Robust optimal design of renewable energy system in nearly/net zero energy buildings under uncertainties

Yuehong Lu, Shengwei Wang, Chengchu Yan and Zhijia Huang

Applied Energy, 2017, vol. 187, issue C, 62-71

Abstract: It is acknowledged that the conventional design methods can easily lead to oversized system or unsatisfactory performance for different design conditions. Most existing studies on design optimization of net zero energy building (nZEB) are conducted based on deterministic data/information. However, the question is: How is the actual performance of a design nZEB in different years considering uncertainties? This study, therefore, proposed a robust design method for sizing renewable energy systems in nZEB concerning uncertainties in renewable resources and demand load. The proposed robust design method is applied to the planning of renewable energy system for the Hong Kong Zero Carbon Building. The annual performance of nZEB under the optimal design options are systematically investigated and compared using the proposed robust design method and the deterministic method. It is meaningful to obtain a fitting formula to identify the relationship between the probability of achieving annual zero energy balance and the design mismatch ratio. On the basis of Monte Carlo uncertainty propagation methods, the uncertainty of nZEB performance is quantified which provides flexibility for designers in selecting appropriate design options according to the required probability of achieving nZEB during the design stage.

Keywords: Net zero energy building; Robust design; Monte Carlo simulation; Mismatch ratio (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (39)

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DOI: 10.1016/j.apenergy.2016.11.042

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