@article {60932, title = {Green, Clean, \& Mean: Pushing the Energy Envelope in Tech Industry Buildings}, year = {2015}, month = {05/2015}, publisher = {Lawrence Berkeley National Laboratory}, abstract = {

When it comes to innovation in energy and building performance, one can expect leading-edge activity from the technology sector. As front-line innovators in design, materials science, and information management, developing and operating high-performance buildings is a natural extension of their core business.

The energy choices made by technology companies have broad importance given their influence on society at large as well as the extent of their own energy footprint. Microsoft, for example, has approximately 250 facilities around the world (30 million square feet of floor area), with significant aggregate energy use of approximately 4 million kilowatt-hours per day.

There is a degree of existing documentation of efforts to design, build, and operate facilities in the technology sector. However, the material is fragmented and typically looks only at a single company, or discrete projects within a company.Yet, there is no single resource for corporate planners and decision makers that takes stock of the opportunities and documents sector-specific case studies in a structured manner. This report seeks to fill that gap, doing so through a combination of generalized technology assessments ({\textquotedblleft}Key Strategies{\textquotedblright}) and case studies ({\textquotedblleft}Flagship Projects{\textquotedblright}).

}, author = {Evan Mills and Jessica Granderson and Wanyu R. Chan and Richard C. Diamond and Philip Haves and Bruce Nordman and Paul A. Mathew and Mary Ann Piette and Gerald Robinson and Stephen E. Selkowitz} } @conference {418, title = {Assessment of Energy Impact of Window Technologies for Commercial Buildings}, booktitle = {2010 ACEEE Summer Study}, year = {2010}, month = {2010}, keywords = {building energy performance, energyplus, shading controls, simulation, windows}, author = {Tianzhen Hong and Stephen E. Selkowitz} } @article {3446, title = {Assessment of Energy Impact of Window Technologies for Commercial Buildings}, year = {2009}, month = {10/2009}, author = {Tianzhen Hong and Stephen E. Selkowitz and Mehry Yazdanian} } @article {239, title = {Towards a Very Low Energy Building Stock: Modeling the US Commercial Building Stock to Support Policy and Innovation Planning}, journal = {Building Research and Information}, volume = {37:5}, year = {2009}, chapter = {610}, abstract = {

This paper describes the origin, structure and continuing development of a model of time varying energy consumption in the US commercial building stock. The model is based on a flexible structure that disaggregates the stock into various categories (e.g. by building type, climate, vintage and life-cycle stage) and assigns attributes to each of these (e.g. floor area and energy use intensity by fuel type and end use), based on historical data and user-defined scenarios for future projections. In addition to supporting the interactive exploration of building stock dynamics, the model has been used to study the likely outcomes of specific policy and innovation scenarios targeting very low future energy consumption in the building stock. Model use has highlighted the scale of the challenge of meeting targets stated by various government and professional bodies, and the importance of considering both new construction and existing buildings.

}, author = {Brian E. Coffey and Sam Borgeson and Stephen E. Selkowitz and Joshua S. Apte and Paul A. Mathew and Philip Haves} } @article {413, title = {Comparing computer run time of building simulation programs}, journal = {Building Simulation}, volume = {1}, year = {2008}, month = {2008}, pages = {210-213}, abstract = {

This paper presents an approach to comparing computer run time of building simulation programs. The computing run time of a simulation program depends on several key factors, including the calculation algorithm and modeling capabilities of the program, the run period, the simulation time step, the complexity of the energy models, the run control settings, and the software and hardware configurations of the computer that is used to make the simulation runs. To demonstrate the approach, simulation runs are performed for several representative DOE-2.1E and EnergyPlus energy models. The computer run time of these energy models are then compared and analyzed.

}, keywords = {computer run time, doe-2, energyplus, simulation program}, doi = {10.1007/s12273-008-8123-y}, author = {Tianzhen Hong and Walter F. Buhl and Philip Haves and Stephen E. Selkowitz and Michael Wetter} } @proceedings {2820, title = {Development of Trade-Off Equations for EnergyStar Windows}, journal = {SimBuild 2004, Building Sustainability and Performance Through Simulation}, year = {2004}, month = {08/2004}, address = {Boulder, Colorado, USA}, author = {Yu Joe Huang and Robin Mitchell and Stephen E. Selkowitz} }