A Framework for Modeling Multifunctional Building Systems and Co-Simulating with Whole Building Energy Models


According to the U.S. DOE Building Energy Data Book (2010), the building sector is responsible for 40% of the nation’s primary energy consumption.1 Historically, the building envelope has been tasked with the challenge of neutralizing highly variable solar, air, and moisture conditions, all while maintaining a constant desired interior condition.2 In an attempt to maintain indoor conditions, modern building systems rely heavily on fossil-fueled mechanisms and highly insulated or glazed static building envelopes to reject exterior energy flows.3 To achieve significant progress towards global targets for clean on-site energy self-sufficiency within the building sector, integrating building envelopes with adaptive multifunctional systems could provided a series of benefits such as: electrical generation, hydrothermal collection, daylighting, reduced cooling loads, humid air dehumidification, water recuperation, distributed heating and cooling, and improved human comfort and well being.

In parallel, current energy modeling tools lack the fidelity and adaptivity necessary to validate the multi-functional benefits of next-generation envelope technologies.4 With currently available, conduction dominant tools, it is difficult to express the dynamic multi-functional convection and radiation effect of new strategies as they relate to established building physics models.5 In practice, this leads to models that are often created separately from BEM and then loosely connected through pre- or post-processing of data. Development of active systems is impeded by current modeling workflows which do not provide adequate feedback or facilitate rapid design iteration within the context of build energy modeling (BEM).6 To integrate and characterize emerging climate responsive technologies, an approach to modeling is required that encourages information exchange between different types of models at different scales, such that adaptive, higher-fidelity models can interface with standard BEM frameworks.

  1. Esterly, S., & Gelmen, R. 2010 Renewable Energy Data Book. EERE, 2010.

  2. S.E. Selkowitz, E.S. Lee, O. Aschehoug. Perspectives on Advanced Facades with Dynamic Glazings and Integrated Lighting Controls.

  3. Krarti, Moncef. Energy Audit of Building Systems: An Engineering Approach. 2nd ed. Boca Raton, FL: CRC, 2011. Print.

  4. Wetter, Michael. A View of Future Building System Modeling and Simulation. In Building Performance Simulation for Design and Operation. Abingdon, Oxon; New York, NY: Spon Press, 2011.

  5. Kim, D.-W. and Park, C.-S. Difficulties and limitations in performance simulation of a double skin facade with EnergyPlus. Energy and Buildings 43, 12 (2011), 3635-3645.

  6. Hensen, Jan, and Roberto Lamberts. Building Performance Simulation for Design and Operation. Abingdon, Oxon: Spon, 2011. Print.

Hypothesis and Goals

To expedite the development and integration of adaptive building technologies for on-site net-zero energy, as well as impact future policy, building codes and design practices, energy models must be easy to mani