Adaptive-predictive control strategy for HVAC systems in smart buildings – A review. (December 2020)

• Record Type: Journal Article
• Authors: Gholamzadehmir, Maryam; Del Pero, Claudio; Buffa, Simone; Fedrizzi, Roberto; Aste, Niccolo'
• Is Part Of: Sustainable cities and society. Volume 63(2020)
• Publication Date: 2020-12
• Subjects: Building automation -- Model predictive control -- Weather predictive -- Grid interaction; Sustainable urban development -- Periodicals; Sustainable buildings -- Periodicals; Urban ecology (Sociology) -- Periodicals; 307.76
• DOI: 10.1016/j.scs.2020.102480
• Languages: English
• ISSNs: 2210-6707

Abstract

Highlights: Comprehensive review of advanced control strategies and their impact on buildings and technical systems. Identifying features and functions of building automation and control system (BACS) in buildings and HVAC systems. Assessment of the implementations and configurations of adaptive-predictive control strategies (APCS) and associated challenges. Demonstrating research gaps in advanced control strategies (ACS) for buildings and HVAC systems. Abstract: High share of energy consumption in buildings and subsequent increase in greenhouse gas emissions along with stricter legislations have motivated researchers to look for sustainable solutions in order to reduce energy consumption by using alternative renewable energy resources and improving the efficiency in this sector. Today, the smart building and socially resilient city concepts have been introduced where building automation technologies are implemented to manage and control the energy generation/consumption/storage. Building automation and control systems can be roughly classified into traditional and advanced control strategies. Traditional strategies are not a viable choice for more sophisticated features required in smart buildings. The main focus of this paper is to review advanced control strategies and their impact on buildings and technical systems with respect to energy/cost saving. These strategies should be predictive/responsive/adaptive against weather, user, grid and thermal mass. In this context, special attention is paid to model predictive control and adaptive control strategies. Although model predictive control is the most common type used in buildings, it is not well suited for systems consisting of uncertainties and unpredictable data. Thus, adaptive predictive control strategies are being developed to address these shortcomings. Despite great progress in this field, the quantified results of these strategies reported in literature showed a high level of inconsistency. This is due to the application of different control modes, various boundary conditions, hypotheses, fields of application, and type of energy consumption in different studies. Thus, this review assesses the implementations and configurations of advanced control solutions and highlights research gaps in this field that need further investigations.