energy management’s hottest couple: utility bill & interval data
TRANSCRIPT
Energy Management’s Hottest Couple: Utility Bill & Interval Data
September 17, 2015
Optimize energy performance and costs by combining utility bill & interval data
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Meet your presenters
Erik Becker VP, Sales
Urjanet
Alisdair McDougall Senior Manager,
Advisory Services Verdantix
D.j. Amis Director,
Product Management Urjanet
Jeff Floyd VP,
Global Data Operations Schneider Electric
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What will we cover today? The Future of Energy Management: Gaining financial energy insights from the boiler room to the board room
Ways to Receive Utility Data: Pros and cons
Unlocking the Value of Combining Utility Bill & Interval Data: Using software and data visualization tools to drive deeper insights
Case Studies & Examples: Translating improved visibility of energy performance and costs into results
5 Live Q&A
The Future of Energy Management Gaining financial energy insights from the boiler room to the board room
6 Firms are increasingly developing global energy management strategies as energy makes its way up the corporate agenda
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As with all strategic issues $$$$ is the main focal point
8 Although energy impacts profitability, few firms have any visibility into consumption or expenditure
9 Firms that do generally rely on utility meter data, but that can only take you so far
Non half hourly meters • Energy consump4on
• Energy spend
Half hourly / 15-‐min interval meters • Out of hours usage
• Peak charge analysis
10 Firms should not be making strategic decisions based on a blended unit cost
Cost / Unit
Total Energy Consump4on
Total Energy Spend
11 Instead firms need to understand the underlying factors driving energy costs
How much energy is being consumed?
What is consuming energy?
What drives peak demand?
Which systems are most cri4cal?
What is the tariff?
What are the peak charges?
How accurate is the billing?
Does 4me of use impact costs?
12 Interval data combined with utility and non-energy data provides the context required
Utility Bill Data, Utility Tariff Data, Facility Smart Meter Data, Onsite Generation Data, Regional Utility Tariff Data
Sub-Meter Data
Sensor Data, Sub-Meter Data
Roll-up of Meter And Utility Data From All Facilities
Facility Production Schedule Data, Benchmark Data From Similar Facilities, Regional Carbon Legislation / Factor Data, Local Supply Chain Data
Production Line Schedule Data, Material Usage Data, Benchmark Data From Similar Facilities
Asset Management & Maintenance Data, External Asset Benchmark Data Sources
Financial Data, Production Forecast Data, Carbon Legislation / Factor Data, External Benchmarking Data
Energy Data Non-Energy Data
Utility Bill Management, Energy Procurement & Risk Management,
Energy Reporting, Carbon Reporting, Project & Portfolio
Management, Energy Monitoring & Targeting
Energy Monitoring & Targeting, Project & Portfolio Management
Asset Management & Maintenance
Energy Reporting, Carbon Reporting, Project & Portfolio
Management
Analysis
Asset
Production Line
Facility
Corporate
Dat
a Fr
om E
ach
Leve
l Flo
ws
Into
The
Lev
el A
bove
Level
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……to understand the true cost of energy
How much energy is being consumed?
When is energy being
consumed?
What are the related energy
costs?
What is consuming energy?
What tariff?
14 Only then can you go beyond the low hanging fruit and start to answer the big questions surrounding energy management
How are we performing rela4ve to budget?
Should we change our procurement approach?
Can we incorporate renewable energy?
How exposed are we to energy market fluctua4ons?
How can we lower opera4ng costs?
Should we change our opera4ons to alter our load
profile?
What is the business case for energy efficiency?
What is our forecasted energy consump4on/costs?
Fix vs Replace?
15 Firms that capture data at a more granular level will benefit from greater savings
$- $8 $26 $53 $80 $101 $- $25 $53 $68 $69 $40
$- $14 $36
$57 $81 $80
$-
$200
$400
$600
$800
$1,000
$1,200
$1,400
$1,600
$1,800
1 2 3 4 5 6
Savi
ngs
($ th
ousa
nd)
Year
Year-on-Year Savings By Category
Energy Optimization Supply Side Management Reporting
$- $44 $143
$286 $433
$544
$- $51
$102
$124
$117 $56
$- $14
$36
$57
$81 $80
$-
$200
$400
$600
$800
$1,000
$1,200
$1,400
$1,600
$1,800
1 2 3 4 5 6
Savi
ngs
($ th
ousa
nd)
Year
Year-on-Year Savings By Category
Energy Optimization Supply Side Management Reporting
$- $128
$409
$807
$1,210
$1,508
$-
$71
$137
$159
$143
$60
$-
$14
$36
$57
$81
$80
$-
$200
$400
$600
$800
$1,000
$1,200
$1,400
$1,600
$1,800
1 2 3 4 5 6
Savi
ngs
($ th
ousa
nd)
Year
Year-on-Year Savings By Category
Energy Optimization Supply Side Management Reporting
U,lity bill Total Investment: $0.7m Total Savings: $0.8m Payback Period: 3.3 yrs
Half hourly metering Total Investment: $1.4m Total Savings: $2.2m Payback Period: 3.0 yrs
Sub-‐meter / BMS Total Investment: $2.6m Total Savings: $4.9m Payback Period: 2.1 yrs
16 Savings can be achieved at all levels within a firm across a number of different business units
Ways to Receive Utility Data Pros and cons
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DATA SERVICE
TEXT FILE
XML FILE
Ways to Receive Utility Bill Data
PAPER BILLS
SCANNED IMAGE
STRUCTURED PDF
ELECTRONIC DATA INTERCHANGE
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Paper Bills
Cons
• Environmentally wasteful • Unmanageable when bill volume is
too high • Requires manual data entry and/or
OCR technology to input data points into back-end systems
• Receipt of bill can often come weeks after statement date, resulting in old or delayed data
• Data format not standardized across utility providers
• Error-prone if manually entered into a system
Pros
• Easy to read • All utilities support paper
Paper was the original method of transferring utility bill data. Millions of paper bills are still circulated in the mail each month.
Utility Bill Data
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Scanned Image
Cons
• Requires manual data entry and/or OCR technology to input data points into back-end systems
• Receipt of bill can often come weeks after statement date, resulting in old or delayed data
• Data format not standardized across utility providers
• Error-prone if manually entered into a system
Pros
• Easy to read • Portable due to electronic nature
Physical bills can be scanned and reproduced in .jpeg, .png, .pdf, and other formats for easy electronic viewing.
Utility Bill Data
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Structured PDF
Cons
• Manual data entry and/or OCR technology are often used to input data points into back-end systems
• Data format not standardized across utility providers
• Error-prone and slow if manually entered into a system
• Not scalable if data is manually entered
Pros
• Easy to read • Portable due to electronic nature • Environmentally sound alternative to
paper bills • Higher quality image than a scan • Structured file format can facilitate
technology-based collection methods
PDF files generated by the utility can typically be downloaded from the utility’s website or sent via email.
Utility Bill Data
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Electronic Data Interchange (EDI)
Cons
• Requires time to invest in data interpretation tools
• Variability and lack of standardization among providers
• No bill image • Historical data typically not provided • Need to directly coordinate with each
utility provider
Pros
• Direct B2B communication • No manual data entry needed • Environmentally friendly • Data deliveries typically occur less
than 48 hours after statement date • Standardization within a utility across
tariffs
Some utility providers will generate invoices in Electronic Data Interchange (EDI) format and post it directly to bill payment systems.
Utility Bill Data
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Text File
Cons
• Often limited number of data points • Need to request data from utility
account representative • No bill image • Data format not standardized across
utility providers • Few utilities offer this format
Pros
• Portable due to electronic nature • Environmentally friendly • Data is often available sooner than it
would be with traditional mail • Ability to set parameters and
generate ad hoc requests • Structured file format can facilitate
technology-based collection methods
Utility providers have also been known to offer invoice data by way of .xls or .csv file formats.
Utility Bill Data
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XML
Cons
• Need to request data from utility account representative
• No bill image • Data format not standardized across
utility providers • Few utilities offer this format
Pros
• Portable due to electronic nature • Environmentally friendly • Standardization within a utility across
tariffs • Structured file format can facilitate
technology-based collection methods • There is a broad knowledge base
among developers and systems
Although not a popular option amongst utility providers, the XML format has been chosen by a few of them.
Utility Bill Data
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Data Service
Cons
• Investment of time required to choose the right service provider
• Some data services are expensive • Must understand data service’s
methods of collection in order to determine data quality
Pros
• Can capture everything on the bill • Data format standardized across all
utility providers • Structured repository stores all
collected data throughout time • When collection process is automated:
• Process is extremely scalable and data is delivered quicker
• Data is much more accurate • Single solution for collecting data from
all locations • Can leverage deep utility data
expertise to increase data quality
Utility bill data service providers can collect data from many different types of sources and can fully standardize how the data is presented. Superior service providers will leverage technology to acquire and normalize the data where possible.
Utility Bill Data
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Source scorecard Comparing ways to recieve your utility bill data
Paper Bills Criteria Scanned Images Structured PDF EDI
Data Detail
Timely
Standardized
Scalable
Easy Integration
Image
Storage
Text File XML Data Service
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SUBMETERING
DATA SERVICE
Ways to Receive Interval Data
GREEN BUTTON
PROPRIETARY UTILITY SYSTEM
COMMERCIAL SYSTEM FOR
UTILITIES
ELECTRNIC DATA INTERCHANGE (EDI
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Green Button
Cons
• Not fully standardized or adopted identically by each provider
• Adoption by utility providers is slow and few utilities currently offer Green Button
• Some adopters only make a subset of data available
Pros
• Usually free • Simple to use and export data • Well-publicized
Green Button is an industry-led effort to provide utility customers with easy and secure access to their interval data in a simple and consumer-friendly format.
Interval Data
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Proprietary Utility System
Cons
• Often a high price barrier because utilities are not incentivized to make the data free
• Data format not consistent from provider to provider because they may use other systems
• Different utilities provide different data points
Pros
• More data points and additional viewing options than Green Button
• Easy to receive data if you use only one utility provider
Some utilities develop their own systems to provide their customers with interval data.
Interval Data
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Commercial System
Cons
• Often a high price barrier because utilities are not incentivized to make the data free
• Data format not consistent from provider to provider because providers may use other systems
• Different utilities provide different data points
Pros
• More data points and additional viewing options than Green Button
• Easy to receive data if you use only one utility provider
• Robust visualization, reporting, and notification tools
• Established and well-tested in the market
Utilities often purchase commercial systems that not only provide customers with interval data, but also turn customer usage data into actionable information.
Interval Data
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Submetering
Cons
• Capital expense • Incompatible software platforms • Increased complexity due to many
different device types across locations • Different vendor contracts and
design specs • Challenging to replace and
manage life cycle of old submeters
• Responsible for managing network of submeters and their parameters
Pros
• Set desired interval frequency • Able to check against the master
meter • Asset and functional-level data • Receive data in real-time • Direct control over what you are
monitoring • Can reduce up-front costs by only
submetering high energy-consuming facilities and equipment
• Easy for small organizations to keep submetering devices and platform consistent
Certain companies and organizations that want to monitor specific pieces of equipment or other individual loads for more robust analytics usually utilize submetering.
Interval Data
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Data Service
Cons
• Sometimes data can be subject to utilities’ hardware and software issues
• The majority of the data will not be in real-time
Pros
• Single format type • No cross-platform communication
and translation challenges • Single point of contact for data
questions and issues • Extremely scalable • Consistency in data format across all
locations • Few technical internal resources
needed • No need to manage complicated
system • Standard pricing
An interval data service provider can gather interval data from a variety of sources. Some leverage utilities’ smart meter infrastructure and can collect data from customers’ utility portals, standardize it, and deliver it into business systems.
Interval Data
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Source Scorecard Comparing ways to recieve your utility bill data
Green Button Criteria Proprietary System
Commercial System
Submetering
Price Consistency
Standardized
Real-time
Control Interval
Easy Integration
Analytics Tools
Data Detail
Data Service
Unlocking the Value of Combining Utility Bill & Interval Data
Using software and data visualization tools to drive deeper insights
37 Confidential Property of Schneider Electric
Energy and sustainability services 4 steps to leverage your data Focus today on how you can analyze and act on your data
Identify
Determine what data exists and identify gaps based on required KPI’s
Capture
Integrate data into a SaaS energy and
sustainability management platform
Analyze
Analyze integrated data across the enterprise to
prioritize actions
Act
Take action, implement recommendations
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Identify
Identify the energy & sustainability data available in your facilities
Capture and clean data in the cloud Integrate diverse datasets and ensure data quality
Capture
• Monthly Invoices • Spreadsheets • Manual Data • Utility Interval Data • Metering & Submetering • Energy Market data • Financial Data • Other data (Weather) • Survey Data
Collect, aggregate and clean data across your
enterprise
API’s
Integration methodologies
DATA
Schneider Electric’s energy and sustainability platform
300K sites 4500 clients €30 Billion energy spend managed 40 Million metric tons CO2 managed
Analyze
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Enable your teams to act on data Use internal or external experts to make recommendations to ACT
Act
Take action, implement recommendations > Deploy capital projects > Integrate renewable energy to meet goals > Deploy best practices to reduce energy or water consumption in top-consuming locations
Data connection & integration service
Connect directly to utility data
Connect to building equipment or software
Customer Portfolio of Buildings
AND/OR
Leverage and analyze your data
Case Studies & Examples Translating improved visibility of energy performance and costs into results
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> Historical data captured and used to develop a baseline for testing current data against historical trends
> Invoice validation highlighted a significant drop in water consumption at one location > Worked with the utility to conduct an in-depth review of all accounts > Result: Utility applied incorrect conversion factor resulting in the client being overbilled for over a year - total credit of $64,492
Case Study
Real examples of customer data in action Large medical company overbilled due to vendor conversion error
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Ø > Customer needed data to help make decisions: - How to best renew energy supply contract - Whether to re-commission thermal storage system
Ø > Combined historical energy data and predictive-data services to analyze past and current energy consumption pattern relative to the forecasted load
Ø > Schneider leveraged forecasted load data to find a supplier that was able to discount the price by $8.80 /MWh
> Result: $85,000 per year savings, $300,000 total savings and had the data to confidently make the decision to move forward and re-commission thermal storage system
Real examples of customer data in action Commercial property leverages data to negotiate better rate
Case Study
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> Hotel chain wanted to leverage its electricity purchasing power in the market
> Detailed and accurate interval consumption data would be required for the supplier to appropriately balance the load
> By accurately tracking and managing the loads, the hotel chain could protect $3M of the overall $18M in projected savings
> Result: Savings $18M a year
Real examples of customer data in action Hotel chain “escapes” its utility
Case Study
