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Energy Efficiency Journey

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Learning Objectives

Review how IU Health Facilities have utilized the IPL custom incentive “Opt in” program

Identify challenges when implementing a an energy conservation program within day to day operations, repair, and replacement opportunities.

Explain what specific quantifiable measures (metrics) were established to define success of the initiatives or projects

Discuss how technical training, staff education,empowerment and engagement contributed

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Health Facilities Management Challenges

• Across the Board Staffing Cuts (RIFs)

• New Buildings are NOT More Energy Efficient

• Designs are Based on the Lowest First Cost

• Run to Fail Capital Renewal and Deferred Maintenance Strategy

• Unrelenting Regulation

• Aging Facility Management Workforce with No Succession Planning

• Fewer Skilled Trades Paired with More Complex Systems

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Maintenance & Operations Driven to 25% Benchmark for $/SF

• ASHE, IFMA, and UHC are most commonly used

• Incentives and other utilities procurement agreements are helping to hold onto staff

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Heroes of the Process

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• Equipment and Systems –Existing and Future Staff Attitude vs. Aptitude

• Created Energy Team with mixed Resourcing (Insourcing + Outsourcing)

• Leveraging Technology to Improve Productivity

• Dedicated Budget for Training

• One on One Training Sessions at the BMS Workstation

Engaged and Empowered

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• Patients are First - Continuity of Care

• Collaborative & Creative Thinking

• Honest Conversation – what has and hasn’t worked

• Persistence

• High Performing Team

• Subject Matter Experts Participate in Key Training Events

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Let’s be REAL with ourselves

IUH AHC Future of Facilities Engineering

• Keys to Success

– What’s Best for the Patients

– Customer Satisfaction at Every Level

– Prioritize Dollar Needs

– Manage Risk (FMEA)

– Continuous Research & Testing of New Innovative Methods for Improved Efficacy & Efficiency

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Culture; Prioritizing WorkPatient Care Continuity to Risk to Revenue

UPGRADEadditional controls or 

sensors

FIX broken systems or components

OPTIMIZEImplement more 

efficient sequences

ANALYZEData harvesting, 

analysis, visualization

Guide to Infrastructure Improvement  Priorities

Infection Control Patient/Staff Comfort

Fans, coils, humidifiers, dampers, sensors, pumps, and major equipment

Five-year capital planning

M&V requirements for Incentives

Individual Room ACPH, Digital temperature, pressure, filter life, and RH

Discharge air temps, humidifier set points and building pressures

Setbacks, resets, rebalancing, and re-engineering

Digital temperature, pressure, and RH monitoring

DAT reset, OSA/Exhaust Air balancing, Enthalpy based economizer

KPI’s, door pressure alarm counting, temp & RH minutes in alarm, particle counting, ACPHs

Real Time Dashboards

Data visualization

Uptime or reliable systems controllability

DAT, OSA percent, building pressure monitoring, configured faults and alarms (predictive maintenance)

Fans, coils, humidifiers, dampers, sensors, pumps, and major equipment

Fans, coils, humidifiers, dampers, sensors, pumps, and major equipment

Business Performance/Efficiency

“Current Peak Demand was Hindering Ability to Meet Energy Cost Reduction Goals”

Define Goals – Create Actionable Items

A consistent peak demand cause and effect relationship

Analyze – Advanced Data Analytics

The sources and percentage of variable energy consumption and means for metering

Improve – Solutions Customized to Facility

Successfully implement measures without compromising optimal patient care conditions, prioritize needs to invest in legacy equipment 

Measure & Verify – Confirm Improvements & Set New Targets

IPL Incentives were tied to verifiable results

Utility costs reductions impact future utility budgets!

Administrative Support and Decision Making 2

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1New requirement under proposed rule

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Utility Incentives Aid Our Process

• The major electric utilities in Indiana have Rebates and Incentive programs –including the REMC groups

• Utility Programs of two basic types– Prescriptive: Replace “X” with approved “Y” &

get “Z” dollars per unit (lighting, HVAC, motors, pumps, etc.)

– Custom: equipment upgrades, control strategies, that have a proven sustainablereduction in kW and kWh can earn an incentive of $0.0x per kWh saved

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How IU Health Applies The Programs 

• Much of our Facilities and Equipment are older, therefore as we retrofit, upgrade and replace equipment, we always ask:

• “If we choose a more energy efficient piece of equipment or implement a better control strategy, will the utility incentives, yield a reasonable payback on the difference between a “normal” replacement and more sustainable energy efficient solution?”

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IU Health IPL Programs to date

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• Total Incentives earned through IPL programs• These one time incentives represent approximately  $1,500,000 A YEAR in ongoing annual electric savings

• IU Health is on track  to earn close to the annual cap of $500,000 in 2018

Methodist Hospital Energy Star and EUI kBTU per Square Foot

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Monthly Peak Demand from 2009 to present

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Sustained Significant Demand Reduction

New IPL Substation Project Overview

• Reports can be generated to confirm predicted energy savings for internal funding paybacks or IPL custom incentives

• Actual real time energy performance can be determined and compared to the predicted goals.

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BMS Migration to Open Protocol

• Scope: – Open Protocol Language– Wireless Access– Web Browser Access– Resides on the House

Ethernet• Benefits:

– Lower First Cost (and Renovations)

– Improved Maintenance Response Time

– Reduces Maintenance Staffing Requirements

– Reduces Maintenance Costs

Peak Saving Activities by BMS Controls Technician

Messages Not Permitted

Daily Forecast via weather station email

Decision Making and Dissemination of Peaking Shaving Mode

Data and Priority Reports

Graphics and Display

Information Direct to Smartphone or Tablet

Developed Robust Workstation with Training

Trained BMS WatchmanManual initiation of peak shaving 

sequences, assist with communication, set point 

adjustment,manage alarm log

Robust Data Collection During Peak Shaving Periods supports Root Cause Analysis (if needed)

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1Real Time Monitoring.

Real Time Monitoring (RTM) is a tool that informs maintenance and operations personnel of immediate system conditions that affect service continuity, eminent failure, energy efficiency, loss of infection control measures, and thermal comfort.

2Central Plant Energy RTM.

RTM for the central plant systems focuses on reducing or maintaining steam and electrical demand during peak periods as a utility cost reduction measure, rather than relying on daily, weekly or monthly reporting measures.

3Air Handler RTM.

Provides cost of delivered CFM based on control set points and functions and as an early sub optimal detection system based on users or operated adjusted set points to maintain space conditions. 

Real Time Monitoring Examples/Definitions

4Surgery Infection Control

RTM for the surgery department is a tool that informs maintenance and operations personnel of immediate system conditions that affect RH, temperature, or room pressures.

5Domestic Water Chemistry

RTM for the domestic hot water systems informs operators and the water treatment team on current return water temperatures and residuals levels of disinfection chemicals.

Real Time Monitoring Examples/Definitions

6Life Safety PM’s & ILSM’s.

RTM for the life safety PM’s and ILSM’s provides daily updates of life safety work order completion and status of associated interim life safety measures in place.

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Real Time meter of key unit or relationship being measured

Upper limit based on historic data and is reset based on annual review with CDD and HDDs.

Unit or relationship 

measurement

Color indexed range of key relationship

Core Component - Chiller Plant kW/Ton Meter

This data is trended and integrated with alarms/notifications

Open Protocol Platform could Accommodate Building Dashboard Tools

Chilled Water Optimization Project:Real Time Chilled Water Plant Dashboard

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Real Time Need Drove Forecasting Need

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• The operators discovered by using real time monitoring dashboards that not enough time existed to make adjustments to manage peak demand. This created the need for forecasting to allow ample time to prepare or adjust to peak demands

• Anticipating not reacting

Forecasting 3 Step Process

Inputs from BMS Sub-meters

Calculations Using Linear Regression

Formulas

Facility Global Weather Station

Real Time Inputs

Real Time kW

Real Time Tons Delivered

Current Temp & Daily High

Current RH (no forecast available)

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Analysis of Multiple System ParametersEnthalpy vs. Methodist Campus Peak kW, July 2016

Linear Regression ‐ Determine Peak kW 

Source: Energy Consultants Inc.

Image 1: kW vs. Peak by Service

Image 2: Linear Regression

It was established that peak kW management would begin above 85% Load

June 2018 Demand & Ton hours vs. Enthalpy

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Enthalpy vs. kW Linear Regression Analysis

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Monthly Peak Demand

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Chilled Water Ton Hours Usage Trend Report

• Not all systems sub metered

• Cost vs. benefit  analysis of additional M&V for overall plant efficiency, affordability, and management

Meter inaccuracies and inconsistencies

Image 1: Ultrasonic Flow Meter

Prerequisite –Accuracy of Chilled Water Sub‐meters

Prerequisite –Established Standards for M&V Data

Tracking & Trending Network ReliabilityDeveloped Robust Data Standards that Address: 

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Sensor Quality & Calibration

Network Analysis, Data Gaps, and Long Term Storage and Retrieval

Fault Detection Diagnostics (FDD) and BAS Alarms Integration

Trend Every Point, Every 15 Minutes!  

Certain Points Trended at 1 Minute for Fine Tuning

Report on regular intervals

Energy Management Device PM Ticket Template

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Need to manually initiate load shed sequences

Focus on peak reduction cost savings

Peak Real Time and Forecasted Demand Meters

Treatment gap for stroke risk reduction therapies

Low Load High Load Periods

Considerations for BMS Watchman

Moderate Load

90% of Peak Demand Generates a page or 

text alert

Real Time Peak and Forecasted Peak Demand

Cooling Tower Replacement Project:Existing Cooling Towers

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•Reached End of Life; Severe corrosion & leaking

•Could no longer maintain 85 deg. F supply to chillers; required continuous make up water during peak periods

•Support of plate and frame heat exchanger during winter periods was very limited

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Cooling Tower Project:New Cooling Towers & Variable Flow CW

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• Variable Flow Condenser Water

• Condenser Water Supply Reset

• Chiller Head Pressure Control

• Plate & Frame economizer restored

• Cooling Tower optimized to minimize fan energy (maximize surface area)

• Required tower fan kW feedback to test and confirm tower staging sequences

Cooling Tower Project:Converted Chillers to Variable Flow CW

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• Efficiency Targets were Established

• Goal to keep chiller energy optimum and reduce condenser pump energy to a minimum

• Required chiller & pump kW feedback to test and confirm pressures, flows, and staging of each condenser pump

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Plate & Frame Economizer Dashboard:Helped to Inform Operators while “in mode”

Air Handling Optimization Projects:Existing Conditions

• Control set points were overridden

• Sensors had not been regularly calibrated or fixed if broken

• Dampers & actuator not functional

• Poor of if any mixed air control caused simultaneous heating and cooling

• Could not economize when outside enthalpy allowed

• Found less than desired level of humidification rates

36Source: Scofield – Sterling 1985

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Peak Shaving Determination of Tiers

Surgery & ICU

Patient Care & Ancillary Support

Clinics & Public Spaces

Tier #1 Exempt

Offices & Storage (non sterile)

Degree of allowable variance

Inform occupants and end users when and how long peak shaving time periods would occur.  Included campus wide notification through Pulse.

Confirm with end users any elevated temperatures would not negatively affect processes.

Peak Saving Requirements for Occupant Acceptance

* Each Peak Tier Raised DAT by 1°

Tier #2 Closer to Actual (No Margins)

Tier #3 Slight tolerance for elevated temps

Tier #4 cooling degree is more of 

a luxury

Created Tiers for Peak Shaving Initiation

No Peak Shave

92% Peak 95% Peak 98% Peak

Air Handler Tier #1

Air Handler Tier #2

Air Handler Tier #3

Air Handler Tier #4

Peak Load Shed Tier Matrix

Degree of downside risk 

Example of Elevated Discharge Temps:

Tier 4:    No Peak ‐ 55° 92% ‐ 57 ° 95% ‐ 59° 98% ‐ 61°

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Setup of Dashboard & Trending of the Air Handling Control System

• Early detection of performance degradation or need for ‘loop’ tuning

• Prevents over cooling or heating

• Graphic displays to correlate multiple variables

Source: ASHE Commissioning Handbook

Delta P Valve curves were used to calculate flows

AHU 4 & 5;Air Handling Optimization through Real Time $ per CFM Dashboard

• Calculates Costs of– Heating & Humidification– Cooling– Supply & Return Fan Energy

• Alarms/Notifies of– Mixed Air Out of Range– Simultaneous Heating & Cooling– Fan Speed Out of Range

• Before - $5-11.00/10,000 CFM

• After - $2-6.00/10,000 CFM

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Surgery Setback, Temperature, RH and Pressure Monitoring System

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Occupancy Sensor

Temp & RH Sensor

Room Pressure Monitor

Room Temp Adj. & User Interface

Room Phoenix Air 

Valve(s)

Multiple Operator Monitor DevicesHospital VPN

Network

Surgery Rooms User Interfaces, Trending/Reporting & Dashboards

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Domestic Water TreatmentControl Schematic

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Network

Thermostatic Mixing Valve

ClO2 Injection Pump

Continuous ClO2 residual monitoring

BMS Notification of DHW Temp

• Monitoring

• Measuring

• Contributed anecdotally to new CDC Guidelines

• Non typical BMS points

Cold Water Injection Data Analysis Hot water return temp Fault Detection

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• New Technologies

• Aging Equipment

• Changing Energy Rates

• Changing Regulations

• Staff Turnover

• New Buildings

• Research

• M&V; Every Day of Every Year

Our Work is Never Done

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END OF PRESENTATION

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