Mistretta Marina, Brunetti Alberto, Cellura Maurizio, Guarino Francesco, Longo Sonia
University Mediterranean of Reggio Calabria, Department of Information Engineering, Infrastructure and Sustainable Energy (DIIES), Via Graziella, Feo di Vito, Reggio Calabria 89122, Italy.
University of Palermo, Department of Engineering, Viale delle Scienze Building 9, Palermo 90128, Italy.
Sci Total Environ. 2024 Jul 10;933:172751. doi: 10.1016/j.scitotenv.2024.172751. Epub 2024 Apr 26.
Temporal fluctuations of the electricity grid generation composition, variability of electricity consumption in building operation over the year and of the on-site renewable energy systems are factors that should be properly considered, using high-resolution data in the building energy and environmental performance assessment. In this study a methodological framework is developed to model high-resolution electricity mixes in building operation and to assess the related energy and environmental impacts over the year, by means of a life cycle approach. For most impact categories, the imported electricity generation mixes, to meet the residual building demand, show impact variations not higher than +20 % and not lower than -38 % at seasonal and daily time compared with the annual average values. Temporal variations are even more relevant in building consumption electricity mixes, which are significantly characterized by self-consumption and show noticeable reductions compared to the annual electricity generation mix in both assessed scenarios. As an example, summer and spring energy generation mixes show the best results for climate change (0.09 kgCO/kWh) compared to the annual ones, while in winter and autumn mixes the contribution to climate change overcomes the respective annual results. Both summer day-mixes contribute to climate change for about 0.12 kgCO/kWh, with a reduction of nearly 30 % if compared the annual data. Conversely, in the winter day-mixes the contribution to climate change is about 0.20 kgCO/kWh and comes mostly from the grid. The results highlight that assessed temporal variations are significant through the year for the most assessed environmental indicators. Furthermore, the use of high-resolution electricity generation mixes allows to optimize efficiently the temporal use of electricity in buildings, in sight of energy and environmental impact reduction also thanks to the employment of life cycle oriented approaches. The results also highlight the relevance of the storage system in fulfilling periods of peak demand or low renewable generation.
电网发电构成的时间波动、建筑物运行中全年电力消耗的变化以及现场可再生能源系统的变化,都是在建筑能源和环境性能评估中应使用高分辨率数据予以适当考虑的因素。在本研究中,开发了一个方法框架,通过生命周期方法对建筑运行中的高分辨率电力组合进行建模,并评估全年相关的能源和环境影响。对于大多数影响类别,为满足建筑物剩余需求而输入的发电组合,在季节和每日时间尺度上,与年度平均值相比,其影响变化不高于+20%且不低于-38%。时间变化在建筑消费电力组合中更为显著,其显著特点是自消费,并且在两种评估情景下与年度发电组合相比都有明显减少。例如,与年度组合相比,夏季和春季的能源发电组合在气候变化方面显示出最佳结果(0.09 kgCO/kWh),而在冬季和秋季组合中,对气候变化的贡献超过了各自的年度结果。两个夏季日组合对气候变化的贡献约为0.12 kgCO/kWh,与年度数据相比减少了近30%。相反,在冬季日组合中,对气候变化的贡献约为0.20 kgCO/kWh,且大部分来自电网。结果表明,对于大多数评估的环境指标,全年评估的时间变化是显著的。此外,使用高分辨率发电组合能够有效地优化建筑物中电力的时间使用,鉴于减少能源和环境影响,这也要归功于采用面向生命周期的方法。结果还突出了存储系统在满足高峰需求期或可再生能源低发电量时期的相关性。