Optimization of Performance Parameter Design and Energy Use Prediction for Nearly Zero Energy Buildings

Xiaolong Xu, Guohui Feng, Dandan Chi, Ming Liu and Baoyue Dou
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Xiaolong Xu: Shenyang Jianzhu University, Shenyang 110168, China
Guohui Feng: Shenyang Jianzhu University, Shenyang 110168, China
Dandan Chi: Shenyang Jianzhu University, Shenyang 110168, China
Ming Liu: Shenyang Jianzhu University, Shenyang 110168, China
Baoyue Dou: Shenyang Jianzhu University, Shenyang 110168, China

Energies, 2018, vol. 11, issue 12, 1-23

Abstract: Optimizing key parameters with energy consumption as the control target can minimize the heating and cooling needs of buildings. In this paper we focus on the optimization of performance parameters design and the prediction of energy consumption for nearly Zero Energy Buildings (nZEB). The optimal combination of various performance parameters and the Energy Saving Ratio (ESR)are studied by using a large volume of simulation data. Artificial neural networks (ANNs) are applied for the prediction of annual electrical energy consumption in a nearly Zero Energy Building designs located in Shenyang (China). The data of the energy demand for our test is obtained by using building simulation techniques. The results demonstrate that the heating energy demand for our test nearly Zero Energy Building is 17.42 KW·h/(m 2 ·a). The Energy Saving Ratio of window-to-wall ratios optimization is the most obvious, followed by thermal performance parameters of the window, and finally the insulation thickness. The maximum relative error of building energy consumption prediction is 6.46% when using the artificial neural network model to predict energy consumption. The establishment of this prediction method enables architects to easily and accurately obtain the energy consumption of buildings during the design phase.

Keywords: nearly zero energy building; artificial neural network; performance parameter design; energy saving ratio; dynamic simulation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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