{"id":1042,"date":"2025-03-19T09:40:00","date_gmt":"2025-03-19T08:40:00","guid":{"rendered":"https:\/\/fe-zvei.de\/pressemitteilung\/efficient-heating-with-ai-secai-reduces-energy-consumption-and-co%e2%82%82-emissions-by-up-to-18-percent\/"},"modified":"2025-10-23T16:10:55","modified_gmt":"2025-10-23T14:10:55","slug":"efficient-heating-with-ai-secai-reduces-energy-consumption-and-co%e2%82%82-emissions-by-up-to-18-percent","status":"publish","type":"pressemitteilung","link":"https:\/\/fe-zvei.de\/en\/press-release\/efficient-heating-with-ai-secai-reduces-energy-consumption-and-co%e2%82%82-emissions-by-up-to-18-percent\/","title":{"rendered":"Efficient heating with AI: SECAI reduces energy consumption and CO\u2082 emissions by up to 18 percent"},"content":{"rendered":"\n<p>Frankfurt, March 19, 2025 <\/p>\n\n<p>In Zeiten steigender Energiekosten und wachsender Klimaschutzanforderungen r\u00fcckt der Energieverbrauch in Wohngeb\u00e4uden in den Fokus: Rund 28 Prozent<a href=\"applewebdata:\/\/27020C66-FF5C-413C-8779-17020362B85F#_ftn1\"><sup>[1]<\/sup><\/a> des gesamten Energieverbrauchs in Deutschland entfallen beispielsweise auf private Haushalte, wobei etwa 70 Prozent<a href=\"applewebdata:\/\/27020C66-FF5C-413C-8779-17020362B85F#_ftn2\"><sup>[2]<\/sup><\/a> davon f\u00fcr Raumw\u00e4rme genutzt werden. Given this high proportion, optimising heating control offers enormous savings potential \u2013 both economically and ecologically. <\/p>\n\n<p>Here, the SECAI research project is using artificial intelligence (AI) for smart heating control. The innovative system analyzes sensor data from apartments in real time, combines it with weather forecasts, and regulates the heat supply in buildings individually and according to needs. This not only reduces heating costs but also CO\u2082 emissions, without compromising comfort for residents.   <\/p>\n\n<p>From March 17 to 21, 2025, the consortium leadership will demonstrate how these savings potentials can be realized using a demonstrator at the ISH in Frankfurt am Main at the wibutler booth (Hall 11.1, C88). The demonstrator incorporates a number of different parameters that influence the heating behavior in a building. It visualizes various assumptions regarding the configuration and integration of the heating system into the building.  <\/p>\n\n<p><strong>Save heating energy with AI<\/strong><\/p>\n\n<p>The project&#8217;s first heating period (October 2024 to March 2025) revealed that the flow temperature of heating systems is often set higher than necessary. A reduction of just 3\u00b0C \u200b\u200bcould reduce energy consumption by up to 18 percent \u2013 \u200b\u200ba huge savings potential. Furthermore, tenant behavior significantly influences the efficiency of heating systems. This is where SECAI comes in: Using digital &#8220;nudging&#8221; techniques, the system provides targeted advice to encourage energy-efficient behavior.   <\/p>\n\n<p>&#8220;AI-supported heating optimization offers benefits for everyone involved: Residential complex operators receive automated, optimized heating plans that reduce energy consumption and save costs. Tenants can adjust their individual comfort needs via the SECAI app and receive valuable tips for reducing their energy consumption,&#8221; says Dr. Florian Remark, partner at Strategion GmbH and consortium leader at SECAI. <\/p>\n\n<p><strong>Edge cloud technology for maximum efficiency<\/strong><\/p>\n\n<p>SECAI combines edge and cloud technologies for precise and secure heating control. Sensors in the apartments collect data on temperature, humidity, and usage patterns. This data is stored locally on an edge device, where an AI creates a customized model for each apartment. In addition, untraceable model parameters from multiple buildings, along with current weather data, are incorporated into a cloud-based model. This allows the system to predict how much heat is needed in each building and adjust heat generation accordingly.    <\/p>\n\n<p>SECAI also aims to make older buildings, in particular, compatible with the edge-cloud-based AI system through retrofitting. Both existing and new buildings benefit from the advantages of intelligent control. The cost of equipping a four-room apartment with a central control unit, five digital actuators, four temperature sensors, and a push button totals approximately \u20ac1,500. All components are preconfigured and ready for use immediately after installation, eliminating the need for complex integration. SECAI thus scales significantly better than conventional energy efficiency measures, such as building insulation.     <\/p>\n\n<p><strong>An important contribution to the energy transition<\/strong><\/p>\n\n<p>SECAI offers a cost-effective way to make existing heating systems more efficient, saving time and money, without the need for expensive renovations. The system is suitable for both new and existing buildings and contributes to saving fossil fuels. SECAI makes heating smarter, more sustainable, and more efficient\u2014an important step toward climate-friendly buildings.  <\/p>\n\n<p>About SECAI: <\/p>\n\n<p>SECAI is one of ten projects in the &#8220;Edge Data Economy&#8221; technology program, funded by the German Federal Ministry for Economic Affairs and Climate Protection (BMWK) with \u20ac30 million. The SECAI consortium consists of the partners Digital Building Technology (DBT), the German Research Center for Artificial Intelligence (DFKI), the Electrical Engineering Research Association at the ZVEI (German Electrical and Electronic Manufacturers&#8217; Association), Goethe University Frankfurt, GSW Sigmaringen, Strategion (consortium leader), and Ubimet. In addition, co2online, the German Federal Environmental Foundation (DBU), the Federal Association of German Housing and Real Estate Companies (GDW), and the wibutler alliance are associated partners in SECAI.  <\/p>\n\n<p><a href=\"applewebdata:\/\/27020C66-FF5C-413C-8779-17020362B85F#_ftnref1\"> <sup>[1]<\/sup> <\/a> AG Energiebilanzen e. V., evaluation tables for the German energy balance. Data for the years 1990 to 2023. As of September 2024: <a href=\"https:\/\/ag-energiebilanzen.de\/wp-content\/uploads\/2023\/11\/awt_2023_d.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/ag-energiebilanzen.de\/wp-content\/uploads\/2023\/11\/awt_2023_d.pdf<\/a><\/p>\n\n<p><a href=\"applewebdata:\/\/27020C66-FF5C-413C-8779-17020362B85F#_ftnref2\"><sup>[2]<\/sup><\/a> Umweltbundesamt, Entwicklung des Endenergieverbrauchs nach Sektoren und Energietr\u00e4gern: https:\/\/www.umweltbundesamt.de\/daten\/energie\/energieverbrauch-nach-energietraegern-sektoren#entwicklung-des-endenergieverbrauchs-nach-sektoren-und-energietragern<\/p>\n","protected":false},"template":"","categories":[22,15,16],"class_list":["post-1042","pressemitteilung","type-pressemitteilung","status-publish","hentry","category-building","category-digitalization","category-energy"],"acf":[],"_links":{"self":[{"href":"https:\/\/fe-zvei.de\/en\/wp-json\/wp\/v2\/pressemitteilung\/1042","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/fe-zvei.de\/en\/wp-json\/wp\/v2\/pressemitteilung"}],"about":[{"href":"https:\/\/fe-zvei.de\/en\/wp-json\/wp\/v2\/types\/pressemitteilung"}],"wp:attachment":[{"href":"https:\/\/fe-zvei.de\/en\/wp-json\/wp\/v2\/media?parent=1042"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/fe-zvei.de\/en\/wp-json\/wp\/v2\/categories?post=1042"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}