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Benchmarking of adaptive control strategies of HVAC systems in a dynamic co-simulation environment

keywords BUILDING AUTOMATION, BUILDING ENERGY MANAGEMENT, INTELLIGENT BUILDINGS

Reference persons ALFONSO CAPOZZOLI

Research Groups BAEDA lab (www.baeda.polito.it), TEBE

Description In the last few years, many research activities are aimed at exploring strategies for simultaneously optimizing indoor environmental quality and energy demand through multi-objectives and quasi-real time control procedures based on forecasting and online analytics. Adaptive and predictive optimal control provides powerful opportunities for leveraging building properties (e.g. thermal mass, storage, renewable energy sources) to enhance energy flexibility during operation. However, a robust benchmarking of these control strategies against other known techniques remain an open issue to address.


Deadline 24/02/2023      PROPONI LA TUA CANDIDATURA




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