- Li, Yanting & Peng, Xinghao & Zhang, Yu, 2022. "Forecasting methods for wind power scenarios of multiple wind farms based on spatio-temporal dependency structure," Renewable Energy, Elsevier, vol. 201(P1), pages 950-960.
- Tonni Agustiono Kurniawan & Mohd Hafiz Dzarfan Othman & Xue Liang & Muhammad Ayub & Hui Hwang Goh & Tutuk Djoko Kusworo & Ayesha Mohyuddin & Kit Wayne Chew, 2022. "Microbial Fuel Cells (MFC): A Potential Game-Changer in Renewable Energy Development," Sustainability, MDPI, vol. 14(24), pages 1-20, December.
- Dhaval Dalal & Muhammad Bilal & Hritik Shah & Anwarul Islam Sifat & Anamitra Pal & Philip Augustin, 2023. "Cross-Correlated Scenario Generation for Renewable-Rich Power Systems Using Implicit Generative Models," Energies, MDPI, vol. 16(4), pages 1-20, February.
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Keywords
principal component theory; R-vine copula theory; several wind farms; scenario generation; spatiotemporal correlation;All these keywords.
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