Affiliation:
1. Mines Paris, PSL University, Centre for Energy Efficiency of Systems (CES), 75006 Paris, France
Abstract
The climate data used for dynamic energy simulation of buildings located in urban regions are usually collected in meteorological stations situated in rural areas, which do not accurately represent the urban microclimate (e.g., urban heat island effect), and this might affect the simulation accuracy. This paper aims at quantitatively evaluating the effects of heat island on a high-rise building’s energy performance based on the microclimate simulation tool ENVI-met and the building energy simulation tool COMFIE. However, the computation of microclimate models is time consuming; it is not possible to simulate every day of a year in a reasonable time. This paper proposes a method that generates hourly “site-specific climate data” to avoid long microclimate simulation times. A coupling method of ENVI-met and COMFIE was developed for more precise building energy simulation, accounting for the heat island effect. It was applied to a high-rise building in Wuhan, China. The results showed that the yearly average urban heat island effect intensity at the height of 3 m was estimated to be 0.55 °C and decreased with height. Compared to the simulation considering the outdoor temperature variation with the height and orientation, using the original climate data collected in rural areas led to an overestimation of the heating load by around 5.8% and an underestimation of the cooling load by around 8.7%. Compared to the weather file at the height of 3 m near the north facade neglecting the temperature variation along the height, the heating load was overestimated by 8.2% and the cooling load was underestimated by 10.8%. The methods proposed in this paper can be used for the more precise application of urban building energy simulation.
Funder
China Scholarship Council
the Chair ParisTech VINCI Eco-design of buildings and infrastructure
Subject
Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous),Building and Construction
Reference47 articles.
1. A Review of The-State-of-the-Art in Data-Driven Approaches for Building Energy Prediction;Sun;Energy Build.,2020
2. A Method to Account for the Urban Microclimate on the Creation of ‘Typical Weather Year’ Datasets for Building Energy Simulation, Using Stochastically Generated Data;Tsoka;Energy Build.,2018
3. Hall, I.J., Prairie, R.R., Anderson, H.E., and Boes, E.C. (1978). Generation of a Typical Meteorological Year, Sandia Labs.
4. An Evaluation Model for Urban Carrying Capacity: A Case Study of China’s Mega-Cities;Wei;Habitat Int.,2016
5. Is Urbanisation Also the Culprit of Climate Change?—Evidence from Australian Cities;Maheshwari;Urban Clim.,2020
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献