Skip to main content
x
Overview

2019 Energy Management Leadership Awards

 

What is the Energy Management Leadership Awards?

 

The Energy Management Leadership Awards recognize organizations using an ISO 50001-certified energy management system to save energy and reduce costs. The CEM Energy Management Leadership Awards raise global awareness of the benefits of energy management, helping accelerate broad implementation of these proven systems to help meet organizational, national and global energy and climate goals.

 

What is the Clean Energy Ministerial (CEM) Energy Management Working Group (EMWG)?

 

View the EMWG homepage for more information, or learn more about the Clean Energy Ministerial.  

 

Who should apply?

 

View Who Should Apply in the Official Rules

 

How do I apply?

 

View How to Apply in the Official Rules

 

How are the winners selected? 

 

View Selection Process in the Official Rules 

 

When and how will the winners be announced? 

 

View Global Recognition and Award Notification in the Official Rules 

 

We have a case study already written about our ISO 50001 experiences and results. Can we submit that?

 

All entries for the Energy Management Leadership Awards should be submitted using the Case Study Template. Existing content can be pasted into this template, though entrants should review the Case Study Topics and Evaluation Criteria and ensure you have addressed the topics to be scored during the selection process.

 

Must I address every item listed in the CEM case study template?

 

To be competitive for the CEM Award of Excellence and any applicable national awards, entrants should review the Case Study Topics and Evaluation Criteria and ensure the topics to be scored during the selection process have been addressed. 

 

Can I change the subheadings in my case study or must I use what is in the template?

 

We encourage organizations to use the headings in the case study template. Organizations are welcome to additional subheadings. 

 

What is the maximum page or word limit in submittal of a case study? 

 

Submitted case studies must be 4–6 pages in length; shorter or longer case studies will not be accepted. 

 

What if my organization has multiple sites certified to ISO 50001? Should we submit a case study for each site or can we integrate our sites’ experiences into one case study?

 

An organization may submit either a single entry that collectively describes ISO 50001 implementation and results for multiple sites or separate entries for its different ISO 50001 certified sites. We encourage you to choose whichever path represents your unique story. Please see additional guidance below. 

 

The CEM Energy Management Leadership Awards program has received entries that highlight a variety of approaches to achieve ISO 50001 certification. We are hearing exciting stories from the field. For example, we’ve heard of companies with robust corporate energy management strategies that establish an EnMS at a corporate level and leverage that EnMS (and associated expertise) across its sites to maximize implementation efficiency and drive the portfolio toward company goals. We’ve heard of individual sites independently taking on energy management using ISO 50001 and achieving impressive savings, drawing the attention of senior management. And we’ve heard of organizations with multiple individual sites certified to ISO 50001, reflecting the outcomes of a broader corporate energy management strategy that supports individual facility action. 

 

In each case, organizations and sites are displaying agility and innovation while tackling challenges and creating solutions that fit. We welcome all ISO 50001 certified organizations to submit case studies for the award program, and look forward to learning more about the variety of approaches being used to drive value within the organization through ISO 50001.  

 

Guidance on developing your case study: Regardless of the path you choose, case studies should describe the strategy and decision for pursuing certification(s) and how it relates to a business, corporate, and/or site strategy.

 

For entries with multiple sites: 

  • If you choose to submit a case study that addresses a corporate energy management system with multiple sites included within the scope of the ISO 50001 certificate, the case study entered needs to cover the entire full scope of the certification.  
  • If you submit a case study describing ISO 50001 implementation and results for multiple sites, a copy of each relevant site’s ISO 50001 certificate is required. 
  • Quantitative results can be provided in aggregate, averaged, or separately by site (e.g., for the “Case Study Snapshot” box included in the Case Study Template, organizations can enter an aggregate, average, or several individual site results for the following fields: energy performance improvement, annual energy cost savings, cost to implement, and payback period). 
  • In the “Case Study Snapshot” box, a summary may be included for industry and location (e.g., 4 sites in Sweden, 2 sites in Korea, 3 sites in the United States). 
  • Photos of different sites may be included throughout the case study.

 

What does "accredited" certification body mean? Accredited by whom?

 

Certification bodies are accredited by Accreditation Bodies that are members of the International Accreditation Forum (IAF). The primary function of IAF is to “develop a single worldwide program of conformity assessment which reduces risk for business and its customers by assuring them that accredited certificates may be relied upon.” Accreditation ensures that the certification body has been independently evaluated against internationally recognized standards to conduct ISO 50001 audits with impartiality and competence. Accreditation provides confidence in certification outcomes.  

 

Organizations entering the awards program must have ISO 50001 certificates issued by an accredited certification body. Once organizations submit their entry and ISO 50001 certificate(s), the Secretariat will identify the body that accredited the certification body, determine if the accreditation body is an IAF member, and confirm that the certification body’s accreditation is current. If the certificate does not readily identify the accreditation body, the Coordinator may inquire further with the certification body to verify its accreditation status for ISO 50001, and whether the scope of accreditation covers the applicant’s country. 

 

View Accreditation Body members of IAF, listed by country.

 

Can I apply for an award if my organization participated in the 2016, 2017, or 2018 awards program?

 

Previous award recipients may enter the 2019 awards program if: 

 

  • the scope and boundaries of the EnMS have changed (e.g., an expanded scope from single facility to multiple or certification of a different facility within the organization) or 
  • after recertification to ISO 50001. 

 

The program does not accept re-entry of case studies that received awards from this program in past years (i.e., revised versions of case studies that address the same scope and boundaries and include the same ISO 50001 certificates). Organizations that have previously won an Award of Excellence in Energy Management are not eligible for the 2019 Award of Excellence, but are eligible to receive an Insight Award.

 

Can I see an example of how to calculate the energy performance improvement?

 

The following example shows a company using the Good and Better methodologies to calculate its energy performance improvement. The company includes the Better calculation on its entry to earn a higher score.

 

-------------

 

As an example, a manufacturing facility monitors monthly energy consumption and production output for a baseline period (calendar year 2016) and a reporting period (calendar year 2017).  The only energy source for the facility is electricity.  In 2016, the facility consumed 10,520,447 kWh of electricity and produced 64,501 units of output.  In 2017, the facility consumed 10,734,997 kWh of electricity and produced 68,642 units of output. 

 

“Good”

 

To calculate energy performance improvement using the Good methodology, an organization calculates the energy intensity for each year by dividing the total energy use by a variable that the organization determines appropriate, such as production output, number of building occupants, value added, or some other variable.  For the example manufacturing facility, the energy team chooses to calculate energy intensity by dividing the total energy consumption by the production output for each year.

 

The table below summarizes the data and the energy intensity (kWh/unit) for the two years.

 

 

2016

2017

Electricity (kWh)

10,520,447

10,734,997

Production (Units of output)

64,501

68,642

Energy Intensity (kWh/unit)

163.11

156.39

 

To determine energy performance improvement using the Good methodology, the facility compares the 2017 energy intensity to the 2016 energy intensity using an equation similar to the performance improvement equation given earlier:

 

EPI calculation

 

Thus, based on the change in energy intensity, the Good methodology results in an energy performance improvement of 4.12% between 2016 and 2017.

 

For this approach, please explain how you took into account the influence of energy driving and governing factors when determining the energy performance improvement.

 

“Better”

 

If this same facility decides to use the Better methodology to determine the energy performance improvement between 2016 to 2017, then a regression analysis will be needed.  For most needs, a linear regression model is sufficient.  A linear regression model takes the form of:

 

linear regression model

 

Where xi is the relevant variable quantity, b0 is the base load energy consumption not related to relevant variables, and bi>0 is the incremental energy consumption per unit of that relevant variable.

 

The facility uses a spreadsheet tool to perform this type of statistical analysis using the same energy consumption and production data while adding weather as a relevant variable, based on their assumption that colder winter weather impacts the energy needs of the facility.  The impact of colder weather is commonly calculated using Heating Degree Days.  The facility personnel used online weather data resources to determine that the Heating Degree Days for the facility’s location for each month in 2016 and 2017.  The Heating Degree Days totaled 5,267 for 2016, and 5,726 for 2017. 

 

The table below summarizes the monthly input data used for the regression analysis. 

 

 

Electricity (kWh)

Production (units)

Heating Degree Days

2016

January

           921,551

           5,354

           1,260

February

           928,883

           5,320

           1,234

March

           914,499

           5,312

               806

April

           889,693

           5,312

               283

May

           868,909

           5,283

                 57

June

           840,407

           5,310

                   9

July

           718,741

           5,320

                           0

August

           797,594

           5,347

                  0

September

           813,532

           5,472

                   7

October

           900,204

           5,481

               201

November

           947,741

           5,497

               645

December

           978,693

           5,493

               765

2016 Totals

10,520,447

64,501

5,267

2017

January

           918,069

           5,653

           1,324

February

           939,050

           5,695

           1,180

March

           938,331

           5,728

               912

April

           925,986

           5,740

               308

May

           882,558

           5,750

               111

June

           826,817

           5,753

                  0

July

           775,322

           5,682

                  0

August

           847,794

           5,745

                   1

September

           843,841

           5,757

                 44

October

           881,970

           5,712

               259

November

           958,582

           5,699

               749

December

           996,677

           5,728

               838

2017 Totals

10,734,997

68,642

5,726

 

The results of the regression analysis include a “modeled” value for 2017 energy consumption.  In this case, the facility personnel chose to perform a “forecast” normalization, which estimates the 2017 energy consumption assuming the weather and production in 2017 influence energy consumption the same as they did in 2016. 

 

The US DOE’s EnPI Lite tool was used to develop the model, and details on the model are at the end of this example.  This tool uses statistical validity checks to ensure models are valid, and details of these checks are also found at the end of this example. (The same statistical analysis can be conducted using Microsoft Excel with the same results.)

 

If a site has more than one energy source, a regression model should be developed for each energy source, and the relevant variable can be different for each sources (e.g., cooling degree days applies to electricity while heating degree days applies to natural gas).

 

The table below summarizes the results of the linear regression.

 

 

2017 (Modeled)

2017 (Actual)

Electricity (kWh)

11,731,322

10,734,997

 

To determine energy performance improvement using the Better methodology, the facility compares the 2017 modeled energy consumption to the 2017 actual energy consumption using an equation similar to the performance improvement equation given earlier:

 

EPI better methodology

 

Thus, based on the regression model required by the Better methodology, the energy performance improvement for the facility was 8.49% between 2016 and 2017.  For this particular example, the Better methodology results in a higher estimated improvement in energy performance relative to the Good methodology.  Note that the Better methodology will not always provide higher energy performance improvement results, but typically will be a more accurate reflection of performance improvement.

 

If your organization uses a different formula than noted above and wish to include this in the case study, please provide rationale and fully explain the calculation of energy performance improvement, for review by the selection committee.

 

EnPI Lite model results

 

forecast model details

 

EnPI LITE Statistical Validity Checks

  • An F test for the overall model fit must have a p-value less than 0.10 (i.e., the overall fit is statistically significant at the 10% significance level). For a 12 month data set:

 

If the model includes:

The F-stat value must be
greater than this F-critical value:

1 variable

3.2850

2 variables

3.0065

3 variables

2.9238

4 variables

2.9605

5 variables

3.1075

 

  • All included variables in the model must have a p-value less than 0.2
    • This does not include the intercept p-value
  • At least one of the variables in the model must have a p-value less than 0.10
  • The R2 for the regression must be at least 0.5
  • All Relevant Variables must be valid (see below)

 

For the model to be valid for calculating adjusted energy consumption, the average of the predictor (x) variables used to calculate the adjusted consumption from the model must fall within either:

  • The range of observed data that went into the model or
  • Three standard deviations from the mean of the data that went into the model.

 

Our company won’t allow us to disclose financial information such as cost savings and expenditures, but we can provide information on energy savings in gigajoules (GJ). Can I still participate in the 2019 awards program? Will I lose points for not sharing this information?

 

Yes, you can still participate. If sharing this information is not an option, we recommend providing the payback period on the ISO 50001 EnMS implementation that normalizes the economics without having to share absolute or specific financials. A simple payback period can be calculated by using the following formula: Payback Period (years) = Cost to implement EnMS/ Annual operational energy savings.  In the Case Study Template: In the table titled “Case Study Snapshot” add a row at the bottom; in the left column enter: “Payback Period (years)” and in the right column: enter your payback period. In the Entry Form, leave the relevant financial cell empty and in Row 72: enter “Payback Period (years)” (under Cost to Implement EnMS) and then enter the year(s) in column K. 

 

For points, this program asks for the financial information to provide a full story of the value of using an ISO 50001 EnMS – these case studies are helpful and insightful for other organizations that are considering ISO 50001. Payback period will be accepted though full points might not be awarded. That said, the numbers are one part of the story and should be well supported for either financial information or payback period. Please make sure to review the evaluation criteria and address the case study topics as completely as possible.
 

I have more questions about this Energy Management Leadership Awards competition.

 

Please carefully review the Official Rules and our Frequently Asked Questions (FAQ). For additional questions, contact the Award Administrator at EMWG@energetics.com. When appropriate, the EMWG will share new questions (without attribution) and answers via email to organizations that requested updates and via clarifications added to this list of FAQs.
 

 

Countries
Operating Agent
Partners