Hybrid system controls of natural ventilation and HVAC in mixed-mode buildings: A comprehensive review
Abstract
Mixed-mode buildings utilise a combination of natural ventilation from operable building envelopes and mechanical systems to realise climate-friendly ventilation and cooling. The control of such hybrid systems is a promising solution to improve energy efficiency for buildings and comfort for occupants. Meanwhile, it is also a challenging task due to the complexity of the systems and coupled indoor and outdoor air flows and disturbances. This paper presents a systematic review of mixed-mode building controls. From the topical aspects of case studies, the paper analyses locations, climates, building and space types, and sensors. From a control point of view, the paper presents control algorithms based on a well-structured taxonomy, where various algorithms are classified into four categories (On-Off and PID control, rule-based control, optimal control including model predictive control and reinforcement learning, and computational intelligence including fuzzy logic and data-driven control). From an evaluation point of view, the paper illustrates evaluation platforms (simulation and real-world implementation) and results. Modelling and control tools for (co-) simulation are summarised. The evaluation results are compared based on metrics of natural ventilation and night cooling potentials, thermal comfort, indoor air quality, and energy savings. Finally, findings from the review and future research concerns are discussed.
- Publication:
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Energy and Buildings
- Pub Date:
- December 2022
- DOI:
- 10.1016/j.enbuild.2022.112509
- Bibcode:
- 2022EneBu.27612509P
- Keywords:
-
- Building energy conservation;
- Natural ventilation;
- HVAC;
- Mixed-mode;
- MPC;
- Reinforcement learning;
- Machine learning;
- Building control;
- Smart building