article · Sustainability
Achieving global energy transition goals requires modern buildings to reduce dependence on fossil fuels and cut carbon emissions. To support the design of sustainable and energy-positive infrastructure, this review examines international standards, modelling strategies, and recent developments in building control systems. By filtering and critically analysing relevant studies, the research assesses how different approaches manage energy efficiency alongside thermal comfort. The investigation reveals that model predictive control is currently the most prevalent technique, especially when combined with artificial intelligence tools. However, the adoption of model predictive control continues to encounter difficulties, particularly concerning the complexity of its implementation. The findings map current progress and highlight critical gaps in control methods to guide ongoing research towards more practical, low-impact building management solutions.
Buildings consume substantial amounts of energy for heating and cooling. Identifying the most effective control systems helps reduce operational carbon footprints without compromising occupant comfort, supporting the broader transition to zero-carbon energy systems.
This work is a literature review representing early-stage research rather than an applied commercial product. It provides developers of building management systems and automation engineers with an overview of control methodologies, indicating that while artificial intelligence and model predictive control are favoured in research, simpler implementation frameworks are required before widespread market uptake can occur.
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The objective of energy transition is to convert the worldwide energy sector from using fossil fuels to using sources that do not emit carbon by the end of the current century. In order to achieve sustainability in the construction of energy-positive buildings, it is crucial to employ novel approaches to reduce reliance on fossil fuels. Hence, it is essential to develop buildings with very efficient structures to promote sustainable energy practices and minimize the environmental impact. Our aims were to shed some light on the standards, building modeling strategies, and recent advances regarding the methods of control utilized in the building sector and to pinpoint the areas for improvement in the methods of control in buildings in hopes of giving future scholars a clearer understanding of the issues that need to be addressed. Accordingly, we focused on recent works that handle methods of control in buildings, which we filtered based on their approaches and relevance to the subject at hand. Furthermore, we ran a critical analysis of the reviewed works. Our work proves that model predictive control (MPC) is the most commonly used among other methods in combination with AI. However, it still faces some challenges, especially regarding its complexity.
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DOI: 10.3390/su16052154
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