Spatial and Temporal Variability of PV Output in an Insular Grid: Case of Reunion Island

David, Mathieu; Ramahatana, Faly; Liandrat, Olivier

doi:10.1016/j.egypro.2014.10.117

Cited by 33 publications

(13 citation statements)

References 15 publications

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“…This metric proposed by [27] is the standard deviation of the change in the clear sky index defined by: The values of solar variability in Table 1 have been calculated for a time scale Δt = 1 hour (as we deal with hourly GHI records) and for a time span that corresponds to two years of hourly data. A site with variability above 0.2 is considered as experiencing very unstable conditions [27,28].…”

Section: Sites Analysismentioning

confidence: 99%

Solar Forecasting in a Challenging Insular Context

Lauret¹,

Lorenz

David³

2016

Atmosphere

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This paper aims at assessing the accuracy of different solar forecasting methods in the case of an insular context. Two sites of La Réunion Island, Le Tampon and Saint-Pierre, are chosen to do the benchmarking exercise. Réunion Island is a tropical island with a complex orography where cloud processes are mainly governed by local dynamics. As a consequence, Réunion Island exhibits numerous micro-climates. The two aforementioned sites are quite representative of the challenging character of solar forecasting in the case of a tropical island with complex orography. Hence, although distant from only 10 km, these two sites exhibit very different sky conditions. This work focuses on day-ahead and intra-day solar forecasting. Day-ahead solar forecasts are provided by the European Center for Medium-Range Weather Forecast (ECMWF). This organization maintains and runs the Numerical Weather Prediction (NWP) model named Integrated Forecast System (IFS). In this work, post-processing techniques are applied to refine the output of the IFS model for day-ahead forecasting. Statistical models like a recursive linear model or a nonlinear model such as an artificial neural network are used to produce the intra-day solar forecasts. It is shown that a combination of the IFS model and the neural network model further improves the accuracy of the forecasts.

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Section: Sites Analysismentioning

confidence: 99%

Solar Forecasting in a Challenging Insular Context

Lauret¹,

Lorenz

David³

2016

Atmosphere

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“…By analysis of the figure, the strength of the procedures shown in Section 5 clearly appears to be predicting the different behavior during the day, not only in terms of radiation level but also in terms of variability of instantaneous solar irradiance. The first part of the day, in fact, is characterized by low values of mean solar irradiance (low r k 1,22,10 , see Equation (16)) and a significant variability value. The second part of the day, instead, is characterized by a regular profile of the solar irradiance with a high value of mean solar irradiance (high r k 2,22,10 , see Equation (16)).…”

Section: Month Experimental Parametric Ss Mae (Pu) Ss Rmse (Pu) Ss Mamentioning

confidence: 99%

“…The first part of the day, in fact, is characterized by low values of mean solar irradiance (low r k 1,22,10 , see Equation (16)) and a significant variability value. The second part of the day, instead, is characterized by a regular profile of the solar irradiance with a high value of mean solar irradiance (high r k 2,22,10 , see Equation (16)). This behavior is quite well captured by the forecasting procedure, of which the accuracy is evident, especially in case of accurate weather predictions.…”

Section: Month Experimental Parametric Ss Mae (Pu) Ss Rmse (Pu) Ss Mamentioning

confidence: 99%

“…This has been treated in the relevant technical literature in [3][4][5][6][7][8][9][10][11][12][13][14][15][16], where the clear sky index and the clearness index (or the normalized clearness index [12]) are typically used to describe solar irradiance and radiation.…”

Section: Introductionmentioning

confidence: 99%

“…In particular, in [14][15][16] the variability of solar irradiance is captured by observing the changes in clear sky index for a considered time interval. The primary usefulness of the clear sky index is the removal of diurnal and seasonal signals from a given set of radiation data to compute fluctuation power content ([17]).…”

Section: Introductionmentioning

confidence: 99%

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Solar Radiation Forecasting, Accounting for Daily Variability

2016

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Radiation forecast accounting for daily and instantaneous variability was pursued by means of a new bi-parametric statistical model that builds on a model previously proposed by the same authors. The statistical model is developed with direct reference to the Liu-Jordan clear sky theoretical expression but is not bound by a specific clear sky model; it accounts separately for the mean daily variability and for the variation of solar irradiance during the day by means of two corrective parameters. This new proposal allows for a better understanding of the physical phenomena and improves the effectiveness of statistical characterization and subsequent simulation of the introduced parameters to generate a synthetic solar irradiance time series. Furthermore, the analysis of the experimental distributions of the two parameters' data was developed, obtaining opportune fittings by means of parametric analytical distributions or mixtures of more than one distribution. Finally, the model was further improved toward the inclusion of weather prediction information in the solar irradiance forecasting stage, from the perspective of overcoming the limitations of purely statistical approaches and implementing a new tool in the frame of solar irradiance prediction accounting for weather predictions over different time horizons.

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Reviews on characteristic of renewables: Evaluating the variability and complementarity

Yan

Han

et al. 2020

Int Trans Electr Energ Syst

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Spatial and Temporal Variability of PV Output in an Insular Grid: Case of Reunion Island

Cited by 33 publications

References 15 publications

Solar Forecasting in a Challenging Insular Context

Solar Forecasting in a Challenging Insular Context

Solar Radiation Forecasting, Accounting for Daily Variability

Reviews on characteristic of renewables: Evaluating the variability and complementarity

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