Multi-agent system for energy consumption optimisation in higher education institutions

Ahmad Al-Daraiseh, Eyas El-Qawasmeh, Nazaraf Shah

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)


Global warming is one of the most serious issues faced by today’s world. The increase in world population and adoption of modern lifestyle have dramatically increased the demand for energy. Over the last decade Higher Educational Institution (HEI) buildings have seen massive increase in energy consumption due to increased use of IT equipments, longer occupancy and increased use of Heating Ventilation and Air Conditioning (HVAC) systems. Current Building Management Systems (BMS) fail to optimize energy consumption of HVAC systems in commercial and educational buildings. In this paper we present an intelligent agent based system to optimize energy consumption of HVAC system in HEI buildings. The system employs artificial intelligence techniques to predict the demand of the system and optimize energy consumption of the HVAC system. The experimental results have shown that the deployment of the system has resulted in 3% reduction in energy consumption of HVAC.
Original languageEnglish
Pages (from-to)958–965
JournalJournal of Computer and System Sciences
Issue number6
Publication statusPublished - 2015

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  • Energy management
  • Energy optimisation
  • Energy conservation
  • Sensor network
  • HVAC control
  • Energy efficiency


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