This study investigates control strategies for coordinating the variable solar-optical properties of a dynamic building envelope system with a daylight controlled electric lighting system to reduce electricity consumption and increase comfort in the perimeter zone of commercial buildings. Control strategy design can be based on either simple, instantaneous measured data, or on complex, predictive algorithms that estimate the energy consumption for a selected operating state of the dynamic envelope and lighting system. The potential benefits of optimizing the operation of a dynamic envelope and lighting system are (1) significant reductions in electrical energy end-uses - lighting, and cooling due to solar and lighting heat gains - over that achieved by conventional static envelope and lighting systems, (2) significant reductions in peak demand, and (3) increased occupant visual and thermal comfort. The DOE-2 building energy simulation program was used to model two dynamic envelope and lighting systems, an automated venetian blind and an electrochromic glazing system, and their control strategies under a range of building conditions. The energy performance of simple control strategies are compared to the optimum performance of a theoretical envelope and lighting system to determine the maximum potential benefit of using more complex, predictive control algorithms. Results indicate that (1) predictive control algorithms may significantly increase the energy-efficiency of systems with non-optimal solar-optical properties such as the automated venetian blind, and (2) simpler, non-predictive control strategies may suffice for more advanced envelope systems 1 incorporating spectrally selective, narrow-band electrochromic coatings.

The Five-Phase Method (5-pm) for simulating complex fenestration systems with Radiance is validated against field measurements. The capability of the method to predict workplane illuminances, vertical sensor illuminances, and glare indices derived from captured and rendered high dynamic range (HDR) images is investigated. To be able to accurately represent the direct sun part of the daylight not only in sensor point simulations, but also in renderings of interior scenes, the 5-pm calculation procedure was extended. The validation shows that the 5-pm is superior to the Three-Phase Method for predicting horizontal and vertical illuminance sensor values as well as glare indices derived from rendered images. Even with input data from global and diffuse horizontal irradiance measurements only, daylight glare probability (DGP) values can be predicted within 10% error of measured values for most situations.

This article presents and discusses the lessons learned from the monitoring of 25 integrated daylighting and electric lighting international case study projects. The case studies consist of real occupied buildings that have been monitored as part of the International Energy Agency (IEA) SHC Task 61/EBC Annex 77 Programme. The general goal of the case studies was to balance lighting energy use with occupants’ visual and non-visual requirements. This was achieved using innovative solutions for daylighting and electric lighting with advanced controls, but also implementing simple and out-of-the-box strategies. The findings suggest that energy demands for lighting can significantly be reduced by combining sensible daylight provision, efficient lighting sources, and advances in controls. Yet, the effective achievement of project goals requires adequate monitoring, fine-tuning, and verification. The findings also suggest that the adoption of “integrative” lighting – that is, lighting systems that address both visual and non-visual responses – is getting increasingly popular. Catering to non-visual requirements will likely drive further innovation in lighting technology. Currently, there is limited investment available for developing daylighting systems for integrative lighting, and the current related electric strategies often come at the risk of energy rebound effects. Overall, providing daylighting and understanding user requirements are fundamental steps towards achieving quality projects, with potential benefits beyond saving energy.