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Building energy model calibration using automated optimization-based algorithm

机译：使用基于自动优化的算法进行建筑能耗模型校准

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Multiple numbers of Building Energy Simulation (BES) programs have been improved and implemented during the last decades. BES models play a crucial role in understanding building energy demands and accelerating the malfunction diagnosis. However, due to the very high number of interacting parameters, most of the developed energy simulation programs do not accurately predict building energy performance under a known condition. Even the energy models which are developed with the very precise assignment of parameters, there is always significant discrepancies between the simulation results and the real-time data measurements. Current study develops an optimization-based framework to calibrate the whole building energy model. The optimization algorithm attempts to set the identified parameters to minimize the error between the simulation results and the real-time measurements. Due to the high number of parameters, the developed optimization algorithm utilizes a Harmony Search algorithm as its search engine coupled with the energy simulation model to accelerate the calibration process. Moreover, to illustrate the efficiency of using the developed framework, a case study of the office building is modeled and calibrated and the statistical analysis was conducted to assess the accuracy of the results. The results of the calibration process show the reliability of the framework. (C) 2019 Elsevier B.V. All rights reserved.
机译：在过去的几十年中，已经改进并实施了许多建筑节能模拟（BES）程序。 BES模型在理解建筑物的能源需求和加快故障诊断中起着至关重要的作用。但是，由于相互作用参数的数量很大，大多数已开发的能源模拟程序无法在已知条件下准确预测建筑物的能源性能。即使使用非常精确的参数分配开发的能量模型，在模拟结果和实时数据测量之间也始终存在显着差异。当前的研究开发了一个基于优化的框架来校准整个建筑能耗模型。优化算法尝试设置识别出的参数，以最小化仿真结果和实时测量之间的误差。由于参数数量众多，因此开发的优化算法将Harmony Search算法用作其搜索引擎，并与能量模拟模型结合使用，以加快校准过程。此外，为了说明使用开发的框架的效率，对办公大楼进行了案例研究并进行了校准，并进行了统计分析以评估结果的准确性。校准过程的结果表明了该框架的可靠性。 （C）2019 Elsevier B.V.保留所有权利。

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