Contents lists available at ScienceDirect Automation in Construction journal homepage: www.elsevier.com/locate/autcon Assessing the energy and daylighting impacts of human behavior with window shades, a life-cycle comparison of manual and automated blinds Amir Nezamdoost ⁎ , Kevin Van Den Wymelenberg, Alen Mahic University of Oregon, Energy Studies in Buildings Laboratory, Eugene & Portland, OR, USA ARTICLE INFO Keywords: Manual blind use Automated blind operation LM-83 Lightswitch Blindswitch Spatial daylight autonomy Annual sunlight exposure Life-cycle analysis ABSTRACT Manual and automated blind controls are typically not included in energy and daylight simulation in part be- cause there is no consensus in the research or practice communities about the way users operate manual blinds or override automated blinds. In order for blind use patterns to become part of energy and daylight simulation best practices, the range of annual energy and daylighting impacts associated with blind use must be understood. This paper addresses these aspects by comparing four leading candidates of manually-controlled blinds plus two automated blind control algorithms using a high-rise office building located in Boise, ID. This study revealed that all four current “manual” blind use algorithm choices perform relatively similarly to automated systems, and surprisingly sometimes even more efficiently. LM-83 currently has the lowest average occlusion during regularly occupied hours, followed by Lightswitch-2002, while Blindswith-A and -B have the highest average occlusion. The IES-recommended manual blind algorithm resulted even in lower average blind occlusion and lighting energy consumption than automated systems. Finally, life-cycle cost analysis was calculated. The results show that the cost savings from interior automated shading system are substantial over a 30-year time horizon, when compared with common passive manual blinds ($25 versus $7.6 Net Present Value per SF glazing area). 1. Introduction Daylighting is a common energy-efficiency strategy that also boasts a myriad of other human benefits [17,26,27,30,39]. Successful day- lighting design that saves energy and improves human satisfaction in- corporates many technologies, spans several disciplines, and requires attention to detail throughout the design process and implementation. Blinds are quite common in spaces designed for daylighting (12 out of 22 spaces in one field study per [8,24,25]), since most daylighting designs will include some period of low angle sunlight, causing inter- mittent glare and require mitigation. The impact of manual and auto- mated blinds on the performance of daylighting and energy consump- tion in buildings has been a subject of some inquiry [1,2,4,19–21,31,38]. According to Laouadi [14], when closed, blinds reduce solar heat gain by 40% with high-performance windows to 50% with conventional windows in comparison to unshaded windows. Due to daylight penetration impact, blinds can significantly alter interior lighting loads in systems with daylight sensing electric lighting controls [6,38]. There is a growing need to evaluate the impact of automated blind controls as an energy efficiency measure, and the baseline assumptions of the presence and/or operation of manual blinds are critical to such an evaluation. A few studies have examined the benefit of internal automated blinds in lab or field settings [4,12,15,35] and reported savings in peak cooling load (5–30%), cooling and ventilation energy savings (10–30%), lighting energy savings (20–45% compared to sys- tems with photocell dimming and static blinds) and total energy savings (25%) for all systems. However, the assumptions about the baseline presence and operation of manual blinds vary in these studies. There are a limited number of studies that have provided behavioral models for manual operation of interior blinds. One of the leading manual blind control algorithms, Lightswitch-2002, was developed by Reinhart [31]. According to this algorithm, blinds are assumed to be fully occluded when the transmitted vertical irradiance exceeds 50 W/ m2 and fully raised at the start of the following workday. Another al- gorithm was proposed by Lee and Selkowitz [16] to predict the op- eration of interior venetian blinds on an hourly basis in response to incident radiation values that are either above or below 95 W/m2 threshold. Inkarojrit [10] developed a probabilistic model which pre- dicts the probability that a shading device will be lowered based on the intensity of transmitted vertical irradiance. In 2010, the IES Daylight Metrics Committee proposed a manual blind control algorithm and published it as part of IES LM-83 [7–9], which adjusts blinds based upon maintaining a threshold of less than 2% of a simulated interior https://doi.org/10.1016/j.autcon.2018.03.033 Received 5 July 2017; Received in revised form 14 November 2017; Accepted 29 March 2018 ⁎ Corresponding author. E-mail address: amirn@uoregon.edu (A. Nezamdoost). Automation in Construction 92 (2018) 133–150 0926-5805/ © 2018 Elsevier B.V. All rights reserved. T