{"id":2522,"date":"2016-01-21T12:11:43","date_gmt":"2016-01-21T12:11:43","guid":{"rendered":"http:\/\/www.iic.uam.es\/\/?page_id=2522"},"modified":"2016-02-22T11:39:29","modified_gmt":"2016-02-22T11:39:29","slug":"kernel-en","status":"publish","type":"page","link":"https:\/\/www.iic.uam.es\/en\/big-data-services\/energy-environment\/kernel-en\/","title":{"rendered":"Kernel EA2"},"content":{"rendered":"[vc_row type=&#8221;full_width_section&#8221; top_padding=&#8221;-10&#8243;][vc_column width=&#8221;1\/1&#8243;][vc_column_text]\n<div id=\"rev_slider_111_1_wrapper\" class=\"rev_slider_wrapper fullwidthbanner-container\" style=\"margin:0px auto;background-color:transparent;padding:0px;margin-top:0px;margin-bottom:0px;\">\n<!-- START REVOLUTION SLIDER 5.0.9 fullwidth mode -->\n\t<div id=\"rev_slider_111_1\" class=\"rev_slider fullwidthabanner\" style=\"display:none;\" data-version=\"5.0.9\">\n<ul>\t<!-- SLIDE  -->\n\t<li data-index=\"rs-152\" data-transition=\"fade\" data-slotamount=\"default\"  data-easein=\"default\" data-easeout=\"default\" data-masterspeed=\"default\"  data-rotate=\"0\"  data-saveperformance=\"off\"  data-title=\"Slide\" data-description=\"\">\n\t\t<!-- MAIN IMAGE -->\n\t\t<img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.iic.uam.es\/wp-content\/uploads\/2015\/12\/cabecera_KERNL.jpg\"  alt=\"\"  width=\"1903\" height=\"300\" data-bgposition=\"center center\" data-bgfit=\"cover\" data-bgrepeat=\"no-repeat\" class=\"rev-slidebg\" data-no-retina>\n\t\t<!-- LAYERS -->\n\n\t\t<!-- LAYER NR. 1 -->\n\t\t<div class=\"tp-caption Fashion-BigDisplay   tp-resizeme\" \n\t\t\t id=\"slide-152-layer-1\" \n\t\t\t data-x=\"center\" data-hoffset=\"-1\" \n\t\t\t data-y=\"center\" data-voffset=\"-54\" \n\t\t\t\t\t\tdata-width=\"['880']\"\n\t\t\tdata-height=\"['70']\"\n\t\t\tdata-transform_idle=\"o:1;\"\n \n\t\t\t data-transform_in=\"opacity:0;s:300;e:Power2.easeInOut;\" \n\t\t\t data-transform_out=\"opacity:0;s:300;s:300;\" \n\t\t\tdata-start=\"500\" \n\t\t\tdata-splitin=\"none\" \n\t\t\tdata-splitout=\"none\" \n\t\t\tdata-responsive_offset=\"on\" \n\n\t\t\t\n\t\t\tstyle=\"z-index: 5; 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For example, when applied to solar technology, forecasts may be made for a single plant, for a set of plants contained in a farm, or for wider areas such as the Iberian Peninsula.<\/p>\n[\/vc_column_text][\/vc_column][\/vc_row][vc_row bg_color=&#8221;#ffffff&#8221; top_padding=&#8221;40&#8243; bottom_padding=&#8221;20&#8243;][vc_column width=&#8221;1\/1&#8243;][vc_column_text]\n<h3 style=\"text-align: center;\"><span style=\"color: #9f1700;\">Benefits<\/span><\/h3>\n<p style=\"text-align: center; font-size: 23px;\"><span style=\"color: #bbbbbb;\">Kernel EA2 advantages lie in the fact that: <\/span><\/p>\n[\/vc_column_text][\/vc_column][\/vc_row][vc_row bg_color=&#8221;#ffffff&#8221; top_padding=&#8221;40&#8243; bottom_padding=&#8221;20&#8243;][vc_column width=&#8221;1\/2&#8243;]<div class=\"iconbox  wpb_content_element iconbox-style-1 icon-color-accent color-dark\"><h3><i class=\"fa sl-settings boxicon\" style=\"\"><\/i>It uses 100% IIC technology<\/h3><p>\n<p style=\"text-align: justify;\">It uses 100% IIC technology; it is a result of our expertise.<\/p>\n<\/p><\/div><div class=\"spacer\" style=\"height: 50px;\"><\/div><div class=\"iconbox  wpb_content_element iconbox-style-1 icon-color-accent color-dark\"><h3><i class=\"fa sl-compass boxicon\" style=\"\"><\/i>It can be adjusted to clients\u2019 demand<\/h3><p>\n<p style=\"text-align: justify;\">It can be adjusted to clients\u2019 demands and integrated into other applications.<\/p>\n<\/p><\/div><div class=\"spacer\" style=\"height: 50px;\"><\/div><div class=\"iconbox  wpb_content_element iconbox-style-1 icon-color-accent color-dark\"><h3><i class=\"fa sl-equalizer boxicon\" style=\"\"><\/i>It is based on easily customizable models<\/h3><p>\n<p style=\"text-align: justify;\">It is based on easily customizable models, adaptable to the evolution of predictive variables used.<\/p>\n<\/p><\/div>[\/vc_column][vc_column width=&#8221;1\/2&#8243;]<div class=\"single_image wpb_content_element align-center \" data-animation=\"none\" data-delay=\"\"><img decoding=\"async\" src=\"https:\/\/www.iic.uam.es\/wp-content\/uploads\/2015\/11\/EA2_01.png\" alt=\"\" \/><\/div><div class=\"iconbox  wpb_content_element iconbox-style-1 icon-color-accent color-dark\"><h3><i class=\"fa sl-layers boxicon\" style=\"\"><\/i>It may be applied to any data source<\/h3><p>\n<p style=\"text-align: justify;\">It may be applied to any data source offering results at any level of disaggregation.<\/p>\n<\/p><\/div>[\/vc_column][\/vc_row][vc_row type=&#8221;full_width_section&#8221; bg_color=&#8221;#ffffff&#8221;][vc_column width=&#8221;1\/1&#8243;]<div class=\"divider divider1\" style='margin:1px 0 0px 0 !important;'><\/div>[\/vc_column][\/vc_row][vc_row top_padding=&#8221;40&#8243; bottom_padding=&#8221;40&#8243;][vc_column width=&#8221;1\/1&#8243;][vc_tabs][vc_tab title=&#8221;Guaranteed efficiency&#8221; tab_id=&#8221;f2edc2fa-a528-8&#8243;][vc_row_inner][vc_column_inner width=&#8221;2\/6&#8243;][vc_column_text]\n<h3 style=\"text-align: left;\"><span style=\"color: #9f1700;\">Guaranteed efficiency [\/vc_column_text][\/vc_column_inner][vc_column_inner width=&#8221;4\/6&#8243;][vc_column_text]\n<\/span><\/h3>\n<p style=\"text-align: justify;\">IIC has a long history developing and deploying <strong>advanced algorithms<\/strong> such as statistic models, neural networks, Support Vector Machines (SVM), clustering tools and some other <strong>machine learning<\/strong> techniques.<\/p>\n<p style=\"text-align: justify;\">The Kernel EA2 algorithm approximations, carried out by the <strong>IIC team of experts<\/strong> on these techniques, are adapted, enhanced and renewed according to the needs arising from the locations forecasts were made for: small installations, solar orchards, etc.<\/p>\n[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][\/vc_tab][vc_tab title=&#8221;Why invest in Kernel EA2?&#8221; tab_id=&#8221;1450806263940-1-10&#8243;][vc_row_inner][vc_column_inner width=&#8221;2\/6&#8243;][vc_column_text]\n<h3 style=\"text-align: left;\"><span style=\"color: #9f1700;\">Why invest in Kernel EA2?<\/span><\/h3>\n[\/vc_column_text][\/vc_column_inner][vc_column_inner width=&#8221;4\/6&#8243;][vc_column_text]\n<p style=\"text-align: justify;\">Selling or buying energy at the <strong>electric market<\/strong> requires hourly production forecasts a day in advance, since photovoltaic plants or suppliers, as any market participant, must <strong>pay a penalty<\/strong> for deviations generated, i.e., for the difference between the offer made to the market and the amount actually produced, if the system is not benefited.<\/p>\n<p style=\"text-align: justify;\">Therefore, it is clear that an accurate forecast would involve a direct economic reward as <strong>deviation charges would be reduced<\/strong>. Acquiring a reliable and accurate model means counting on an extremely <strong>useful and particularly redeemable<\/strong> tool both for the market and the plant maintenance, directly impacting the economy of agents.<\/p>\n[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][\/vc_tab][\/vc_tabs][\/vc_column][\/vc_row][vc_row bg_color=&#8221;#f1f1f1&#8243; top_padding=&#8221;40&#8243; bottom_padding=&#8221;40&#8243;][vc_column width=&#8221;1\/1&#8243;][vc_column_text]\n<h3 style=\"text-align: center;\"><span style=\"color: #9f1700;\">Solutions implemented so far<\/span><\/h3>\n[\/vc_column_text][vc_row_inner][vc_column_inner width=&#8221;1\/2&#8243;][vc_column_text]\n<p style=\"text-align: justify;\">As far as functioning is concerned, Kernel EA2 may be applied in virtually <strong>any area of the world<\/strong>, using any data source and refreshing according to the latency required by the information, at any level of disaggregation.<\/p>\n[\/vc_column_text][\/vc_column_inner][vc_column_inner width=&#8221;1\/2&#8243;][vc_column_text]\n<p style=\"text-align: justify;\">Kernel EA2 has been specially developed for Transmission System Operators (TSO), Distribution System Operators (DSO), energy generators, energy suppliers, companies related to <strong>energy efficiency<\/strong> and, in general, agents related to Smart Grids.<\/p>\n[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][vc_row bg_color=&#8221;#2b99cc&#8221; text_color=&#8221;light&#8221; top_padding=&#8221;15&#8243; bottom_padding=&#8221;15&#8243;][vc_column width=&#8221;1\/1&#8243;][vc_raw_html]JTNDcCUyMHN0eWxlJTNEJTIybGluZS1oZWlnaHQlM0ElMjAyOHB4JTNCJTIwZm9udC13ZWlnaHQlM0ElMjAxMDAlM0IlMjBmb250LWZhbWlseSUzQSUyME9wZW4lMjBTYW5zJTNCJTIwZm9udC1zaXplJTNBJTIwMjBweCUzQiUyMHRleHQtYWxpZ24lM0ElMjBjZW50ZXIlM0IlMjIlM0VBY2N1cmF0ZSUyMGZvcmVjYXN0cyUyMGludm9sdmUlMjBhJTIwZGlyZWN0JTIwZWNvbm9taWMlMjByZXdhcmQlMjBhcyUyMGRldmlhdGlvbiUyMGNoYXJnZXMlMjB3b3VsZCUyMGJlJTIwcmVkdWNlZC4lM0MlMkZwJTNF[\/vc_raw_html][\/vc_column][\/vc_row][vc_row bg_image=&#8221;2082&#8243; top_padding=&#8221;40&#8243; bottom_padding=&#8221;40&#8243;][vc_column width=&#8221;1\/1&#8243;][vc_column_text]\n<p style=\"text-align: center;\"><a href=\"\/en\/more-information\/\" target=\"_self\" class=\"button color-8 large \" style=\"border-radius: 2px;\">MORE INFORMATION<\/a>\n[\/vc_column_text][\/vc_column][\/vc_row]\n","protected":false},"excerpt":{"rendered":"<p>[vc_row type=&#8221;full_width_section&#8221; top_padding=&#8221;-10&#8243;][vc_column width=&#8221;1\/1&#8243;][vc_column_text][\/vc_column_text][\/vc_column][\/vc_row][vc_row top_padding=&#8221;30&#8243; bottom_padding=&#8221;30&#8243;][vc_column width=&#8221;1\/1&#8243;][vc_column_text] The key to observe and understand what is happening and predict what the future holds is counting on a good organization of data, a wide set of modelling tools and a long experience analysing results of predictive models. Our experience has been applied to Smart Grids, a way of managing electricity efficiently, optimizing generation and distribution and using information technology with the aim of balancing supply and demand between producers and consumers. This is the environment where modelling tools, such as Kernel EA2, are used to cover different needs. [\/vc_column_text][\/vc_column][\/vc_row][vc_row bg_color=&#8221;#f1f1f1&#8243; top_padding=&#8221;40&#8243; bottom_padding=&#8221;40&#8243;][vc_column width=&#8221;1\/2&#8243;][vc_column_text] What is Kernel EA2?[\/vc_column_text][vc_column_text] The Kernel EA2 predictive models library is used at the core of IIC products related to wind and solar renewable energy forecast, as well as in other systems and services related to modelling and energy forecasting. Kernel EA2 allows including powerful predictive models \u2015based on neural networks or Support Vector Machines (SVM), among others\u2015 into general Data Mining systems easily and flexibly. [\/vc_column_text][\/vc_column][vc_column width=&#8221;1\/2&#8243;][vc_column_text] How does Kernel EA2 work?[\/vc_column_text][vc_column_text] Kernel EA2 applies predictive analytics techniques to offer precise forecasts that may be integrated into systems such as the applications used by TSOs. It has also [&hellip;]<\/p>\n","protected":false},"author":4,"featured_media":0,"parent":2513,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-2522","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v23.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Kernel EA2 - IIC<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.iic.uam.es\/en\/big-data-services\/energy-environment\/kernel-en\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Kernel EA2 - IIC\" \/>\n<meta property=\"og:description\" content=\"[vc_row type=&#8221;full_width_section&#8221; top_padding=&#8221;-10&#8243;][vc_column width=&#8221;1\/1&#8243;][vc_column_text][\/vc_column_text][\/vc_column][\/vc_row][vc_row top_padding=&#8221;30&#8243; bottom_padding=&#8221;30&#8243;][vc_column width=&#8221;1\/1&#8243;][vc_column_text] The key to observe and understand what is happening and predict what the future holds is counting on a good organization of data, a wide set of modelling tools and a long experience analysing results of predictive models. Our experience has been applied to Smart Grids, a way of managing electricity efficiently, optimizing generation and distribution and using information technology with the aim of balancing supply and demand between producers and consumers. This is the environment where modelling tools, such as Kernel EA2, are used to cover different needs. [\/vc_column_text][\/vc_column][\/vc_row][vc_row bg_color=&#8221;#f1f1f1&#8243; top_padding=&#8221;40&#8243; bottom_padding=&#8221;40&#8243;][vc_column width=&#8221;1\/2&#8243;][vc_column_text] What is Kernel EA2?[\/vc_column_text][vc_column_text] The Kernel EA2 predictive models library is used at the core of IIC products related to wind and solar renewable energy forecast, as well as in other systems and services related to modelling and energy forecasting. Kernel EA2 allows including powerful predictive models \u2015based on neural networks or Support Vector Machines (SVM), among others\u2015 into general Data Mining systems easily and flexibly. [\/vc_column_text][\/vc_column][vc_column width=&#8221;1\/2&#8243;][vc_column_text] How does Kernel EA2 work?[\/vc_column_text][vc_column_text] Kernel EA2 applies predictive analytics techniques to offer precise forecasts that may be integrated into systems such as the applications used by TSOs. 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