Meeting/Event Information

    RMESE March Meeting

    March 19, 2013
    6:00 PM - 9:00 PM
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    Tavern Downtown
    1949 Market St
    Denver, CO 80202
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    Graduate / Doctorate Student Presentations

    Neal Kruis

    How do you account for heat loss from your building foundation? Many energy modelers either drastically simplify this heat loss in their models or neglect it entirely. This is because the multi-dimensional, large-timescale nature of foundation heat losses can become very computationally intensive, to the point where it becomes time prohibitive for most modeling projects.

    My research aims at answering several unanswered questions about foundation heat loss: 

    • How significant is foundation heat loss relative to other loads in the building? 
    • How good are our current tools at estimating these losses? 
    • What can be done to improve theses estimations and reduce computation time? 
    • What are best practices for insulating building foundations?

    Anna Osborne

    A grant awarded to the International Center for Appropriate and Sustainable Technology (ICAST) from the U.S. Department of Housing and Urban Development (HUD) is funding a study to assess the effect of energy conservation measures (ECMs) and behavioral change measures (BCMs) on the energy use patterns of 800 units of multi-family low-income residential properties. Since the effects of ECMs are known and calculable, the main goal of the study is to determine the degree of change that can be achieved through education of the occupants and combined effects of ECMs and BCMs. Anna has also developed a Matlab program which performs complex linear regression on utility data to assess the degree of efficiency of the building in question. The energy modeling component involves a sensitivity study on occupant behavior by adjusting schedules and setpoints as well as comparison to the Matlab program. The results are still preliminary. 

     

    Ben Brannon

    Ben Brannon will be presenting the initial development of his thesis on the Modeling and Control Design and Field Experimentation of a Thermally Activated Residence.  The project stems from a home in Missouri that attempts to direct heat obtained from massy walls to beneficial locations around the home and control radiative heat transfer.

     

    Lincoln Harmer

    This project serves as a proof-of-concept that calibrated building models when applied real-time information provide enhanced energy management and diagnostic capabilities. Rather than comparing against a static baseline as is customary in Monitoring Based Comissioning (MBCx), the building models used in this project are dynamically kept in tune with the actual building, over time horizons stretching several time scales. A straightforward energy management application involves determining the percent deviation in facility natural gas consumption or electricity use between the actual building and its model over the last day, week, month, and year; a predefined threshold of permissible deviation (say +/- 10 ) would then trigger an alarm or alert to the building management staff. Selecting the right performance metrics will be part of this research. Envisioned examples of extended diagnostic capabilities include a) fault detection and diagnosis (FDD) such as finding the most likely HVAC system parameters that explain the observed consumption patterns and thus detecting system degradation, b) prediction of facility energy use and electrical demand for the next day or week, and c) load aggregation for multiple buildings to be served by an electrical supplier in a deregulated utility context. The simulation models employed may be white box models based on first principles, statistical black box models using only monitored data, or inverse gray box models that combine reduced order building physics with simplified models for the energy systems. These inverse gray box models involving both first principles as well as parameter estimation appear as likely contenders.  The expected result is a software demonstration of using a building model and measured historical and/or real-time building information for building performance evaluation. While many of the research questions may be answered using surrogate data, we’re collecting real-time data from two facilities and are aiming to prove the concept on both buildings using a real-time field implementation.

     

    Ryan Tanner

    My research is entitled Stochastic Optimal Control of Mixed Mode Buildings Considering Occupant Driven Uncertainty

    I use offline model predictive control to optimize the controls of (simulated) mixed mode buildings, a process which results in 'optimal control datasets'. Next, I use machine-learning algorithms to derive viable BAS control rules from the optimal control datasets. EnergyPlus has been the building energy modeling tool used throughout my research, providing virtual test-buildings to try different controls in. Throughout all simulations, occupant behavior is accounted for by one of two methods. (1) Co-simulation using the building controls virtual test bed (BCVTB) to couple the EnergyPlus simulation with occupant behavior algorithms written in matlab. (2) Writing occupant behavior algorithms directly into EnergyPlus via the Energy Management System (EMS).

    Tickets

    $10.00 RMESE (ASHRAE Member)

    $10.00 RMESE (Non-ASHRAE Member)

    Future Meetings

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    June 19, 2020
    7:00 AM - 5:00 PM

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    360 Union Blvd
    Lakewood, CO 80228
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    This page was updated on 04-Jan-18