Research On Determination Of Climate Design Conditions For Air-conditioning Load

The outdoor climate design conditions of the air-conditioning include the“point-condition”parameter and the“day-condition”parameter,which are the basic design parameters necessary for the air-conditioning system design process such as load calculation and equipment selection.At present,the"point conditions"of climate design conditions in domestic neglect the simultaneous occurrence characteristics between parameters;And the correlation between climate design conditions and indoor environment.The"day-condition"of the climate design conditions ignore the regional climate difference.The study proposes a reasonable climate design conditions determination method to solve above problems.For the"point conditions",the Copula connection function is used to construct the joint distribution function,which reflects the co-occurrence between meteorological elements from the perspective of probability.And then the correlation model between the risk level of climate design conditions and the indoor environment risk level was constructed based on Monte Carlo method.The probability distribution of the indoor environment risk level under different climate design conditions was determined.Thus,the climate design conditions of any indoor thermal environmental reliability level are determined.The method is applied in Tianjin,Shanghai and Guangzhou,and about1000 building models that meet the corresponding energy saving standards in China were established.Through 30 years of actual hourly load and design load simulation,the correlation rules between outdoor climate design condition risk level and indoor thermal environment risk level are established.Based on the correlation rules and probability confidence level,the outdoor climate design conditions that satisfies the reliability of any indoor thermal environment are determined.The statistical results show that the outdoor calculation parameters of air conditioning based on the inverse determination of indoor environmental reliability are significantly lower than the values recommended by domestic and international standards at any probability confidence level.For"day conditions",the study uses the K-Means clustering method to extract the daily variation characteristics and trend of meteorological parameters based on the basic theory of big data.The comparison results of design-day showed there were some differences between the traditional methods and the new ones.Current regulations cannot reflect regional climate differences accurately,while the independent and joint hourly coefficients were more applicable to the actual observed meteorological data of five typical cities.Compared with the independent hourly coefficient,the joint hourly coefficient considers the coupling relationship among parameters.Making a comprehensive evaluation.From the data aspect,the research design-day is based on the basic principle of big data to extract the hourly variation characteristics,and more accurately reflect the actual near-extreme meteorological characteristics compared with the current norm.And the co-occurrence among climate design conditions and the correlation rules were considered,which is more reasonable.From the application aspects,compared with the stage I,Guangzhou,Shanghai and Tianjin design-day of stage III can reduce the design load by an average of 11.0,10.8and 12.5W/m~2.Namely,the Stage III design day significantly reduces the cost while meeting the reliability of the indoor environment,achieving a trade-off between comfort and economy.