A simple but accurate two-state model for nowcasting PV power

Paulescu, Marius; Stefu, Nicoleta; Dughir, Ciprian; Sabadus, Andreea; Calinoiu, Delia; Bădescu, Viorel

doi:10.1016/j.renene.2022.05.056

Cited by 8 publications

(4 citation statements)

References 28 publications

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“…It is worth to note that PV2-state successfully passed the accuracy tests (see e.g. [8]). The case study, presented next, is just trying to identify and explain the specifics of the atmosphere that determine this behavior.…”

Section: A General Assessment Of the Model Performance During The Two...mentioning

confidence: 86%

“…Due to such particularities in the state-of-the-sky, during the two days analyzed in this study, the performance of the PV2-state is rather modest. However, it is worth to emphasize that the overall performance of PV2-state model is high [8] at intra-hour forecast horizons. The results of this study constitutes a basis for further research aimed at an increase in the quality of PV2-state forecasts.…”

Section: Discussionmentioning

confidence: 99%

“…Equation (2) underlines without question the high significance of SSN in PV2-state operation, this being the sole quantity directly forecasted. For a detailed description of PV2-state model and a practical implementation guide we point the reader to [8].…”

Section: Pv2-state Modelmentioning

confidence: 99%

“…This study evaluates the performance of the PV2-state model [8] to intra-hour PV power forecasting in highly variable sky conditions. The model operates as follows: if it is expected that the Sun will shine at the forecast time horizon, the PV power is estimated using a real-time adjusted clear-sky model; otherwise, the estimated clear-sky PV power is corrected by taking into account the real-time cloud transmittance.…”

Section: Introductionmentioning

confidence: 99%

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Short-Term PV Power Forecasting Based on Sky Imagery. A Case Study at the West University of Timisoara

Dughir

Sabadus

Stefu

et al. 2022

Annals of West University of Timisoara - Physics

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This study deals with the performance of PV2-state model in intra-hour forecasting of photovoltaic (PV) power. The PV2-state model links an empirical model for estimating the PV power delivered by a PV system under clear-sky with a model for forecasting the relative position of the Sun and clouds. Sunshine number (SSN), a binary quantifier showing if the Sun shines or not, is used as a measure for the Sun position with respect to clouds. A physics-based approach to intra-hour forecasting, processing cloud field information from an all-sky imager, is applied to predict SSN. The quality of SSN prediction conditions the overall quality of PV2-state forecasts. The PV2-state performance was evaluated against a challenging database (high variability in the state-of-the-sky, thin cloud cover, broken cloud field, isolated passing clouds) comprising radiometric data and sky-images collected on the Solar Platform of the West University of Timisoara, Romania. The investigation was performed from two perspectives: general model accuracy and, as a novelty, identification of characteristic elements in the state-of-the-sky which fault the SSN prediction. The outcome of such analysis represents the basis of further research aiming to increase the performance in PV power forecasting.

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Section: A General Assessment Of the Model Performance During The Two...mentioning

confidence: 86%

Section: Discussionmentioning

confidence: 99%

Section: Pv2-state Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations