Technology and Engineering
  • ISSN: 2333-2581
  • Modern Environmental Science and Engineering

ZEB Prototype Controlled by A Machine Learning System


Federico Cinquepalmi1, Sofia Agostinelli2, and Fabrizio Cumo2
1. Italian Ministry of University and Education, Rome, Italy

2. CITERA – Sapienza University of Rome, Italy


Abstract: This communication concerns a research project by the Interdepartmental Research Centre for Territory Construction Restoration and Environment (CITERA) of Sapienza University of Rome in collaboration with ENEA (Italian National Agency for New Technologies, Energy and Sustainable Economic Development) based on the realization of a 1:1 scale demonstrator of a Zero Energy Building (ZEB) that allows continuous experimentation of new technologies for innovative photovoltaic systems, efficient storage systems and high-performance envelope materials. In particular a measurement protocol has been developed for both the overall efficiency of the building and the individual technological components with a view to a comparative critical analysis of the integration of the individual components in the building-system complex. All the technological systems has been used in Solar Decathlon Middle East 2018 competition in Dubai. The project concerns the development of a control and management system for photovoltaic energy production systems for the ZEB prototype, based on an intelligent self-learning system (AI) able to optimize the parameters of self-produced electricity supply based on real consumption of air conditioning equipment, electrical power supply to the equipment, access control and safety equipment. The most immediate result concerns the integrated design of both the hardware systems for the production and use of electricity and the algorithms that continuously measure parameters such as grid load, consumption and electricity production, and which takes into account weather forecasts, energy tariffs, and learns the trend of electricity consumers through the use of artificial intelligence.


Key words: Zero Energy Building (ZEB), machine learning control, energy efficiency




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