Targeted Energy Efficiency with Multifacility Benchmarking

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Targeted Energy Efficiency with
Multi-facility Benchmarking
14th Annual E Source Energy Managers'
Roundtable May 9-11, 2007 Boston,
Massachusetts Kelly Kissock Ph.D.
P.E. Associate Professor Department of
Mechanical Engineering, University of
Dayton Principal Go Sustainable Energy
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Corporate Energy Managers

• Responsible for multiple facilities
• Responsibilities include
• Reducing energy costs
• Energy cost budgeting
• Documenting energy / environmental performance
• Carry out responsibilities with limited
  resources
• Budget
• Time
• Expertise

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Some Broadly Available Resources

• Utility billing data
• Free, accurate
• Production/sales/occupancy data
• Primary metrics of most corporations
• Weather data
• Actual and typical free over internet
• Computational and graphical power of computers

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Utilizing Resources to Fulfill Responsibilities

• RESPONSILITIES
• Responsible for multiple facilities
• Responsibilities include
• Reducing energy costs
• Energy cost budgeting
• Documenting energy / environmental performance
• Carry out responsibilities with limited
  resources
• Budget
• Time
• Talent

• RESOURCES
• Utility billing data
• Free, accurate
• Production/sales/occupancy data
• Primary metrics of most corporations
• Weather data
• Actual and typical free over internet
• Computational and graphical power of computers

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Benchmarking

• Benchmarking comparisons
• Benchmarking types
• Multi-facility benchmarking
• Compare facilities
• Internal and external to corporation
• Identify worst, average and best performers
• Past-performance benchmarking
• Compare performance over time
• Identify improving and declining performance

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Benchmarking Difficulties

• Influential variables (weather, production,
  sales, occupancy) vary
• By location
• Over time
• Thus, hard to compare energy performance
• Between locations
• Over time
• Rarely helps understand performance
• Why is a facility the best, average or worst?
• Why is performance improving or declining?
• Difficulties reduce effectiveness of benchmarking
  efforts

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Our Method To Improve Usefulness of
Benchmarking

• Uses power of computer
• Graphical, statistical and engineering analyses
• Transparent trustworthy results
• Complementary to EnergyStar 6 metrics instead
  of one
• Target energy efficiency efforts
• Save time and money

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Facility Metrics Method

• 1) Characterize performance with
• Energy signature model
• 2) Remove noise with
• Normalized annual consumption NAC
• 3) Track performance with
• Sliding NAC analysis
• 4) Benchmark performance with
• Multi-site sliding NAC analysis

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Data Requirements

• Monthly electricity and/or fuel bills
• Influential variables
• Floor area, production, sales, occupancy, etc.
• Actual and typical weather data

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Actual and Typical Temperature Data
http//www.engr.udayton.edu/weather
http//rredc.nrel.gov/solar/old_data/nsrdb/tmy2/
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1) Characterize Performance with Energy
Signature Model

• Develop
• multi-variable
• three parameter
• change-point model
• Of energy use as function of
• temperature
• influential variables.

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Load Gas and Temperature Data

• 3 Years of Gas Bills 3 Years of
  Temperature Data

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Three-parameter Heating (3PH) Model
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Three-parameter Heating (3PH) Model
HS
Eind
Tbal
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Three-parameter Cooling (3PC) Model
CS
Eind
Tbal
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Physical Meaning of Coefficients

• Balance temperature
• Outdoor temperature where heating/cooling begins
• Thermostat set point
• Internal heat gain
• Slope
• Heating/Cooling energy per degree of temperature
• Heat loss/gain through envelope
• Efficiency of heating/cooling equipment
• Production/sales/occupancy
• Energy use per unit prod/sales/occ
• Independent energy use

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Disaggregate Fuel Use
Fuel
Weather
Production/Sales
Independent
Temperature
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Disaggregate Electricity Use
Electricity
Weather
Production/Sales
Independent
Temperature
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Use Budgeting
Fuel
Weather
Production/Sales
Production/Sales
Independent
Temperature
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Use Inform Decisions Allocate Resources
Fuel
Weather
Production/Sales
Independent
Temperature
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Use Identify Opportunities
Electricity
Weather
Production/Sales
Independent
Temperature
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Use Identify Opportunities
Fuel
Weather
Production/Sales
Independent
Temperature
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Use Identify Opportunities
Fuel
Fuel
Weather
Weather
Production/Sales
Production/Sales
Independent
Independent
Temperature
Temperature
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Use Identify Opportunities
Fuel
Fuel
Weather
Weather
Production/Sales
Production/Sales
Independent
Independent
Temperature
Temperature
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Using Models to Identify Problems Chillers Left
On

• R2 0.92 CV-RMSE 22.4

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Using Models to Identify Problems Malfunction
Economizer

• R2 0.70 CV-RMSE 7.8

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Using Models to Identify Problems High Scatter
Poor Control
Observation Heating energy varies by 3X at same
temp! Discovery Didnt close shipping doors!

• R2 0.59 CV-RMSE 68

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Using Models to Identify SuccessLow Scatter
Good Control

• R2 0.99 CV-RMSE 1.1

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2) Normalized Annual Consumption NAC

• Utility bills tells us Annual Consumption,
  which how much energy building consumed with
  weather that actually occurred
• We want to know how much energy building would
  have consumed during normal weather.
• This is called Normalized Annual Consumption
  NAC
• Calculating NAC is a two step process.

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Calculating NAC Step 1 of 2

• Actual gas bills Actual weather
  data Energy signature model

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Calculating NAC Step 2 of 2

• Energy signature model Typical weather
  NAC

production/sales/occupancy
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NAC is Noisefree Energy Consumption

• NAC removes noise from variable weather,
  production/sales/occu-pancy
• NAC reveals true energy use characteristic of
  facility
• NAC allows comparison of sites with different
  weather, production/sales/occu-pancy

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3) Track Noiseless Performance with Sliding
NAC Analysis

• Calculate NAC for every twelve month period in
  data set.
• Change in NAC indicates change in building energy
  use characteristic
• Understand change in NAC by examining change in
  energy signature coefficients

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Sliding NAC
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Sliding NAC and Heating Slope
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Sliding NAC and Independent Fuel Use
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Sliding NAC and Balance Temperature
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4) Benchmark Performance with Multi-site
Sliding NAC

• Quantify average energy performance and
  distribution of energy performance across all
  sites
• Benchmark best/worst NAC and change in NAC
• Benchmark best/worst coefficients and change in
  coefficients

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NAC and Change in NAC
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Slope and Change in Slope
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Sorted NAC

• Overall
• biggest
• gas users
• Independent of
• Weather
• Production
• Sales

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Sorted Independent Energy Use

• Best candidates for
• Timers
• Insulation
• Water heater retrofits
• Water temp set backs

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Sorted Heating Slope

• Best
• candidates for
• Weatherization
• Furnace
• efficiency
• Air conditioning
• efficiency

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Sorted Balance Temperature

• Best
• candidates for
• Programmable
• thermostats
• Temperature
• controls

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Our Experience

• 80 of sites presented problems we expected

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Summary

• Process of
• Characterizing performance with
• Energy Signature model
• Removing weather, production, etc. noise with
• Normalized Annual Consumption NAC
• Tracking change in energy use with
• Sliding NAC analysis
• Benchmarking performance with
• Multi-site Sliding NAC analysis
• Can
• Improve budgeting process
• Identify energy saving opportunities
• Target energy efficiency efforts to improve
  effectiveness
• Measure and track savings and effectiveness
• Save time, money and resources..

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Thank you! questions to kkissock_at_udayton.edu
937-229-2852