@techreport {29804, title = {Technology Assessments of High Performance Envelope with Optimized Lighting, Solar Control, and Daylighting}, year = {2016}, month = {09/2016}, institution = {Lawrence Berkeley National Laboratory}, address = {Berkeley, CA}, abstract = {

Innovative, cost-effective, energy efficiency technologies and strategies for new and retrofit construction markets are essential for achieving near-term, broad market impacts. This study focuses on innovative shading and daylighting technologies that have the potential to significantly curtail annual cooling and lighting electricity use and reduce summer peak electric demand, particularly in the hot, sunny, inland areas where there has been significant population growth.

The building industry is well aware that energy-efficiency potential does not always match actual, real world performance in the field due to a variety of mitigating factors. Third party verification of the energy savings potential of innovative technologies is important for market adoption. In the case of shading and daylighting technologies, new simulation tools have only recently been developed to improve modeling accuracy. Market acceptance is also heavily dependent on how well the technology balances comfort and indoor environmental quality (IEQ) requirements (e.g., view, brightness, etc.). PG\&E commissioned this full-scale monitored study to better understand the impact of mitigating factors on performance so as to make more informed decisions when constructing program interventions that support technology adoption in the market.

}, author = {Eleanor S. Lee and Anothai Thanachareonkit and Samir Touzani and Spencer M. Dutton and Jordan Shackelford and Darryl J. Dickerhoff and Stephen E. Selkowitz} } @conference {57409, title = {Application of a stochastic window use model in EnergyPlus}, booktitle = {SimBuild 2012, 5th National Conference of IBPSA-USA, August 1-3, 2012}, year = {2012}, month = {08/2012}, address = {Madison, WI}, abstract = {

Natural ventilation, used appropriately, has the potential to provide both significant HVAC energy savings, and improvements in occupant satisfaction.

Central to the development of natural ventilation models is the need to accurately represent the behavior of building occupants. The work covered in this paper describes a method of implementing a stochastic window model in EnergyPlus. Simulated window use data from three stochastic window opening models was then compared to measured window opening behavior, collected in a naturally-ventilated office in California. Recommendations regarding the selection of stochastic window use models, and their implementation in EnergyPlus, are presented.

}, url = {https://escholarship.org/uc/item/2gm7r783}, author = {Spencer M. Dutton and Hui Zhang and Yongchao Zhai and Edward A. Arens and Youness Bennani Smires and Samuel L. Brunswick and Kyle S. Konis and Philip Haves} }