Smart Energy Automation System
Advanced artificial intelligence and predictive systems for energy optimization and savings in all buildings / infrastructures
Energy is a key element of the European Union’s economy. The EU consumes 12% of the global energy, translated to 1,629 Mtoe in 2015 . 53% of this energy is imported at the cost of more than € 400 billion per year2 that corresponds to ~3% of EU GDP in 2015, making Europe the biggest energy importer worldwide .
Numerous reports and studies have highlight the huge economic, social, and environmental impact behind EU energy efficiency, making it one of the cornerstones of EU Energy Policy2, and closely linked to its three main pillars: security (security of supply, import independence, safe production), sustainability (reducing greenhouse gas GHG emissions) and competitiveness (affordable energy for end-users).
In this context, the EU published in 2012 an Energy Efficiency Directive that established a set of binding measures to help Europe reach its 20% energy efficiency target by 2020. This target was revised in 2016 including a new 30% energy efficiency target for 2030. However, despite the high ambitions and numerous actions taken, the progress done till today has not matched the expectations: the implementation of the Energy Efficiency Directive adopted in 2012, is behind schedule and the 2020 target of a 20% saving is likely to be missed at the European level, as the primary energy savings are projected to reach only 17.6% by 2020 .
SEAS: THE SOLUTION FOR ENERGY EFFICIENCY
Smart Energy Automation System (SEAS) is a stand-alone, intelligent, energy management and automation platform combining both software and hardware elements. SEAS leverages artificial intelligence and machine learning technologies to proactively identify energy savings opportunities and automatically take real-time actions without human intervention to help industrial, commercial and residential users to reduce their energy costs.
Depending on the use-case served, the system collects and analyses in real-time multi-parametric data (energy, environmental and process) from different field devices (power meters, environmental sensors, etc.) utilizing the power of IoT. In addition, SEAS uses predictive analytics to improve equipment operation and maintenance and predict downtimes, which can extend the lifetime of the equipment and help schedule maintenance visits.
Due to its artificial intelligence characteristics, the SEAS helps its users to effectively monitor and automatically manage their energy consumption without any human intervention, supporting them to achieve their energy efficiency goals.