Journal publications

• Javan, Farzad Dadras; Campodonico Avendano, Italo Aldo; Najafi, Behzad; Rossi, Michele; Rinaldi, Fabio. (2024) Estimating morning ramp-up duration for the cooling season in a smart building using machine learning: Determining most promising features. Sustainable Energy Technologies and Assessments
  Academic article
• Kaboli, Ali; Dadras Javan, Farzad; Campodonico Avendano, Italo Aldo; Najafi, Behzad; Colombo, Luigi Pietro Maria; Perotti, Sara. (2024) Just-in-Time Morning Ramp-Up Implementation in Warehouses Enabled by Machine Learning-Based Predictive Modelling: Estimation of Achievable Energy Saving through Simulation. Energies
  Academic article
• Campodonico Avendano, Italo Aldo; Andersen, Kamilla Heimar; Erba, Silvia; Moazami, Amin; Aghaei, Mohammadreza; Najafi, Behzad. (2024) A novel framework for assessing the smartness and the smart readiness level in highly electrified non-residential buildings: A Norwegian case study. Energy and Buildings
  Academic article
• Campodonico Avendano, Italo Aldo; Javan, Farzad Dadras; Najafi, Behzad; Moazami, Amin. (2024) Calibration and validation of physics-based data-driven models for simulating the thermal behavior of indoor spaces in an assisted living facility. E3S Web of Conferences
  Academic article
• Campodonico Avendano, Italo Aldo; Javan, Farzad Dadras; Najafi, Behzad; Moazami, Amin Nitter; Rinaldi, Fabio. (2023) Assessing the impact of employing machine learning-based baseline load prediction pipelines with sliding-window training scheme on offered flexibility estimation for different building categories. Energy and Buildings
  Academic article
• Javan, Farzad Dadras; Campodonico Avendano, Italo Aldo; Najafi, Behzad; Moazami, Amin Nitter; Rinaldi, Fabio. (2023) Machine-Learning-Based Prediction of HVAC-Driven Load Flexibility in Warehouses. Energies
  Academic article

Part of book/report

• Javan, Farzad Dadras; Najafi, Behzad; Rinaldi, Fabio; Campodonico Avendano, Italo Aldo; Moazami, Amin Nitter. (2023) Modulating the HVAC Demand of a Warehouse to Provide Load Flexibility for Charging Electric Trucks. ECMS European Council for Modelling and Simulation
  Academic chapter/article/Conference paper
• Campodonico Avendano, Italo Aldo; Moazami, Amin Nitter; Javan, Farzad Dadras; Najafi, Behzad. (2023) Predicting Hvac-Based Demand Flexibility in Grid-Interactive Efficient Buildings Utilizing Deep Neural Networks. ECMS European Council for Modelling and Simulation
  Academic chapter/article/Conference paper