Liu, Jingjing (2010-05). Improvements and Applications of the Methodology for Potential Energy Savings Estimation from Retro-commissioning/Retrofit Measures. Master's Thesis. Thesis uri icon

abstract

  • This thesis has improved Baltazar's methodology for potential energy savings estimation from retro-commissioning/retrofits measures. Important improvements and discussions are made on optimization parameters, limits on optimization parameter values, minimum airflow setting for VAV systems, space load calculation, simulation of buildings with more than one type of system, AHU shutdown simulation, and air-side simulation models. A prototype computer tool called the Potential Energy Savings Estimation (PESE) Toolkit is developed to implement the improved methodology and used for testing. The implemented methodology is tested in two retro-commissioned on-campus buildings with hourly measured consumption data. In the Sanders Corps of Cadets Center, the optimized profiles of parameter settings in single parameter optimizations can be explained with engineering principles. It reveals that the improved methodology is implemented correctly in the tool. The case study on the Coke Building shows that the improved methodology can be used in buildings with more than one system type. The methodology is then used to estimate annual potential energy cost savings for 14 office buildings in Austin, TX with very limited information and utility bills. The methodology has predicted an average total potential savings of 36% for SDVAV systems with electric terminal reheat, 22% for SDVAV systems with hot water reheat, and 25% for DDVAV systems. The estimations are compared with savings predicted in the Continuous Commissioning assessment report. The results show it may be helpful to study the correlation by using generalized factors of assessment predicted energy cost savings to estimated potential energy cost savings. The factors identified in this application are 0.68, 0.66, and 0.61 for each type of system. It is noted that one should be cautious in quoting these factors in future projects. In the future, it would be valuable to study the correlation between measured savings and estimated potential savings in a large number of buildings with retrocommissioning measures implemented. Additionally, further testing and modifications on the PESE Toolkit are necessary to make it a reliable software tool.
  • This thesis has improved Baltazar's methodology for potential energy savings
    estimation from retro-commissioning/retrofits measures. Important improvements and
    discussions are made on optimization parameters, limits on optimization parameter
    values, minimum airflow setting for VAV systems, space load calculation, simulation of
    buildings with more than one type of system, AHU shutdown simulation, and air-side
    simulation models. A prototype computer tool called the Potential Energy Savings
    Estimation (PESE) Toolkit is developed to implement the improved methodology and
    used for testing.
    The implemented methodology is tested in two retro-commissioned on-campus
    buildings with hourly measured consumption data. In the Sanders Corps of Cadets
    Center, the optimized profiles of parameter settings in single parameter optimizations
    can be explained with engineering principles. It reveals that the improved methodology
    is implemented correctly in the tool. The case study on the Coke Building shows that the
    improved methodology can be used in buildings with more than one system type.
    The methodology is then used to estimate annual potential energy cost savings
    for 14 office buildings in Austin, TX with very limited information and utility bills. The
    methodology has predicted an average total potential savings of 36% for SDVAV
    systems with electric terminal reheat, 22% for SDVAV systems with hot water reheat,
    and 25% for DDVAV systems. The estimations are compared with savings predicted in
    the Continuous Commissioning assessment report. The results show it may be helpful
    to study the correlation by using generalized factors of assessment predicted energy cost
    savings to estimated potential energy cost savings. The factors identified in this
    application are 0.68, 0.66, and 0.61 for each type of system. It is noted that one should
    be cautious in quoting these factors in future projects.
    In the future, it would be valuable to study the correlation between measured
    savings and estimated potential savings in a large number of buildings with retrocommissioning
    measures implemented. Additionally, further testing and modifications
    on the PESE Toolkit are necessary to make it a reliable software tool.

publication date

  • May 2010