Development of the Potential Energy Savings Estimation (PESE) Toolkit

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Development of the Potential Energy Savings
Estimation (PESE) Toolkit

• Jingjing Liu,
• Juan-Carlos Baltazar and David E. Claridge
• Energy Systems Laboratory
• Texas AM University
• August 2010

17th Symposium for Improving Building Conditions
in Hot and Humid Climates
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Overview

• Introduction
• Methodology
• PESE Toolkit
• Example of Application
• Conclusions

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Introduction
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Problem Statement

• Some form of screening is needed to determine
  whether there is sufficient potential for savings
  to justify a EBCx assessment.

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Approach to Problem

• Dr. Baltazar (2006) developed a methodology for
  potential energy savings estimation
• Applied to several retro-commissioned buildings
  in Texas
• To make it a useful tool in EBCx, further
  improvement and testing of the methodology is
  necessary, which requires development of a
  prototype computer tool.

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Approach to Problem

• To make it a useful tool in EBCx, further
  improvement and testing of the methodology is
  necessary, which requires development of a
  prototype computer tool.

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Methodology
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Review of Methodology

• Compares actual energy cost with minimized cost
  from a simulation based on modified bin method
• Minimum energy use cost determined with
• A model representing system performance
• weather conditions, load calculation, air-side
  system simulation
• The numerical procedure for energy cost
  minimization
• Uses sequential exhaustive search
• Generates the input parameter values for minimum
  energy cost

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Review of Methodology
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Review of Methodology

• Potential Energy Cost Savings
• Actual Energy Cost Minimum EnergyCost
• Energy Cost (ELE CostLTEQ ELE CostFANP)
  CHW Cost HHW Cost

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Review of Methodology
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Improvements on Methodology

• Optimization Parameters
• Five parameters exterior and interior zone room
  temperature set points, cold deck and hot deck
  (only for dual duct) leaving air temperature set
  points, outside air flow rate.
• Space load calculation
• Based on modified bin method
• Enabled by optimizing room temperature

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• Buildings with Multiple Types of Systems
• Permitted
• AHU Shutdown Simulation
• A new empirical method is developed and used for
  estimating the energy use during the AHU shutdown
  and start-up period.

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PESE Toolkit(Potential Energy Savings Estimation)
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Overview of PESE Toolkit

• Purpose to test the improved methodology
• Developed with Excel VBA 2003
• Important features
• User friendly input interface
• Space load calculation is included
• User can decide which optimization parameters to
  activate
• Simulation models of four common HVAC systems
• Comprehensive output for each bin and illustrated
  in plots.
• Input and output

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Building information, system information and
optimization options input in the calibrated
simulation
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Bin data input in the simulation
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Bin data input in the simulation
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Chart Sheet Plot Unit
(1) Energy cost and saving (a) Energy cost during occupied Thousand
(1) Energy cost and saving (b) Energy cost during unoccupied Thousand
(1) Energy cost and saving (c) Savings during occupied Thousand
(1) Energy cost and saving (d) Savings during unoccupied Thousand
(2) Consumptions and loads during occupied period (a) Measured and optimized energy use MMBtu MWh
(2) Consumptions and loads during occupied period (b) System consumption loads and bin hours MMBtu/hr hours
(2) Consumptions and loads during occupied period (c) Exterior zone loads MMBtu/hr
(2) Consumptions and loads during occupied period (d) Interior zone loads MMBtu/hr
(3) System parameters during occupied period (a) Temperatures F
(3) System parameters during occupied period (b) Air flow rates Thousand cfm
(3) System parameters during occupied period (c) Humidity ratios and relative humidity Lbw/lbda
(3) System parameters during occupied period (d) Air flow ratios
(4) Consumptions and loads during unoccupied period (a) Measured and optimized energy use MMBtu MWh
(4) Consumptions and loads during unoccupied period (b) System consumption loads and bin hours MMBtu/hr hours
(4) Consumptions and loads during unoccupied period (c) Exterior zone loads MMBtu/hr
(4) Consumptions and loads during unoccupied period (d) Interior zone loads MMBtu/hr
(5) System parameters during unoccupied period (a) Temperatures F
(5) System parameters during unoccupied period (b) Air flow rates Thousand cfm
(5) System parameters during unoccupied period (c) Humidity ratios and relative humidity Lbw/lbda
(5) System parameters during unoccupied period (d) Air flow ratios
In each chart sheet, (a), (b), (c), (d) refer to the upper left, upper right, lower left and lower right plot. In each chart sheet, (a), (b), (c), (d) refer to the upper left, upper right, lower left and lower right plot. In each chart sheet, (a), (b), (c), (d) refer to the upper left, upper right, lower left and lower right plot.
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Example of Application
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Sanders Corps of Cadets Center

• Introduction
• Single story display hall (19,363ft2)
• 800AM-500PM (Mon-Fri)
• One AHU, SDVAV
• CC implemented by 11/2/2007
• One year Post-CC hourly data of weather and
  measured consumption

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• Resetting Minimum Airflow
• Reset values are also used in the following
  optimization

Ext. zone (cfm) Int. zone (cfm) Savings
Occupied 7,200 ? 3,820 11,080 ? 3,600 20
Unoccupied 6,370 ? zero 9,800 ? zero 54
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Optimization parameter setting limits
Opt. Parameter Opt. Parameter Unit Lower Limit Upper Limit Grid Division
Occupied Te F 70 78 9
Occupied Ti F 68 72 5
Occupied TCL F 55 70 16
Occupied VOA cfm 600 4,500 11
Unoccupied Te F 65 85 11
Unoccupied Ti F 65 85 11
Unoccupied TCL F 55 70 16
Unoccupied VOA cfm 0 4,500 12
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Optimized parameter settings during occupied
period
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• Potential Energy Cost Savings
• An extra 7 (occupied) and 12 (unoccupied)
  savings compared with resetting minimum airflow

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Conclusions
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• Conclusions of Work
• Methodology has been improved and implemented in
  a prototype computer tool
• Using the tool only requires limited information
  about the building and the built-in HVAC system,
  as well as sorted bin weather and energy
  consumption data.
• It provides comprehensive output of energy costs
  and savings, space loads, and system parameters,
  etc.

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Thanks!