1. Turning Energy Data into Operations Intelligence Presented to: FMA September 17, 2013

2. Energy Practice Overview Energy demand experts: Professional Engineers(PE), Certified Energy Managers (CEM®) International Measurement and Verification Protocol (IPMVP) certifications Process industry expertise Energy analytics Energy Benchmarks Real-time market intelligence powered by UTS technology Market Insights and Benchmarks Procurian Experts: The leading independent provider of Comprehensive Procurement Solutions, managing $27 B in spend to help leaders drive sustainable changes to their cost structure Proven measurable bottom-line savings for leading companies on a global basis Process Rigor and Technology © 2013 Procurian. All rights reserved.2

3. Today’s Objectives Provide you with tools to take back to your organizations to help make the case for change Identify key strategies to help you take the first/next step Highlight case studies for examples of ways clients can translate energy data into operations intelligence that connects to the bottom line © 2013 Procurian. All rights reserved.3

4. Energy Intelligence and Decision Optimization Energy Analysis + Companies are continually investing in operational and energy efficiency projects Leading companies are beginning to collect energy data Challenge is converting data into usable information Closed loop system = Decision Optimization Energy Data Measurement Verification/Tracking of project performance Performance benchmarking Energy Efficiency recommendations © 2013 Procurian. All rights reserved.4

5. Converting Data to Intelligence: Production line example 15 minute data for 1 week Power (kW) Total Line Power Product Change Idle vs. Off Data Collection: −Identify “typical” system to meter −Install meters to collect energy data −Collect “production” data −Collect equipment operations data Analysis: −Split data into working/non-working data sets −Use your eyes Results: 1.Product change, driven by small feature 2.Idle vs. off Savings 3.Operator best practices (not shown) © 2013 Procurian. All rights reserved.5

6. Industrial Furnace Analysis 5 Day Working Profile Optimizing Operations Restart Analysis 3 Months, Workdays Only Load Relatively Flat Random Operating Profile Operates in 80-120kW Band Idle Periods System Restart Measure & document system start peak kW driver Energy data provides equipment utilization metric Quantify impact of high/low idle ops. © 2013 Procurian. All rights reserved.6

7. Industrial Furnace Load Profile and Savings Model Optimization 2 – Savings = 17% Optimizing Operations Optimization 1 – Savings = 8% Load Relatively Flat Create load profile (sort power max. to min.) Identify power level that signals “idle” Create theoretical profile for “low” idle Include re-start costs Add operational limits, assess, and pilot Savings Restart Low Idle Savings Restart Low Idle © 2013 Procurian. All rights reserved.7

8. Pump Optimization Audit All pumps off Problem: Optimize Operation −Five identical pumps/motors −Four on weekdays/ One on weekends Analysis: −4 weeks data collected −Conducted single pump tests Results: 1.“Best” pump uses 25% less power than “worst” 2.Pump combinations can be optimized 3.Equipment on loop impacts power Annual Energy Savings of 20% © 2013 Procurian. All rights reserved.8

9. Pump Optimization On-going Monitoring Problem: Savings Decay −Project implemented and savings verified −Baseline and Target models establish Analysis: −Weekend shutdown is sporadic −Optimal pump combo not always run −Cooling loop flow changed Results: −Always-on monitoring and alerting required −Weekly Performance report for manager −Actual operation indicates additional savings potential “Easy” operational savings do not persist without ongoing monitoring New Savings “off” Opportunity Non-compliance Cooling loop changed © 2013 Procurian. All rights reserved.9

10. Action Observed Savings Installations of meters 0 to 2% (the “Hawthorne effect”) Bill allocation only 2-1/2 to 5% (improved awareness) Building tune- up 5- 15% (improved awareness, and identification of simple O&M improvement) Continuous Commissioning 15 to 45% (improved awareness, ID simple O&M improvements, project accomplishment, and continuous monitoring) * “Energy Management Guidance - EERE”, U.S. Department of Energy, 2012. AEM Insight Enabled Savings AEM Realized Persistent Savings Increasing Project Cost Savings used for ROI Continuous Monitoring is Required to Ensure Persistence of Energy Cost Savings Solution: Continuous monitoring and commissioning offers significant savings by ensuring that improvements persist over time Reference: Lawrence Berkeley National Laboratory 2009, “A Golden Opportunity for Reducing Energy Costs and Greenhouse Gas Emissions” Problem: Traditional approaches to energy management are failing to deliver sustainable cost savings After operational changes and/or capital improvements, energy performance declines over time as operators go back to the “old way” and equipment set points revert back Increasing Project Complexity Savings Decay © 2013 Procurian. All rights reserved.10

11. Chiller Plant Case Study Chillers found to be short cycling Temperature set point was significantly lower than required Temperature control dead band 5x tighter than required Further investigation found chiller refrigerant to be low Control System was found to be incorrect system for installed chiller Power (kW) Chilled Water Load Results:  30% energy reduction  Prepared business case for control system retrofit (8 mo. payback)  Coordinated with corporate engineering to increase control dead band Results:  30% energy reduction  Prepared business case for control system retrofit (8 mo. payback)  Coordinated with corporate engineering to increase control dead band Short Cycling Baseline Control Model New Control Model © 2013 Procurian. All rights reserved.11

12. Take-Away Energy Data must be converted to Energy Intelligence −Identify, validate, and standardize best practices −Use data to challenge status quo Low-cost operational changes (easy to make, easy to lose) −Savings from audits and Kaizen events do not persist −Hardware/Capital project savings also decay (but at slower rate) Always-on Monitoring & Reporting is required to realize savings © 2013 Procurian. All rights reserved.12