Abstract
ABSTRACT Climate change plays a crucial role in shaping a building's energy use. When assessing building performance, simulation software relies on typical meteorological year (TMY) data to represent long-term climate conditions. This study provides the first comprehensive review of TMY datasets for building applications. An extensive analysis of 530 publications from 1978 to 2023 was conducted to extract the present status of the existing TMY databases, conventional methods, advancements, critical research gaps, and potential future directions to enhance the TMY representativeness for building energy simulation. The TMY improvement methods were analyzed based on the simulation parameters, measured outcomes, and evaluation metrics. The review reveals limitations in existing TMY databases, including sparse station data, fixed weighting schemes, and failure to account for microclimate or abrupt climate change. The study identifies four key research areas to develop more accurate and representative TMY datasets for sustainable building applications: (1) expanding case study scales, (2) refining meteorological parameters, (3) improving data pre-processing techniques, and (4) enhancing validation strategies for the TMY improvement methods. This study offers a holistic view of TMY generation for building applications, and implementing its recommendations can advance building energy research for sustainable design strategies and operation practices.
Published Version
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