| In recent years,the rapid development of urbanization and industrialization,a large number of people from rural to urban transfer,labor transfer brought about remarkable economic development,driving the steady growth of our economy year by year.At the same time,urban problems are exposed.The expansion speed of some cities cannot keep up with the increase of population,and the speed of infrastructure construction cannot keep up with the growth of demand,leading to the deterioration of urban environment,which is mainly manifested by urban heat island effect and air pollution.Urban buildings increase energy consumption and waste,and Typical Meteorological Year(TMY)is the basic outdoor meteorological data in energy conservation design,renovation and evaluation.At present,the influence of urban heat island effect and air pollution should be considered in typical meteorological year.Previous research on urban meteorological data focused on accuracy,regionality and coverage,but paid little attention to the design and calculation parameters of air conditioning equipment in high energy consumption buildings.In response to the national call for energy conservation and emission reduction,and to promote the realization of the goals of "carbon neutrality" and "carbon peaking",the following three aspects of research are carried out by using the latest meteorological data and artificial intelligence algorithm:(1)Supplement and expand TMY data in urban space.By analyzing the correlation between meteorological elements and common air pollutants,the prediction model is established,the TMY data in urban environment is supplemented and expanded,and six columns of air pollution-related data are added.This includes concentrations of SO2,NO2,CO,O3,PM2.5 and PM10 as well as the Air Quality Index(AQI).Combined with the comfort study,OTPCD(Outdoor Thermal and Pollution Comfortable Degree),a composite residential comfort evaluation index,is formed.It is predicted that in the next four years,the number of comfortable days will decrease by 33% and be affected by the change of air quality.The number of comfort days will decrease year by year.(2)Modify the design day parameters of outdoor air conditioners in summer.Hourly weather data including dry bulb temperature,wet bulb temperature and wind speed were selected to modify the hourly variation coefficient β of outdoor temperature in summer combined with urban heat island intensity.By analyzing the correlation and simultaneity between meteorological elements,the β was clustered and calculated,and the future trend of β was predicted by combining the LSTM(Long Short Term Memory neural network)model.The results show that the modified β is more consistent with the actual local meteorological conditions.The time and peak of the maximum temperature on the revised summer design day have changed.(3)The variation of cooling load of hospital buildings in summer in urban heat island area was studied.The modeling software was used to simplify the modeling and analysis of hospital buildings,and the operation parameters of air conditioning systems in each room and region were simulated and calculated.The modified outdoor air conditioning design day parameters were input into the air conditioning model to analyze the current and future summer cooling load changes of different hospital buildings under the influence of urban heat island effect.The research shows that for hospital buildings in Beijing and Shanghai,compared with the corresponding summer cooling load in the previous specifications,the cooling load obtained by the summer air conditioning design daily revision method can more accurately represent the current and future load changes,and provide a more accurate reference for the realization of "carbon peak" and "carbon neutrality" goals. |
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