Comparing Whole Building Energy Implications of Sidelighting Systems with Alternate Manual Blind Control Algorithms

Christopher Dyke,Judi Steciak,Kevin Van Den Wymelenberg,Ery Djunaedy

doi:10.3390/buildings5020467

Abstract

Currently, there is no manual blind control guideline used consistently throughout the energy modeling community. This paper identifies and compares five manual blind control algorithms with unique control patterns and reports blind occlusion, rate of change data, and annual building energy consumption. The blind control schemes detailed here represent five reasonable candidates for use in lighting and energy simulation based on difference driving factors. This study was performed on a medium-sized office building using EnergyPlus with the internal daylight harvesting engine. Results show that applying manual blind control algorithms affects the total annual consumption of the building by as much as 12.5% and 11.5% for interior and exterior blinds respectively, compared to the Always Retracted blinds algorithm. Peak demand was also compared showing blind algorithms affected zone load sizing by as much as 9.8%. The alternate algorithms were tested for their impact on American Society of Heating, Refrigeration and Air-Conditioning Engineers (ASHRAE) Guideline 14 calibration metrics and all models were found to differ from the original calibrated baseline by more than the recommended ±15% for coefficient of variance of the mean square error (CVRMSE) and ±5% for normalized mean bias error (NMBE). The paper recommends that energy modelers use one or more manual blind control algorithms during design stages when making decisions about energy efficiency and other design alternatives.

Highlights

It has been well documented that blinds affect energy use in buildings [1,2,3,4]; the application of blind control algorithms is not common in energy modeling practice
This paper identifies and compares five manual blind control algorithms (Blindswitch-2012A, Blindswitch-2012B, DGI20, Always Engaged and Always Retracted) and reports detailed blind occlusion and rate of change data and subsequent annual building energy consumption
The purpose of the study is to determine how different the competing manual blind control algorithms are, and how impactful these differences may be to the practice of design analysis simulation

Summary

Introduction

It has been well documented that blinds affect energy use in buildings [1,2,3,4]; the application of blind control algorithms is not common in energy modeling practice. Buildings that use daylighting as a primary light source and rely on electric lighting only as needed have been shown to reduce annual lighting energy by up to 60% [1,3,4]. By controlling the amount of daylight and incoming solar radiation through the window, blinds affect interior lighting loads and space heating and cooling loads. There is an important trade-off between available daylight allowance and solar heat gain, and blind use impacts the relationship. In advanced motorized and automated blind systems, energy factors can be balanced to the greatest effect. Most buildings rely on manual blinds and these are controlled by occupants following several influential factors including modulating the amount of daylight, minimizing glare, or for reasons of privacy or other factors [5]

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