{"id":13123,"date":"2022-07-18T07:54:54","date_gmt":"2022-07-18T06:54:54","guid":{"rendered":"https:\/\/reuniwatt.com\/fr\/?p=13123"},"modified":"2022-07-18T08:25:56","modified_gmt":"2022-07-18T07:25:56","slug":"wrf-solar-eps-un-nouvel-outil-probabiliste-pour-la-prevision-solaire","status":"publish","type":"post","link":"https:\/\/reuniwatt.com\/fr\/actu-industrie\/wrf-solar-eps-un-nouvel-outil-probabiliste-pour-la-prevision-solaire\/","title":{"rendered":"WRF-Solar EPS : Un nouvel outil probabiliste pour la pr\u00e9vision solaire"},"content":{"rendered":"<div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-1 fusion-flex-container nonhundred-percent-fullwidth non-hundred-percent-height-scrolling\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:1144px;margin-left: calc(-4% \/ 2 );margin-right: calc(-4% \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-0 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:1.92%;--awb-margin-bottom-large:20px;--awb-spacing-left-large:1.92%;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:1.92%;--awb-spacing-left-medium:1.92%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-text fusion-text-1\" style=\"--awb-text-transform:none;\"><p><strong>Parmi les nombreux mod\u00e8les de pr\u00e9vision num\u00e9rique du temps (PNT) existants, le mod\u00e8le weather research and forecasting (WRF) est le mod\u00e8le pr\u00e9dictif open source le plus largement utilis\u00e9 pour les pr\u00e9visions m\u00e9t\u00e9orologiques dans le monde. Le syst\u00e8me de pr\u00e9diction d&rsquo;ensemble WRF-Solar EPS (Ensemble prediction system) r\u00e9cemment d\u00e9velopp\u00e9 nous permet de fournir des pr\u00e9visions d&rsquo;irradiance solaire probabilistes de haute qualit\u00e9.<\/strong><\/p>\n<h2>Qu&rsquo;est-ce que WRF-Solar ?<\/h2>\n<p>Alors que de plus en plus de syst\u00e8mes photovolta\u00efques (PV) sont install\u00e9s dans le monde entier, les <a href=\"https:\/\/reuniwatt.com\/fr\/previsions-solaires-au-lendemain-daycast\/\">pr\u00e9visions d&rsquo;\u00e9nergie solaire<\/a> intrajournali\u00e8re et journali\u00e8re deviennent de plus en plus importantes. Dans les mod\u00e8les de pr\u00e9vision num\u00e9rique du temps (PNT), le rayonnement solaire n\u2019est pas une variable essentielle, mais une variable diagnostique. En d&rsquo;autres termes, \u00e0 l&rsquo;origine les mod\u00e8les de pr\u00e9vision num\u00e9rique du temps n&rsquo;avaient pas \u00e9t\u00e9 con\u00e7us pour la pr\u00e9vision de l\u2019irradiance solaire.<\/p>\n<p>WRF-Solar est une am\u00e9lioration du mod\u00e8le WRF pour une simulation plus pr\u00e9cise de l&rsquo;interaction a\u00e9rosol-nuage-rayonnement. Au cours des derni\u00e8res ann\u00e9es, le mod\u00e8le weather research and forecasting (WRF) a \u00e9t\u00e9 augment\u00e9 et sp\u00e9cifiquement adapt\u00e9 pour mieux mod\u00e9liser l&rsquo;interaction des a\u00e9rosols, des nuages et du rayonnement <sup>1,2<\/sup>. De nombreuses am\u00e9liorations dans les sch\u00e9mas de param\u00e9trisation du mod\u00e8le WRF ont \u00e9t\u00e9 impl\u00e9ment\u00e9es <sup>3,4<\/sup>. Cela permet de r\u00e9duire consid\u00e9rablement l&rsquo;erreur de pr\u00e9vision de l&rsquo;irradiance solaire, en particulier dans les situations de ciel clair.<\/p>\n<h2>Qu&rsquo;est-ce que le WRF-Solar Ensemble Prediction System (EPS)?<\/h2>\n<p>WRF-Solar EPS est une extension des composants WRF-Solar du mod\u00e8le WRF. Il introduit des perturbations stochastiques dans les variables de param\u00e9trisation les plus pertinentes pour le rayonnement solaire arrivant au sol. Ces variables ont \u00e9t\u00e9 identifi\u00e9es avec des mod\u00e8les lin\u00e9aires tangents. Les m\u00e9thodes de perturbation stochastique dans cet outil de pr\u00e9vision de pointe sont sp\u00e9cialement choisies pour tenir compte des incertitudes de repr\u00e9sentation dans les processus de nuages, d&rsquo;a\u00e9rosols et de rayonnement <sup>5<\/sup>. Un syst\u00e8me de pr\u00e9diction d&rsquo;ensemble de haute qualit\u00e9 comme WRF-Solar EPS nous permet d&rsquo;identifier et de quantifier les ressources d&rsquo;\u00e9nergie solaire, car chaque membre de l&rsquo;ensemble repr\u00e9sente un \u00e9tat futur possible. La propagation d&rsquo;ensemble peut \u00eatre utilis\u00e9e pour \u00e9valuer la plage et l&rsquo;incertitude des pr\u00e9visions d&rsquo;\u00e9nergie solaire et conduire \u00e0 une meilleure pr\u00e9vision probabiliste de l&rsquo;irradiance solaire.<\/p>\n<p>Ce graphique interactif montre un exemple d&rsquo;irradiance horizontale globale (GHI) telle que pr\u00e9dite par WRF-Solar EPS pour Lindenberg (Allemagne) le 4 mars 2022. WRF est configur\u00e9 sur deux domaines : un avec un espacement de grille horizontal de 9 km, et un domaine imbriqu\u00e9 avec un pas de grille de 3 km. La propagation de l&rsquo;ensemble \u00e0 5 membres diff\u00e8re d&rsquo;un domaine \u00e0 l&rsquo;autre. Les observations proviennent du portail Open Data du DWD.<\/p>\n<\/div><div>                        <script type=\"text\/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};<\/script>\n        <script src=\"https:\/\/cdn.plot.ly\/plotly-latest.min.js\"><\/script>                <div id=\"9a15e8b4-d6b5-497d-a92b-988e517a3d76\" class=\"plotly-graph-div\" style=\"height:100%; width:100%;\"><\/div>            <script type=\"text\/javascript\">                                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById(\"9a15e8b4-d6b5-497d-a92b-988e517a3d76\")) {                    Plotly.newPlot(                        \"9a15e8b4-d6b5-497d-a92b-988e517a3d76\",                        [{\"mode\": \"lines\", \"name\": \"WRF-Solar EPS mean 3km, RMSE = 22\", \"type\": \"scatter\", \"x\": [\"2022-03-04T00:00:00+00:00\", \"2022-03-04T00:15:00+00:00\", \"2022-03-04T00:30:00+00:00\", \"2022-03-04T00:45:00+00:00\", 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            <\/script>        <\/div><div class=\"fusion-text fusion-text-2\" style=\"--awb-text-transform:none;\"><h2>Pr\u00e9visions de couverture nuageuse multicouche<\/h2>\n<p>Un mod\u00e8le de pr\u00e9vision num\u00e9rique du temps est une traduction d&rsquo;\u00e9quations physiques en code informatique. Comme les processus dans l&rsquo;atmosph\u00e8re varient de quelques secondes \u00e0 plusieurs jours et de nanom\u00e8tres \u00e0 kilom\u00e8tres, les mod\u00e8les m\u00e9t\u00e9orologiques incluent de nombreuses estimations, approximations et omissions. Le mod\u00e8le est toujours limit\u00e9 par sa r\u00e9solution, qui d\u00e9finit les processus les plus petits et les plus fugaces qui sont r\u00e9solus. WRF permet d&rsquo;imbriquer des domaines, ce qui signifie qu&rsquo;un domaine haute r\u00e9solution imbriqu\u00e9 est initialis\u00e9 \u00e0 l&rsquo;int\u00e9rieur d&rsquo;un domaine avec un espacement de grille plus grossier. Par cons\u00e9quent, m\u00eame avec des co\u00fbts de calcul relativement faibles, une pr\u00e9vision r\u00e9gionale \u00e0 haute r\u00e9solution peut \u00eatre obtenue et les processus de nuage et de convection \u00e0 petite \u00e9chelle peuvent \u00eatre calcul\u00e9s par le mod\u00e8le.<\/p>\n<p>L&rsquo;animation montre un exemple de pr\u00e9vision de couverture nuageuse WRF (nuages hauts, moyens et bas) en Europe centrale avec la m\u00eame configuration \u00e0 deux domaines. Le domaine de droite est imbriqu\u00e9 dans le domaine de gauche, ce qui signifie qu&rsquo;il ne s&rsquo;agit pas d&rsquo;un simple zoom. Tous les processus physiques sont en fait calcul\u00e9s sur la r\u00e9solution la plus \u00e9lev\u00e9e et les conditions aux limites sont donn\u00e9es par l&rsquo;autre domaine. Les conditions initiales et aux limites pour le domaine de gauche sont donn\u00e9es par le Global Forecast System (GFS), pilot\u00e9 par la NOAA. Notez la diff\u00e9rence entre les deux domaines en termes de nuages \u00e0 petite \u00e9chelle. Les modifications WRF-Solar des sch\u00e9mas de param\u00e9trisation conduisent \u00e0 des champs de nuages \u00e0 haute r\u00e9solution beaucoup plus r\u00e9alistes.<\/p>\n<\/div><div class=\"fusion-video fusion-youtube\" style=\"--awb-max-width:1000px;--awb-max-height:563px;--awb-align-self:center;--awb-width:100%;\"><div class=\"video-shortcode\"><div class=\"fluid-width-video-wrapper\" style=\"padding-top:56.3%;\" ><iframe title=\"YouTube video player 1\" src=\"https:\/\/www.youtube.com\/embed\/cHU1JayE_cw?wmode=transparent&autoplay=0\" width=\"1000\" height=\"563\" allowfullscreen allow=\"autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture;\"><\/iframe><\/div><\/div><\/div><div class=\"fusion-text fusion-text-3\" style=\"--awb-text-transform:none;\"><h2>Comparaison du masque nuageux entre WRF et satellite<\/h2>\n<p>L&rsquo;\u00e9valuation de la capacit\u00e9 d&rsquo;un mod\u00e8le PNT \u00e0 pr\u00e9dire correctement un \u00e9tat futur est appel\u00e9e v\u00e9rification. Surtout avec les pr\u00e9visions de nuages, la quantification de la qualit\u00e9 des pr\u00e9visions au niveau spatial est essentielle pour \u00e9valuer les performances du mod\u00e8le. Chez Reuniwatt, nous calculons un masque de nuage \u00e0 partir des pr\u00e9visions WRF et WRF-Solar et pouvons le comparer \u00e0 un masque de nuage obtenu par satellite. Ces observations t\u00e9l\u00e9d\u00e9tect\u00e9es aident \u00e0 cr\u00e9er une statistique \u00ab\u00a0hit-or-miss\u00a0\u00bb sur laquelle nous pouvons baser diff\u00e9rentes mesures et calculs de performance.<\/p>\n<p>La figure montre un exemple de pr\u00e9vision de masque de nuages WRF \u00e0 un espacement de grille de 3 km par rapport \u00e0 un masque de nuages obtenu par satellite. Le diagramme de diff\u00e9rence r\u00e9v\u00e8le les zones dans lesquelles les nuages sont pr\u00e9sents ou absents \u00e0 la fois dans WRF et le satellite, ainsi que la pr\u00e9sence de nuages dans l&rsquo;un ou l&rsquo;autre, WRF ou satellite.<\/p>\n<\/div><div class=\"fusion-image-element \" style=\"text-align:center;--awb-caption-title-font-family:var(--h2_typography-font-family);--awb-caption-title-font-weight:var(--h2_typography-font-weight);--awb-caption-title-font-style:var(--h2_typography-font-style);--awb-caption-title-size:var(--h2_typography-font-size);--awb-caption-title-transform:var(--h2_typography-text-transform);--awb-caption-title-line-height:var(--h2_typography-line-height);--awb-caption-title-letter-spacing:var(--h2_typography-letter-spacing);\"><span class=\" fusion-imageframe imageframe-none imageframe-1 hover-type-none\"><img decoding=\"async\" width=\"700\" height=\"1023\" alt=\"WRF-Solar Pr\u00e9vision de la couverture nuageuse\" title=\"WRF-Solar Pr\u00e9vision de la couverture nuageuse\" src=\"https:\/\/reuniwatt.com\/fr\/wp-content\/uploads\/sites\/2\/2022\/07\/WRF-Solar_Prevision_de_la_couverture_nuageuse.jpg\" class=\"img-responsive wp-image-13124\" srcset=\"https:\/\/reuniwatt.com\/fr\/wp-content\/uploads\/sites\/2\/2022\/07\/WRF-Solar_Prevision_de_la_couverture_nuageuse-200x292.jpg 200w, https:\/\/reuniwatt.com\/fr\/wp-content\/uploads\/sites\/2\/2022\/07\/WRF-Solar_Prevision_de_la_couverture_nuageuse-400x585.jpg 400w, https:\/\/reuniwatt.com\/fr\/wp-content\/uploads\/sites\/2\/2022\/07\/WRF-Solar_Prevision_de_la_couverture_nuageuse-600x877.jpg 600w, https:\/\/reuniwatt.com\/fr\/wp-content\/uploads\/sites\/2\/2022\/07\/WRF-Solar_Prevision_de_la_couverture_nuageuse.jpg 700w\" sizes=\"(max-width: 640px) 100vw, 700px\" \/><\/span><\/div><div class=\"fusion-text fusion-text-4\" style=\"--awb-text-transform:none;\"><h3>R\u00e9f\u00e9rences<\/h3>\n<ol>\n<li>Haupt, S. E., Kosovic, B., Jensen, T. L., Lee, J., Jimenez Munoz, P., Lazo, J. K., \u2026 Hinkleman, L. (2016). <em>The Sun4Cast\u00ae Solar Power Forecasting System: The Result of the Public-Private-Academic Partnership to Advance Solar Power Forecasting<\/em> (No. NCAR\/TN-526+STR). doi:10.5065\/D6N58JR2.<\/li>\n<li>Jimenez, P.A., J. P. Hacker, J. Dudhia, S. E. Haupt, J. A. Ruiz-Arias, C. A. Gueymard, G. Thompson, T. Eidhammer and A. Deng, 2016a: WRF-Solar: Description and Clear-Sky Assessment of an Augmented NWP Model for Solar Power Prediction. <em>Bull. Amer. Met. Soc.<\/em>.\u00a0<strong>97<\/strong>, 1249-1264. doi:10.1175\/BAMS-D-14-00279.1.<\/li>\n<li>Ruiz-Arias, J.A., J. Dudhia and C. A. Gueymard, 2014: A simple parameterization of the short-wave aerosol optical properties for surface direct and diffuse irradiances assessment in a numerical weather model.\u00a0<em>Geosci., Model Devel.<\/em>,\u00a0<strong>7<\/strong>, 1159-1174.<\/li>\n<li>Xie, Yu, M. Sengupta, J. Dudhia, 2016: A Fast-sky Radiation model for Solar applications (FARMS): Algorithm and performance evaluation.\u00a0<em>Solar Energy<\/em>,\u00a0<strong>135<\/strong>, 435-445.<\/li>\n<li>J. -H. Kim\u00a0<em>et al<\/em>., \u00ab\u00a0The WRF-Solar Ensemble Prediction System to Provide Solar Irradiance Probabilistic Forecasts,\u00a0\u00bb in\u00a0<em>IEEE Journal of Photovoltaics<\/em>, vol. 12, no. 1, pp. 141-144, Jan. 2022, doi: 10.1109\/JPHOTOV.2021.3117904.<\/li>\n<\/ol>\n<\/div><div style=\"text-align:center;\"><a class=\"fusion-button button-flat fusion-button-default-size button-default fusion-button-default button-1 fusion-button-default-span fusion-button-default-type\" target=\"_self\" href=\"https:\/\/reuniwatt.com\/fr\/contact\/\"><span class=\"fusion-button-text awb-button__text awb-button__text--default\">Nous contacter<\/span><\/a><\/div><\/div><\/div><\/div><\/div>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":12,"featured_media":13130,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"content-type":"","_eb_attr":"","footnotes":""},"categories":[32],"tags":[],"class_list":["post-13123","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-actu-industrie"],"_links":{"self":[{"href":"https:\/\/reuniwatt.com\/fr\/wp-json\/wp\/v2\/posts\/13123","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/reuniwatt.com\/fr\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/reuniwatt.com\/fr\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/reuniwatt.com\/fr\/wp-json\/wp\/v2\/users\/12"}],"replies":[{"embeddable":true,"href":"https:\/\/reuniwatt.com\/fr\/wp-json\/wp\/v2\/comments?post=13123"}],"version-history":[{"count":4,"href":"https:\/\/reuniwatt.com\/fr\/wp-json\/wp\/v2\/posts\/13123\/revisions"}],"predecessor-version":[{"id":13128,"href":"https:\/\/reuniwatt.com\/fr\/wp-json\/wp\/v2\/posts\/13123\/revisions\/13128"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/reuniwatt.com\/fr\/wp-json\/wp\/v2\/media\/13130"}],"wp:attachment":[{"href":"https:\/\/reuniwatt.com\/fr\/wp-json\/wp\/v2\/media?parent=13123"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/reuniwatt.com\/fr\/wp-json\/wp\/v2\/categories?post=13123"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/reuniwatt.com\/fr\/wp-json\/wp\/v2\/tags?post=13123"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}