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出 处:《日用电器》2025年第1期81-86,共6页ELECTRICAL APPLIANCES
摘 要:本文聚焦于住宅空调负荷计算,开展工程自动化计算方法研究。通过剖析冷负荷系数法问题,分析其计算结果的影响因素,明确进行精准计算的关键在于围护结构相关负荷。提出自动计算方法,涵盖建筑空间自动识别、空间与围护结构部件对应及项目信息匹配围护结构信息等。同时明确气象参数确定及快速降温负荷计算法,考虑历年平均不保证小时数等因素并拟合蓄热负荷公式。经实例计算结果验证,采用新方法的计算结果可将冷负荷系数法与指标估算的差异进行协调。研究表明,机器学习与数据库结合可实现自动计算,调整参数能优化结果,为住宅空调负荷计算提供有效途径。This paper focuses on the calculation of residential air conditioning load and carries out the research on engineering automation calculation method.By analyzing the problem of cooling load coefficient method and the influencing factors of its calculation results,it is clear that the key to accurate calculation is the related loads of the envelope.An automatic calculation method is proposed,which covers the automatic identification of building space,the correspondence between space and envelope components,and the matching of project information with envelope information.At the same time,the determination of meteorological parameters and the calculation method of rapid cooling load are clarified,and the factors such as the average number of unguaranteed hours over the years are considered and the heat storage load formula is fitted.The calculation results of an example show that the difference between the cooling load coefficient method and the index estimation can be coordinated by the calculation results of the new method.The research shows that the combination of machine learning and database can realize automatic calculation,and adjusting parameters can optimize the results,which provides an effective way for residential air conditioning load calculation.
关 键 词:住宅空调负荷 自动化负荷计算 围护结构参数 气象参数 蓄热负荷
分 类 号:TP3[自动化与计算机技术—计算机科学与技术]
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