Comparison of Factorial and Latin Hypercube Sampling Designs for Meta-Models of Building Heating and Cooling Loads

Younhee Choi,Sungmin Yoon,Doosam Song,Junemo Koo

doi:10.3390/en14020512

Younhee Choi, Sungmin Yoon + Show 2 more

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https://doi.org/10.3390/en14020512

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Abstract

Interest in research analyzing and predicting energy loads and consumption in the early stages of building design using meta-models has constantly increased in recent years. Generally, it requires many simulated or measured results to build meta-models, which significantly affects their accuracy. In this study, Latin Hypercube Sampling (LHS) is proposed as an alternative to Fractional Factor Design (FFD), since it can improve the accuracy while including the nonlinear effect of design parameters with a smaller size of data. Building energy loads of an office floor with ten design parameters were selected as the meta-models’ objectives, and were developed using the two sampling methods. The accuracy of predicting the heating/cooling loads of the meta-models for alternative floor designs was compared. For the considered ranges of design parameters, window insulation (WDI) and Solar Heat Gain Coefficient (SHGC) were found to have nonlinear characteristics on cooling and heating loads. LHS showed better prediction accuracy compared to FFD, since LHS considers the nonlinear impacts for a given number of treatments. It is always a good idea to use LHS over FFD for a given number of treatments, since the existence of nonlinearity in the relation is not pre-existing information.

Highlights

The abrupt increase in global energy use is a significant factor that augments global warming
There is no second-order term for the regression model of fractional factorial design (FFD), since the design points only have two levels at the endpoints for all design factors
Meta-model b-1 was derived from the regression analysis considering only the linear effects of design factors from the Latin hypercube sampling (LHS) sampling points

Summary

Introduction

The abrupt increase in global energy use is a significant factor that augments global warming. In Korea, energy use in the building sector constitutes approximately 18% of the total energy consumption. This number increases to 55% in Seoul, the largest cosmopolitan city in South Korea [2]. Many researchers have conducted studies on topics focused on the reduction of the global energy consumption and CO2 emission. Such investigations have expanded to the building sector and are focused primarily on: (1) reducing the heating and cooling loads of buildings, (2) decreasing energy consumption by optimally controlling highly efficient installations, and (3) using as much renewable energy as possible

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