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RSS FeedsEnergies, Vol. 15, Pages 3568: Deep-Learning-Based Adaptive Model for Solar Forecasting Using Clustering (Energies)


13 may 2022 09:08:19

Energies, Vol. 15, Pages 3568: Deep-Learning-Based Adaptive Model for Solar Forecasting Using Clustering (Energies)

Accurate short-term solar forecasting is challenging due to weather uncertainties associated with cloud movements. Typically, a solar station comprises a single prediction model irrespective of time and cloud condition, which often results in suboptimal performance. In the proposed model, different categories of cloud movement are discovered using K-medoid clustering. To ensure broader variation in cloud movements, neighboring stations were also used that were selected using a dynamic time warping (DTW)-based similarity score. Next, cluster-specific models were constructed. At the prediction time, the current weather condition is first matched with the different weather groups found through clustering, and a cluster-specific model is subsequently chosen. As a result, multiple models are dynamically used for a particular day and solar station, which improves performance over a single site-specific model. The proposed model achieved 19.74% and 59% less normalized root mean square error (NRMSE) and mean rank compared to the benchmarks, respectively, and was validated for nine solar stations across two regions and three climatic zones of India.

71 viewsCategory: Biophysics, Biotechnology, Physics
Energies, Vol. 15, Pages 3567: A Practical Review of the Public Policies Used to Promote the Implementation of PV Technology in Smart Grids: The Case of Portugal (Energies)
Energies, Vol. 15, Pages 3569: Computational Optimization of Free-Piston Stirling Engine by Variable-Step Simplified Conjugate Gradient Method with Compatible Strategies (Energies)
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