{"id":2513,"date":"2016-01-21T11:44:42","date_gmt":"2016-01-21T11:44:42","guid":{"rendered":"http:\/\/www.iic.uam.es\/\/?page_id=2513"},"modified":"2017-07-11T12:56:11","modified_gmt":"2017-07-11T10:56:11","slug":"energy-environment","status":"publish","type":"page","link":"https:\/\/www.iic.uam.es\/en\/big-data-services\/energy-environment\/","title":{"rendered":"Energy Environment"},"content":{"rendered":"[vc_row type=&#8221;full_width_section&#8221; top_padding=&#8221;-10&#8243;][vc_column width=&#8221;1\/1&#8243; delay=&#8221;500&#8243;][vc_column_text]\n<div id=\"rev_slider_108_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_108_1\" class=\"rev_slider fullwidthabanner\" style=\"display:none;\" data-version=\"5.0.9\">\n<ul>\t<!-- SLIDE  -->\n\t<li data-index=\"rs-149\" 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\/2016\/01\/cabecera_Energetico1.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-149-layer-1\" \n\t\t\t data-x=\"center\" data-hoffset=\"1\" \n\t\t\t data-y=\"center\" data-voffset=\"-51\" \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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Utilising this knowledge in <a href=\"\/en\/big-data\/\">Big Data<\/a>, we collaborate with Energy companies<strong> treating and analysing the high amount of data<\/strong> they generate and store every day.<\/p>\n<p style=\"text-align: justify;\">Analysing all these data, <strong>identifying behaviour patterns<\/strong> and generating forecasts on their basis are vital, as <strong>efficiency<\/strong> of services might be improved and it helps companies to make decisions, besides reducing costs. This is the focus of our services and our solutions \u2014EA2, Kernel EA2 and ArgestesPlanner\u2014 in the Energy sector.<\/p>\n[\/vc_column_text][\/vc_column][\/vc_row][vc_row type=&#8221;full_width_section&#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 bg_color=&#8221;#f1f1f1&#8243; top_padding=&#8221;40&#8243; bottom_padding=&#8221;20&#8243;][vc_column animation=&#8221;fade-in-from-bottom&#8221; width=&#8221;1\/1&#8243; delay=&#8221;500&#8243;][vc_column_text]\n<h3 style=\"text-align: center;\"><span style=\"color: #9f1700;\">Renewable Energy Production Forecast[\/vc_column_text][vc_column_text]\n<\/span><\/h3>\n<p style=\"text-align: center;\">We generate forecasts on the basis of weather forecast data and renewable energy production data (wind, solar PV and thermosolar energy). They may be applied both in a single park and in wider areas. Service may be provided all over the world.[\/vc_column_text][\/vc_column][\/vc_row][vc_row bg_color=&#8221;#f1f1f1&#8243; top_padding=&#8221;0&#8243; bottom_padding=&#8221;20&#8243;][vc_column animation=&#8221;fade-in-from-bottom&#8221; text_align=&#8221;center&#8221; width=&#8221;1\/2&#8243; delay=&#8221;500&#8243;][vc_column_text]\n<p style=\"text-align: justify;\">Our systems to predict energy production make it possible for companies producing or managing renewable energy to make market operators <strong>accurate offers of generation<\/strong> and plan regular maintenance.<\/p>\n[\/vc_column_text][vc_row_inner][vc_column_inner]<div class=\"single_image wpb_content_element align-center \" data-animation=\"none\" data-delay=\"\"><a href=\"\/en\/big-data-services\/energy-environment\/ea2-en\/\" ><img decoding=\"async\" src=\"https:\/\/www.iic.uam.es\/wp-content\/uploads\/2015\/11\/Ent_Energia_Ea2.png\" alt=\"\" \/><\/a><\/div>[vc_column_text]\n<p style=\"text-align: center; font-size: 18px; line-height: 20px;\"><span style=\"color: #878787;\">Wind power production forecast system<\/span><\/p>\n[\/vc_column_text]<a href=\"\/en\/big-data-services\/energy-environment\/ea2-en\/\" target=\"_self\" class=\"button blue small \" style=\"border-radius: 2px;\">EA2<\/a>[\/vc_column_inner][\/vc_row_inner][\/vc_column][vc_column text_align=&#8221;center&#8221; width=&#8221;1\/2&#8243;][vc_column_text]\n<p style=\"text-align: justify;\">Both <a href=\"\/en\/big-data-services\/energy-environment\/ea2-en\/\">EA2<\/a>, our system designed to <strong>forecast wind power production<\/strong>, and <a href=\"\/en\/big-data-services\/energy-environment\/kernel-en\/\">Kernel EA2<\/a>, for solar energy, are effective applications for Transmission System Operators (TSO), since they help them make more precise generations, ensuring that demand is met and guaranteeing the system\u2019s stability.<\/p>\n[\/vc_column_text][vc_row_inner][vc_column_inner]<div class=\"single_image wpb_content_element align-center \" data-animation=\"none\" data-delay=\"\"><a href=\"\/en\/big-data-services\/energy-environment\/kernel-en\/\" ><img decoding=\"async\" src=\"https:\/\/www.iic.uam.es\/wp-content\/uploads\/2015\/11\/Ent_Energia_Kernel-Ea2.png\" alt=\"\" \/><\/a><\/div>[vc_column_text]\n<p style=\"text-align: center; 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font-weight: 100; color: rgba(255, 255, 255, 1.00);font-family:OPEN SANS;text-align:center;\">The service consists in taking advantage of data collected in real time by several different sensors with the aim of alerting about incidences or determining unusual behaviour patterns. 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These forecasts might be generated for any kind of energy, although so far they have been primarily used for renewable energy.<\/p>\n<p style=\"text-align: justify;\">In addition, we offer a service, consisting on a <strong>combination of forecasts<\/strong>, which generates <strong>high quality prediction<\/strong> using data from different agents.<\/p>\n[\/vc_column_text][\/vc_column][\/vc_row][vc_row bg_color=&#8221;#f1f1f1&#8243; text_align=&#8221;center&#8221; top_padding=&#8221;40&#8243; bottom_padding=&#8221;20&#8243;][vc_column animation=&#8221;fade-in-from-bottom&#8221; width=&#8221;1\/2&#8243; delay=&#8221;500&#8243;][vc_row_inner][vc_column_inner width=&#8221;2\/6&#8243;][\/vc_column_inner][vc_column_inner width=&#8221;4\/6&#8243;]<div class=\"single_image wpb_content_element align-center \" data-animation=\"none\" data-delay=\"\"><a href=\"\/en\/big-data-services\/energy-environment\/demand-forecast-service\/\" ><img decoding=\"async\" src=\"https:\/\/www.iic.uam.es\/wp-content\/uploads\/2015\/11\/Ent_Energia_Demanada_Elect.png\" alt=\"\" \/><\/a><\/div>[vc_column_text]\n<p style=\"text-align: center; font-size: 18px; line-height: 20px;\"><span style=\"color: #878787;\">The demand forecast service issues an hourly demand forecast of up to 10 days<\/span><\/p>\n[\/vc_column_text]<a href=\"\/en\/big-data-services\/energy-environment\/demand-forecast-service\/\" target=\"_self\" class=\"button blue small \" style=\"border-radius: 2px;\">Demand forecast service<\/a>[\/vc_column_inner][\/vc_row_inner][\/vc_column][vc_column animation=&#8221;fade-in-from-bottom&#8221; width=&#8221;1\/2&#8243;][vc_row_inner][vc_column_inner width=&#8221;4\/6&#8243;]<div class=\"single_image wpb_content_element align-center \" data-animation=\"none\" data-delay=\"\"><a href=\"\/en\/big-data-services\/energy-environment\/argestes-planner\/\" ><img decoding=\"async\" src=\"https:\/\/www.iic.uam.es\/wp-content\/uploads\/2015\/11\/Ent_Energia_Argestes.png\" alt=\"\" \/><\/a><\/div>[vc_column_text]\n<p style=\"text-align: center; font-size: 18px; line-height: 20px;\"><span style=\"color: #878787;\">Visualization system that shows several graphical representations of forecasts<\/span><\/p>\n[\/vc_column_text]<a href=\"\/en\/big-data-services\/energy-environment\/argestes-planner\/\" target=\"_self\" class=\"button blue small \" style=\"border-radius: 2px;\">Argestes Planner<\/a>[\/vc_column_inner][vc_column_inner width=&#8221;2\/6&#8243;][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][vc_row bg_color=&#8221;#ffffff&#8221; top_padding=&#8221;30&#8243;][vc_column][vc_column_text]\n<h3 style=\"text-align: center;\"><span style=\"color: #9f1700;\">Fraud Detection and Detection of Incidences on Electric Power Distribution Systems[\/vc_column_text][\/vc_column][\/vc_row][vc_row bg_color=&#8221;#ffffff&#8221; top_padding=&#8221;30&#8243; bottom_padding=&#8221;30&#8243;][vc_column animation=&#8221;fade-in-from-bottom&#8221; width=&#8221;1\/2&#8243; delay=&#8221;500&#8243;][vc_column_text]\n<\/span><\/h3>\n<p style=\"text-align: justify;\">Using structural information and historical consumption data from clients, the fraud detection system can <strong>detect fraud patterns<\/strong> in consumption data.<\/p>\n[\/vc_column_text][\/vc_column][vc_column animation=&#8221;fade-in-from-bottom&#8221; width=&#8221;1\/2&#8243;][vc_column_text]\n<p style=\"text-align: justify;\">Energy suppliers are provided with a ranking containing scores for particular clients, so they may decide whether installations must be <strong>visually checked<\/strong>, according to their own capacities.<\/p>\n[\/vc_column_text][\/vc_column][\/vc_row][vc_row bg_color=&#8221;#ffffff&#8221; text_align=&#8221;center&#8221; top_padding=&#8221;0&#8243; bottom_padding=&#8221;30&#8243;][vc_column animation=&#8221;fade-in-from-bottom&#8221; width=&#8221;1\/3&#8243; delay=&#8221;500&#8243;][\/vc_column][vc_column width=&#8221;1\/3&#8243;]<div class=\"single_image wpb_content_element align-center \" data-animation=\"none\" data-delay=\"\"><a href=\"\/en\/big-data-services\/energy-environment\/energy-fraud-detection\/\" ><img decoding=\"async\" src=\"https:\/\/www.iic.uam.es\/wp-content\/uploads\/2015\/11\/Ent_Energia_Detec_Fraudet.png\" alt=\"\" \/><\/a><\/div>[vc_column_text]\n<p style=\"text-align: center; font-size: 18px; line-height: 20px;\"><span style=\"color: #878787;\">Fraud detection services may be applied to different types of distribution, such as electricity or gas<\/span><\/p>\n[\/vc_column_text]<a href=\"\/en\/big-data-services\/energy-environment\/energy-fraud-detection\/\" target=\"_self\" class=\"button blue small \" style=\"border-radius: 2px;\">Energy fraud detection service<\/a>[\/vc_column][vc_column width=&#8221;1\/3&#8243;][\/vc_column][\/vc_row][vc_row type=&#8221;full_width_section&#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 bg_color=&#8221;#f1f1f1&#8243; top_padding=&#8221;40&#8243; bottom_padding=&#8221;20&#8243;][vc_column animation=&#8221;fade-in-from-bottom&#8221; width=&#8221;1\/3&#8243; delay=&#8221;500&#8243;][vc_column_text]\n<h3 style=\"text-align: left;\"><span style=\"color: #9f1700;\">Forecast and Simulation related to Electrical Vehicles[\/vc_column_text][vc_column_text]\n<\/span><\/h3>\n<p style=\"text-align: justify;\">Incorporating <strong>electrical vehicles<\/strong> to the system represents a major challenge, therefore if we want to deal with it efficiently, it would be very useful to count, on one side, on simulation scenarios on the long term; and, on the other side, on a way to <strong>forecast the charge<\/strong> a whole park of electrical vehicles might involve, on the short term.<\/p>\n<p style=\"text-align: justify;\">One example of this technology offered by IIC is the Simulator of Electrical Vehicle Recharge developed for REE, the sole Transmission System Operator (TSO) in Spain.<\/p>\n[\/vc_column_text][\/vc_column][vc_column animation=&#8221;fade-in-from-bottom&#8221; width=&#8221;1\/3&#8243;][vc_column_text]\n<h3 style=\"text-align: left;\"><span style=\"color: #9f1700;\">Demand Management[\/vc_column_text][vc_column_text]\n<\/span><\/h3>\n<p style=\"text-align: justify;\">Electrical system management must guarantee that demand is covered, and ensure the safety of the whole system. In this sense, <strong>Demand Management Tools<\/strong> are very useful as they allow, for instance, operating on the users\u2019 consumption, or making suggestions to them so that both the system and the user are benefited.<\/p>\n<p style=\"text-align: justify;\">At IIC we are experts on the development of <strong>applications for TSOs<\/strong> able to communicate this kind of actions to the operators responsible of their accomplishment.<\/p>\n[\/vc_column_text][\/vc_column][vc_column animation=&#8221;fade-in-from-bottom&#8221; width=&#8221;1\/3&#8243;][vc_column_text]\n<h3 style=\"text-align: left;\"><span style=\"color: #9f1700;\">Collaborations and associations[\/vc_column_text][vc_column_text]\n<\/span><\/h3>\n<p style=\"text-align: justify;\">We collaborate with UAM-IIC Data Science &amp; Machine Learning Chair <strong>to promote research<\/strong> in basic machine learning and computational intelligence issues and in their application to specific issues from our clients, emphasizing models of electric demand forecast, renewable energy generation and preventive detection of critical events in large systems.<\/p>\n<p style=\"text-align: justify;\">IIC also takes part in many Energy sector platforms. We are members of <strong>FutuRed<\/strong> (Spanish Electrical Grid Platform) and <strong>MadridNetwork<\/strong>, and take part in <strong>ReolTec<\/strong> (Spanish Wind Energy Technology Platform) and the conferences held by <strong>CIGRE<\/strong> (Council on Large Electric Systems) and <strong>EWEA<\/strong> (European Wind Energy Association).<\/p>\n[\/vc_column_text][\/vc_column][\/vc_row][vc_row type=&#8221;full_width_section&#8221; 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; delay=&#8221;500&#8243;][vc_column_text][\/vc_column_text][\/vc_column][\/vc_row][vc_row bg_color=&#8221;#ffffff&#8221; top_padding=&#8221;30&#8243; bottom_padding=&#8221;30&#8243;][vc_column animation=&#8221;fade-in-from-bottom&#8221; width=&#8221;1\/1&#8243; delay=&#8221;500&#8243;][vc_column_text] Big Data in Energy [\/vc_column_text][\/vc_column][\/vc_row][vc_row bg_color=&#8221;#ffffff&#8221; top_padding=&#8221;0&#8243; bottom_padding=&#8221;40&#8243;][vc_column animation=&#8221;fade-in-from-bottom&#8221; width=&#8221;1\/2&#8243; delay=&#8221;500&#8243;][vc_column_text] Nowadays electrical grids are trying to meet expectations ranging from traditional generation to renewable resources, transport and distribution, but energy management might be still improved for all agents of the electric system. With the purpose of providing a safe, economic and sustainable electric supply, smart grids integrate information technologies with current infrastructure so they obtain a vast volume of data on the behaviour of all actors connected: who generates electricity, which TSO transports it and who the main consumers are. [\/vc_column_text][\/vc_column][vc_column animation=&#8221;fade-in-from-bottom&#8221; width=&#8221;1\/2&#8243;][vc_column_text] IIC has a long history developing and deploying advanced algorithms such as statistic models, neural networks, Support Vector Machines (SVM), clustering tools and some other machine learning techniques, as well as applying simulation techniques. Utilising this knowledge in Big Data, we collaborate with Energy companies treating and analysing the high amount of data they generate and store every day. Analysing all these data, identifying behaviour patterns and generating forecasts on their basis are vital, as efficiency of services might be improved and it helps companies to make decisions, besides reducing costs. This is the focus [&hellip;]<\/p>\n","protected":false},"author":4,"featured_media":0,"parent":2470,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-2513","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>Energy Environment - IIC<\/title>\n<meta name=\"description\" content=\"Long history developing and deploying advanced algorithms such as statistic models, neural networks, Support Vector Machines (SVM), clustering tools,...\" \/>\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\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Energy Environment - 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