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Towards fast energy performance evaluation: A pilot study for office buildings

机译:迈向快速能源绩效评估:办公楼的初步研究

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Given the growing concern about building energy efficiency and the difficulty in applying complex simulation tools during retrofit practices, the need for easily and quickly estimating the building energy performance becomes pressing. As a pilot test, this study proposes a systematic method to develop a model, which can immediately assess the annual electricity consumption for office buildings with fan coil system in Shanghai. First, a base-case building model is established by EnergyPlus to create a pool of candidate inputs using orthogonal experiment design. Then, analysis of variance is used to identify a total of 10 key building design parameters, which are selected as the input variables in the support vector regression (SVR) model based on a well-structured database. The performance of SVR is optimized using genetic algorithm (GA) based on radial basis function kernel. Finally, two real office buildings in Shanghai with reliable measured data serve to evaluate the developed hybrid model. The resulting differences between the predicted and measured values are generally within 10%. It is expected that the developed database and model can be used to assess the likely energy savings penalty related with certain parameter changes to some extent during the retrofit process for office buildings. (C) 2016 Elsevier B.V. All rights reserved.
机译:鉴于对建筑能源效率的日益关注以及在改造实践中难以使用复杂的仿真工具的情况,迫切需要快速,轻松地评估建筑能源性能。作为一项先导测试,本研究提出了一种系统化的方法来开发模型,该模型可以立即评估上海带有风机盘管系统的办公楼的年耗电量。首先,EnergyPlus建立了一个基本案例构建模型,以使用正交实验设计创建候选输入池。然后,使用方差分析来识别总共10个关键建筑物设计参数,这些参数将基于结构良好的数据库选择为支持向量回归(SVR)模型中的输入变量。使用基于径向基函数核的遗传算法(GA)优化了SVR的性能。最后,上海的两座具有可靠测量数据的真实办公楼用于评估已开发的混合模型。预测值与测量值之间的差异通常在10%以内。预期开发的数据库和模型可用于评估办公楼翻新过程中与某些参数更改相关的可能的节能损失。 (C)2016 Elsevier B.V.保留所有权利。

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