This study proposes a replicable approach for evaluating the impact of different weather data sources during the building refurbishment. Starting from a deep energy diagnosis, the numerical model is calibrated by using the weather data and the energy billings of the same year. Then, the performance gap is evaluated due to the adoption of conventional or new weather files defined with data recently monitored in areas with different levels of urbanization. The final step is a sensitivity analysis on the energy, environmental and economic indexes for the refurbishment interventions. The proposed approach is applied to the student dormitory of the University of Molise, located in Campobasso, a city of south Italy with oceanic climate according to Köppen classification. The results highlight significant deviations on the estimated energy consumption as well as on the energetic and environmental indexes of the refurbishment design. Instead, the impact on the economic index is quite limited.

Highlights

• The weather data of rural and urban stations are compared with typical weather files.

• The UHI effect in heating-dominated climate in central Italy is proved.

• The mathematical relation between HDD/CCD and weather data evolution is found.

• The impact of different weather files on building energy performance prevision is studied.

• Inaccuracies in energy saving, environmental and economic indexes are quantified.

这项研究提出了一种可复制的方法，用于评估建筑物翻新过程中不同天气数据源的影响。从深度能源诊断开始，使用天气数据和当年的能源账单对数值模型进行校准。然后，由于采用了常规的或新的天气文件，对性能差距进行了评估，这些文件由最近在城市化程度不同的地区监控的数据定义。最后一步是对翻新干预措施的能源，环境和经济指标进行敏感性分析。拟议的方法适用于位于意大利南部城市坎波巴索的莫利塞大学的学生宿舍，根据柯本分类，该市是意大利南部海洋性气候。结果表明，翻新设计的估计能耗以及能量和环境指标存在明显偏差。相反，对经济指数的影响相当有限。

强调

• 将农村和城市气象站的天气数据与典型的气象文件进行比较。

• 事实证明，UHI在意大利中部以供暖为主的气候中具有作用。

• 发现了HDD / CCD与天气数据演变之间的数学关系。

• 研究了不同天气文件对建筑物能源性能预案的影响。

• 量化了节能，环境和经济指标方面的误差。