ISO 50006

© ISO 2013

Energy management systems — Measuring energy performance using energy baselines (EnB) and energy performance indicators (EnPI) — General principles and guidanceLigne de base énergétique et indicateurs de performance énergétique — Principes généraux et lignes directrices

Reference numberISO/DIS 50006:2013(E)

DRAFT INTERNATIONAL STANDARDISO/DIS 50006

THIS DOCUMENT IS A DRAFT CIRCULATED FOR COMMENT AND APPROVAL. IT IS THEREFORE SUBJECT TO CHANGE AND MAY NOT BE REFERRED TO AS AN INTERNATIONAL STANDARD UNTIL PUBLISHED AS SUCH.

IN ADDITION TO THEIR EVALUATION AS BEING ACCEPTABLE FOR INDUSTRIAL, TECHNOLOGICAL, COMMERCIAL AND USER PURPOSES, DRAFT INTERNATIONAL STANDARDS MAY ON OCCASION HAVE TO BE CONSIDERED IN THE LIGHT OF THEIR POTENTIAL TO BECOME STANDARDS TO WHICH REFERENCE MAY BE MADE IN NATIONAL REGULATIONS.

RECIPIENTS OF THIS DRAFT ARE INVITED TO SUBMIT, WITH THEIR COMMENTS, NOTIFICATION OF ANY RELEVANT PATENT RIGHTS OF WHICH THEY ARE AWARE AND TO PROVIDE SUPPORTING DOCUMENTATION.

ISO/TC 242 Secretariat: ANSI

Voting begins on: Voting terminates on:2014-01-20 2014-04-20

ICS: 27.010

ISO/DIS 50006:2013(E)

ii © ISO 2013 – All rights reserved

Copyright notice

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4 © ISO 2013 – All rights reserved

Contents Page

1 Scope ......................................................................................................................................................8

2 Normative references ............................................................................................................................8

3 Terms and definitions ...........................................................................................................................8

4 Measurement of energy performance .............................................................................................. 10 4.1 General overview ................................................................................................................................ 10 4.1.1 General ................................................................................................................................................. 10 4.1.2 Energy consumption .......................................................................................................................... 12 4.1.3 Energy use ........................................................................................................................................... 12 4.1.4 Energy efficiency ................................................................................................................................ 12 4.1.5 Energy performance indicators (EnPIs) ........................................................................................... 12 4.1.6 Energy baselines (EnBs) .................................................................................................................... 13 4.1.7 Quantifying changes in energy performance .................................................................................. 13 4.2 Obtaining relevant energy performance information from the energy review ............................. 14 4.2.1 General ................................................................................................................................................. 14 4.2.2 Defining the energy performance indicator boundaries................................................................. 14 4.2.3 Defining and quantifying the energy sources ................................................................................. 15 4.2.4 Defining and quantifying relevant variables .................................................................................... 16 4.2.5 Defining and quantifying static factors ............................................................................................ 17 4.3 Identifying energy performance indicators ...................................................................................... 18 4.3.1 General ................................................................................................................................................. 18 4.3.2 Identifying users of energy performance indicators....................................................................... 18 4.3.3 Determining the specific energy performance characteristics to be quantified .......................... 19 4.4 Establishing energy baselines and data collection ........................................................................ 21 4.4.1 General ................................................................................................................................................. 21 4.4.2 Determining a suitable data period ................................................................................................... 21 4.4.3 Gathering data and testing EnPIs and EnBs ................................................................................... 22 4.4.3.1 General ......................................................................................................................................... 22 4.4.3.2 Data collection ............................................................................................................................. 22 4.4.3.3 Measurement ............................................................................................................................... 22 4.4.3.4 Data collection frequency .......................................................................................................... 22 4.4.3.5 Data quality .................................................................................................................................. 23 4.4.3.6 Calculating and testing energy baselines ................................................................................ 23 4.5 Using energy performance indicators and energy baselines ........................................................ 23 4.5.1 General ................................................................................................................................................. 23 4.5.2 Calculating changes in energy performance ................................................................................... 23 4.5.3 Determining when energy baselines should be normalized .......................................................... 24 4.5.4 Communicating changes in energy performance ........................................................................... 25 4.6 Maintaining and adjusting energy performance indicators and energy baselines ..................... 25

Annex A (informative) Information generated through the energy review to identify EnPIs and establish EnBs .................................................................................................................................... 27

Annex B (informative) EnPI boundaries in the production process ........................................................... 28

Annex C (informative) Further guidance on energy performance indicators and energy baselines ...... 29 C.1 Examples of static factors and relevant variables .......................................................................... 29 C.2 Types of energy performance indicators ......................................................................................... 29 C.2.1 Measured energy value ...................................................................................................................... 29 C.2.2 Ratio ..................................................................................................................................................... 29 C.2.3 Model-based EnPI ............................................................................................................................... 30 C.3 How to define an energy baseline ..................................................................................................... 31 C.4 Using model-based EnPI to define an energy baseline ................................................................. 31 C.5 Case study ........................................................................................................................................... 31

Annex D (informative) Normalizing energy baselines using relevant variables ........................................ 35

Annex E (informative) Monitoring and reporting energy performance ....................................................... 37 E.1 General ................................................................................................................................................. 37 E.2 Types of monitoring methods and reports ...................................................................................... 37

ISO/DIS 50006:2013(E)

© ISO 2013 – All rights reserved 5

E.3 Target and current EnPI comparison ................................................................................................ 38 E.4 Trend chart ........................................................................................................................................... 39 E.5 X-Y chart ............................................................................................................................................... 39 E.6 Reporting units .................................................................................................................................... 39

ISO/DIS 50006:2013(E)


Foreword

ISO (the International Organization for Standardization) is a worldwide federation of national standards bodies (ISO member bodies). The work of preparing International Standards is normally carried out through ISO technical committees. Each member body interested in a subject for which a technical committee has been established has the right to be represented on that committee. International organizations, governmental and non-governmental, in liaison with ISO, also take part in the work. ISO collaborates closely with the International Electrotechnical Commission (IEC) on all matters of electrotechnical standardization.

International Standards are drafted in accordance with the rules given in the ISO/IEC Directives, Part 2.

The main task of technical committees is to prepare International Standards. Draft International Standards adopted by the technical committees are circulated to the member bodies for voting. Publication as an International Standard requires approval by at least 75 % of the member bodies casting a vote.

Attention is drawn to the possibility that some of the elements of this document may be the subject of patent rights. ISO shall not be held responsible for identifying any or all such patent rights.

ISO 50006 was prepared by Technical Committee ISO/TC 242, Energy Management.

ISO/DIS 50006:2013(E)


Introduction

The purpose of ISO 50001 Energy Management System (EnMS) is to enable organizations to establish the system and processes necessary to improve energy performance. It requires organizations to quantify energy performance and monitor, measure and analyze key characteristics of its operations. It defines operational features as the key characteristics that affect organizational energy performance. Examples of key characteristics include significant energy uses (SEUs), relevant variables related to SEUs, energy baseline (EnB), energy performance indicators (EnPIs), effectiveness of action plans, etc.

This International Standard provides organizations with practical guidance on how to meet the requirements of ISO 50001 related to the establishment, use and maintenance of EnPIs and EnBs in measuring energy performance and energy performance changes. However, the concepts and methods in this standard may also be used by organizations that do not have an existing EnMS. For example, EnPIs and EnBs can also be used at the site, process or equipment level, or for the evaluation of individual energy performance improvement actions.

In order to effectively manage the energy performance of their facilities, systems, processes and equipment, organizations should know how energy is used and how much is consumed over time. EnPIs and EnBs are two key interrelated elements of ISO 50001 that enable the measurement, and therefore management of energy performance in an organization.

An EnPI is a value or measure that quantifies results related to energy efficiency, use and consumption in facilities, systems, processes and equipment. Organizations use EnPIs as a measure of there energy performance.

An EnB quantifies energy performance during a specified time period to be used as a base reference for comparing energy performance. The EnB enables comparisons of energy performance between selected periods thereby enabling the organization to assess changes in energy performance between the periods. The EnB is a reference that characterizes and quantifies an organization's energy performance prior to the introduction of energy performance improvement actions. The EnB is also used for calculation of energy savings, as a reference before and after implementation of energy performance improvements.

Organizations define targets for energy performance as part of the energy planning process in their EnMS. The organization should consider the specific energy performance targets while identifying and designing EnPIs and EnBs. The relationship between EnPIs, EnBs and energy targets is illustrated in Figure 1.

This International Standard includes practical help boxes designed to provide the user with ideas, examples and strategies for measuring energy performance using EnPIs and EnBs.

Figure 1– Relationship between EnPIs, EnBs and energy targets

ISO/DIS 50006:2013(E)


Energy management systems — Measuring energy performance using energy baselines (EnB) and energy performance indicators (EnPI) — General principles and guidance

1 Scope

This International Standard provides guidance to organizations on how to meet the requirements of ISO 50001 related to the establishment, use and maintenance of energy performance indicators (EnPIs) and energy baselines (EnBs) as part of the process of measuring energy performance.

The guidelines in this International Standard are applicable to any organization, regardless of its size, type, location or level of maturity.

This International Standard provides guidance on how to:

identify relevant energy performance information;

establish, use and maintain EnPIs and EnBs.

2 Normative references

The following referenced document is indispensable for the application of this document. For dated references, only the edition cited applies. For undated references, the latest edition of the referenced document (including any amendments) applies.

ISO 50001, Energy management systems – Requirements with guidance for use

3 Terms and definitions

For the purposes of this International Standard, the following terms and definitions apply.

3.1 baseline period specific period of time used as the reference for comparing with the reporting period

NOTE Use for comparing energy performance.

3.2 energy electricity, fuel, steam, heat, compressed air, and other like media

NOTE 1 For the purposes of this International Standard, energy refers to the various forms of energy, including renewable, which can be purchased, stored, treated, used in equipment or in a process, or recovered.

NOTE 2 Energy can be defined as the capacity of a system to produce external activity or perform work.

[SOURCE: ISO 50001:2011, 3.5]

3.3 energy baseline EnB quantitative reference(s) providing a basis for comparison of energy performance

NOTE 1 An energy baseline reflects a specified period of time.

ISO/DIS 50006:2013(E)


NOTE 2 An energy baseline can be normalized using variables which affect energy use and/or consumption, e.g. production level, degree days (outdoor temperature), etc.

NOTE 3 The energy baseline is also used for calculation of energy savings, as a reference before and after implementation of energy performance improvement actions.

[SOURCE: ISO 50001:2011, 3.6]

3.4 energy consumption quantity of energy applied

[SOURCE: ISO 50001:2011, 3.7]

3.5 energy efficiency ratio or other quantitative relationship between an output of performance, service, goods or energy, and an input of energy

EXAMPLE Conversion efficiency; energy required/energy used; output/input; theoretical energy used to operate/energy used to operate.

NOTE Both input and output need to be clearly specified in quantity and quality, and be measurable.

[SOURCE: ISO 50001:2011, 3.8]

3.6 energy performance measurable results related to energy efficiency, energy use and energy consumption

NOTE 1 In the context of energy management systems, results can be measured against the organization's energy policy, objectives, targets and other energy performance requirements.

NOTE 2 Energy performance is one component of the performance of the energy management system.

[SOURCE: ISO 50001:2011, 3.12]

3.7 energy performance indicator EnPI quantitative value or measure of energy performance, as defined by the organization

NOTE EnPIs could be expressed as a simple metric, ratio or a more complex model.

[SOURCE: ISO 50001:2011, 3.13]

3.8 energy performance indicator boundary EnPI boundary boundary of the facility(ies), system(s), process(es) and equipment that includes all the elements for which energy performance is being analyzed 3.9 energy target detailed and quantifiable energy performance requirement, applicable to the organization or parts thereof, that arises from the energy objectives and that needs to be set and met in order to achieve this objective

[SOURCE: ISO 50001:2011, 3.17]

3.10 energy use manner or kind of application of energy

EXAMPLE Ventilation; lighting; heating; cooling; transportation; processes; production lines


[SOURCE: ISO 50001:2011, 3.18]

3.11 facility single installation, set of installation or production processes (stationary or mobile), which can be defined within a single geographical boundary, organization unit or production process

[SOURCE: ISO 14064-3:2006, 2.2.2]

3.12 normalization process of modifying energy data in order to account for changes in relevant variables and static factors to compare energy performance under equivalent conditions

3.13 relevant variable quantifiable variable that impacts energy performance

EXAMPLE Production parameters (production, volume, production rate), weather conditions (outdoor temperature, degree days), operating hours, operating parameters (operational temperature, light level).

3.14 reporting period specific period of time selected for calculation and reporting of energy performance

EXAMPLE The period for which an organization wants to assess changes in EnPIs relative to the EnB period.

3.15 significant energy use SEU energy use accounting for substantial energy consumption and/or offering considerable potential for energy performance improvement

NOTE Significance criteria are determined by the organization.

[SOURCE: ISO 50001:2011,3.27]

3.16 static factors conditions or variables that affect energy performance and do not routinely change

EXAMPLE Facility size, design of installed equipment, the number of weekly production shifts, or the number or type of occupants (e.g. office workers), range of products.

[SOURCE: ISO DIS 50015,3.20, modified – removed “within the M&V boundary”]

4 Measurement of energy performance

4.1 General overview

4.1.1 General

Energy performance is quantified by measurable results related to energy consumption, use and efficiency. In order to effectively measure and quantify its energy performance, an organization establishes EnPIs and EnBs. EnPIs are used to quantify the energy performance of the whole organization or its various parts. EnBs are quantitative references used to compare EnPI values over time and to quantify changes in energy performance.

Energy performance results can be expressed in units of consumption (e.g. GJ, kWh), specific energy consumption (SEC) (kWh/unit), peak power (e.g. kW), etc. The general relationship between EnPIs, EnBs, and energy targets is illustrated in Figure 2.


Figure 2– Relationship between EnPIs, EnBs and energy targets

Energy performance can be affected by a number of factors or variables such as occupancy level, production rate or weather. These factors can be linked to business objectives such as product quality or system reliability.

An overview of the overall process to develop, use and update EnPIs and EnBs is illustrated in Figure 3 and described in detail in Sections 4.2 to 4.6.

Figure 3— Overview of energy performance measurement


4.1.2 Energy consumption

Quantifying energy consumption is one of the main elements for measuring energy performance and energy performance improvements.

Energy consumption can be represented in volume and mass flow or weight units (fuel) or converted into units that are multiples of joules or watt-hours, such as gigajoules (GJ) or kilowatt-hours (kWh) of electricity. Energy consumption is typically measured using permanent meters or sub-meters or through temporary metering. The values can be measured directly or can be calculated.

When multiple forms of energy are used, it is useful to convert all forms to a common unit of measure. Care should be taken however to perform the conversion in a manner that most accurately represents total energy consumed including losses in conversion process within an organization. Conversion of all forms of energy into equivalent units of source energy is a well established and practical method to represent total energy. (e.g. converting natural gas energy into electrical energy or steam energy).

Energy consumption should be measured over a specific period of time (e.g. a day, a week, month, or year).

4.1.3 Energy use

Energy use is a manner or kind of application of energy. Identifying energy uses can support the clear vision about energy systems, processes and equipment that the organization needs to consider when analyzing energy performance.

As a key characteristic of an organization‟s operations, the energy performance of SEUs should be monitored and measured. This increased attention will typically result in identification of energy performance opportunities and improved operational control.

4.1.4 Energy efficiency

Energy efficiency is one of the characteristics for measuring energy performance and may be used as an EnPI.

Energy efficiency can be expressed in a number of ways, including the following examples:

energy output / energy input – conversion efficiency;

energy required / energy consumed – where energy required may be derived from a theoretical model or some other relationship;

production output/energy input – for example the tons of production per unit energy consumed.

Whenever energy efficiency is calculated both inputs and outputs should be measurable.

4.1.5 Energy performance indicators (EnPIs)

There are many types of EnPIs, including measured values, ratios, statistical models or engineering models. An EnPI can range in complexity, from as simple as the total energy consumption in a given period, or the energy consumed per unit of output, to as sophisticated as a complex mathematical model that characterizes the relationships between energy and relevant variables in a linear or non-linear statistical model.

The EnPIs can apply at facility, system, process or equipment levels to provide various levels of specificity or focus. When choosing its EnPIs, the organization should consider its measurement and monitoring needs as well as what data are currently available. An organization should set a targeted value for each EnPI.

EnPIs should provide relevant energy performance information to enable various groups within an organization to understand its energy performance and take actions to improve it.

For example: within one organization, an executive may require a facility-wide EnPI and an operations manager may require an EnPI for a product line or area of facility. Therefore, energy performance is often represented by more than one EnPI.


Organizations should quantify and compare energy performance using reliably measured energy values. To compare under equivalent condition, EnPIs may need to be normalized with respect to relevant variables or changes in static factors. EnPIs should be selected and developed in order to measure the energy performance improvement that results from the implementation of the EnMS.

4.1.6 Energy baselines (EnBs)

Once the EnPIs are selected, EnBs are established to serve as a comparative reference against each corresponding EnPIs. An EnB should be developed using data collected over a suitable period of time known as the baseline period. An organization should compare energy performance changes from the period for which the EnB has been constructed (baseline period) and the period being evaluated by the EnPI (reporting period). The type of information needed to establish an energy baseline is determined by the specific purpose of the EnPI.

Where the effects of the variables need to be accounted for, an EnB can be normalized using variables to compare energy performance between the baseline period and reporting period.

NOTE Where there is no operating history such as in the case of a new facility, it may be necessary to simulate, estimate or calculate the expected energy consumption for the new facility to serve as the EnB against which energy performance will be compared using the EnPI once the facility is operating.

4.1.7 Quantifying changes in energy performance

Energy performance changes can be calculated for facilities, systems, processes or equipment where EnPIs have been chosen.

Comparing energy performance between the baseline period and the reporting period involves calculating the difference in the measured value of the EnPI between the two periods. Figure 4 illustrates the simple case where direct measurement of energy consumption is used as the EnPI and is compared between the baseline and the reporting period.

Figure 4- Concept of Baseline period and Reporting period for EnPI

The baseline period and reporting period should be long enough to ensure that the variability in operating patterns are accounted for by the EnB and EnPI. Typically these periods are 12 months long to account for seasonality in energy consumption and relevant variables.


Care needs to be taken when selecting the time period for EnBs as they may serve as the reference values for EnPIs in relation to a number of time periods. For example, an EnB can be used to define energy performance during a period prior to an organization starting its efforts to improve energy performance.

An organization may decide to re-set its baseline period from time to time either due to significant changes in conditions or eliminate earlier changes in energy performance, such as energy performance improvement actions, which no longer need to be captured. The organization should quantify its current energy performance either continuously or periodically and/or it should quantify the change in energy performance in a reporting period versus its baseline period.

In cases where the organization has determined that relevant variables such as weather, production, building operating hours etc. significantly affect energy performance, the organization should normalize the EnB to compare energy performance under equivalent conditions.

Organizations should determine how best to measure energy performance to serve their specific purposes. This International Standard describes a number of approaches to quantify energy performance.

4.2 Obtaining relevant energy performance information from the energy review

4.2.1 General

The energy review provides useful energy performance information for developing EnPIs and EnBs needed to measure its overall performance, the performance of each SEU and other areas specified by the organization. Measuring energy performance requires access to available organizational energy data, analysis of the data, and processing of energy information to establish appropriate EnPIs and corresponding EnBs.

Annex A illustrates the relationship between the energy review and information needed to identify EnPIs and establish EnBs.

4.2.2 Defining the energy performance indicator boundaries

The boundary of the EnMS comprises the area or the activities within which an organization manages energy performance.

To measure energy performance, suitable measurement boundaries for each EnPI (EnPI boundary) should be defined. EnPI boundaries may overlap.

Considerations in EnPI boundary selection can include:

the existence of SEUs within the EnPI boundary;

the ease of isolating the EnPI boundary from a measurement standpoint (energy and relevant variables);

the extent to which the EnPI boundary definition is aligned with organizational responsibilities; and

the extent to which responsibility for the management of energy within the EnPI boundary is clearly allocated to specific individuals, teams, or groups.

EnPI boundaries should be defined:

for the entire EnMS boundary;

around each SEU (or group of SEUs) the organization designates as a priority to control and improve;

related to specific organizational responsibilities;

according to specific equipment, processes and sub-processes that the organization wishes to isolate and manage ; or

in any other way the appropriate level of management deems useful.


The three primary EnPI boundary types are physical, system-related, and organizational, as described in Table 1.

Table 1 — The three EnPI boundary types EnPI Boundary

Type Description Note

Physical Examples:

- a facility building or fence line in which energy use is measured

- a group of facilities under common management

- usually easy to identify

- often aligns with metering or billing data

System-related A system that represents a significant portion of the facility‟s or organization‟s energy consumption.

Examples: a kiln in a cement factory, or an HVAC system in a commercial building.

Additional meters may be required.

One system may extend across two or more facilities. A boundary around an entire energy system provides a complete picture of energy flow and end-use.

Organizational Often used when the organization is required to report energy performance for legal or business-related requirements.

An organization may encompass many facilities, sites or business units.

An organizational EnPI boundary may be appropriate when all business units have similar energy performance characteristics (e.g. a chain of restaurants).

Organizations may need to aggregate large quantities of data to determine a single EnPI.

Practical help box 1: Determining EnPI boundaries

Evolving business requirements:

Evolving business requirements should be considered when defining EnPI boundaries. Physical changes or business events can occur that change the initially defined EnPI boundaries. For example, a facility expansion or partial shut-down could warrant a change in the EnPI boundaries in which energy is managed and data are collected.

EnPIs at different levels:

The organization may find it valuable to monitor energy at several different levels, each of which defines one (or more) EnPIs. Senior business managers may prefer EnPIs from broader-level boundaries, while operations manager or process engineers may prefer EnPIs based on narrower EnPI boundaries. Energy managers may find use for EnPIs at both levels.

Organizations may determine that the significance of energy use in the EnPI boundary and/or the opportunity for improvement is so high that it can justify the expense of new meters, sub-meters and/or sensors to measure other relevant variables. In such cases, it will specify such metering in its monitoring, measurement and analysis plan.

Reviewing EnPI boundaries:

It may be necessary to revisit EnPI boundaries and revise them based on downstream requirements, such as the availability of appropriate data for certain production lines. Supplemental information on EnPI boundaries in the production process can be found in Annex B.

4.2.3 Defining and quantifying the energy sources

Once an EnPI boundary is defined, the energy flowing across the boundary should be identified. A diagram like the one in Figure 5 can be useful in the energy information required to establish EnPIs. Such diagrams are referred to as Fence Diagrams or Energy Maps. These diagrams visually show flow or energy sources alongside the various energy consuming processes or systems. Such a diagram can also include additional


information, such as metering points and product flow which are important for energy analysis and establishment of EnPIs.

NOTE M=measurement

Figure 5 — Fence Diagram

Energy flows should be measured including all energy inflows and outflows across the EnPI boundary – i.e. import (and export) of electricity, import of primary fuels, changes in stock levels of fuels, import (and export) of other energy sources such as steam or chilled water. All measurements should be conducted taking into account the accuracy and repeatability of the meters and measurement.

The identification of SEUs is an activity within the energy review. EnPIs and EnBs for SEUs require well defined boundaries in order to quantify energy flows. An important consideration for each SEU is appropriate metering for measuring energy consumption that crosses the SEU boundary. All measured values should be validated before exploiting.

4.2.4 Defining and quantifying relevant variables

Depending on the needs of the organization and its EnMS, once the energy sources and SEUs are defined and quantified, additional relevant variables that are likely to have an impact on energy performance should be defined and quantified. Once these additional variables have been identified at each EnPI boundaries, it is important to isolate those variables which are significant in terms of energy performance from the remainder which have little or no influence. While organizations may already have identified obvious relevant variables, additional data analysis is generally required to determine the significance of these variables.

Once the relevant variables have been isolated, further modeling techniques can be used to determine the precise nature of the relationship.

Practical help box 2: Analysis to identify relevant variables

An initial method to assess whether a variable significantly affects energy consumption is to plot the variable against energy consumption using a simple X-Y diagram. If the variable is relevant, one expects to see evidence of a relationship in the scatter of points (see Figure 6a). If the points appear to be scattered around a mathematical function then this is indicative of the presence of relevant variables (see Figure 6b).If the points appear as a random cloud with no evident relationship, the variable is likely not relevant (see Figure 6c).

In many cases, a simple linear relationship is adequate for determining relevance. Certain variables may show nonlinear relationships and the organization will have to decide how to include those variables in the EnPI calculation.


6a) Significant variable 6b) Less significant variable 6c) not significant variable

Figure 6 — Variables with differing levels of significance

To determine if weather is a relevant variable, for example, a trend chart can be used to look for evidence of seasonality in energy consumption throughout the year. If the load is due to heating, the consumption will increase during the cooler winter months. If the load is related to cooling, consumption will increase during the summer months, as showed in Figure 7.

Figure 7 — Trend chart showing seasonality

When a single relevant variable cannot adequately describe the variability in energy consumption, a model- based EnPI, using two or more relevant variables (see Annex C), could be used or the EnPI boundary (see Annex B) could be divided.

Certain relevant variables may exhibit co-linearity. This could be the situation for two different production variables that are interdependent. When this situation arises, only one of the variables should be considered when developing an EnPI using regression analysis. In these instances the variables should be selected based on their relative impacts on energy consumption and their levels of uncertainty.

NOTE Where operating patterns and the values of relevant variables fluctuate significantly, it is important to ensure that the data being analyzed for correlations are at the correct frequency to enable the effects of each variable to be accurately observed.

4.2.5 Defining and quantifying static factors

Factors affecting energy performance often change in value. Factors should be analyzed to see if they are best considered as a relevant variable that routinely changes or as a static factor that does not routinely or significantly change.

Example: Production changes in quantity and quality on a daily or routine basis (relevant variable) but the product mix itself may not change on a routine basis (static factor).


It is important to record the condition of these static factors at the time when EnPIs and EnBs are being established. The organization should review these static factors over time, to ensure that the EnPIs and EnBs remain appropriate and to record any major changes that could affect energy performance.

Although static factors are not deemed to vary substantively during the reporting periods being evaluated, they could become a relevant variable in the future if conditions change.

Examples of potential static factors and changes that could turn them into relevant variables are shown in Table 2.

Table 2 — Examples of potential static factors Static factor Description Conditions which change a static factor into a

relevant variable

Product type Specific products produced by the plant A plant introduces a new product and/or product mix changes.

Shifts per day Plant currently runs a set number of shifts per day

A change to more or less shifts would significantly impact energy consumption.

Building occupancy The occupancy pattern of a building is determined by the current tenants.

A change in tenants might result in a significant change in occupancy pattern resulting in changes in energy use and consumption.

Floor area The size of the building that is the focus of the EnMS

The building is expanded which impacts energy use and consumption.

4.3 Identifying energy performance indicators

4.3.1 General

Organizations define targets for energy performance as part of the energy planning process in their EnMS. The targets may be a single improvement value at the site level or may be composed of a number of sub-targets. The sub-targets may be designed to roll up into a single value.

EnPIs should, when compared over time, allow an organization to determine if the energy performance has changed.

When selecting appropriate EnPIs, key factors to consider are the users of the information and the measurable energy performance results that can be quantified.

The main types of EnPIs are:

measured energy value(in total or broken down by energy use);

ratio derived from measured values, such as energy efficiency;

statistical model: linear and non-linear regressions;

engineering based model: simulation.

NOTE Statistical and engineering models estimate energy values. The purpose of the models is to enable energy value comparisons under equivalent conditions, even if there are changes of relevant variables. Models generally describe the relationship between energy values and relevant variables in the baseline period. Models are explained in more detail in Annex C.

4.3.2 Identifying users of energy performance indicators

EnPIs need to take into account the needs of users. EnPIs should be clear so as to inform continuous improvement efforts and enable the user to make decisions and take actions. Where complex statistical or engineering model-based EnPIs are used the EnPI values may be presented to users in simplified forms, such as with charts. Therefore, multiple EnPI types may be needed to support the energy management efforts of different end users.


EnPIs can be developed for internal or external users. Internal users typically use EnPIs to manage improvements in energy performance. External users typically use EnPIs to meet information requirements derived from legal and other requirements. These users may include regulatory bodies, professional and sector associations, EnMS auditors, other organizations and customers. Table 3 outlines some common internal users of EnPIs.

Table 3 – Internal EnPI users

Internal EnPI Users Usage/application of EnPIs

Top management Responsibilities include to ensure that EnPIs are appropriate to the organization, to consider energy performance in long term planning, to ensure that all legal and other external requirements are met and to ensure that results are measured and reported at determined intervals.

Management representative (energy manager)

Working with an energy management team, has the responsibility for delivering measurable results within the EnMS to the top management.

Plant or facility manager

Typically controls resources within the plant or facility and is accountable for results. Oversees supervisors who typically hold operational responsibility for a significant energy use and monitor energy performance over time. The plant or facility manager should understand both planned energy performance and any deviation from desired performance both in terms of energy consumption and/or energy efficiency and in financial terms.

Operation and maintenance personnel

Responsible for using EnPIs to control and ensure efficient operation by taking corrective actions for deviations in energy performance, eliminating waste and undertaking preventive maintenance to reduce energy performance degradation.

EnPIs can be established at various levels of the organization or facility, can be tiered and can be of different types depending on the needs of the users within the organization.

4.3.3 Determining the specific energy performance characteristics to be quantified

The organization should choose the type of EnPI according to user needs and the complexity of the application. The EnPI type should be chosen based on Table 4.

Table 4 — Types and applications of EnPIs

EnPI Type Useful for Examples Disadvantages

Measured energy Value

Measuring reductions in absolute use or consumption of energy

Meeting regulatory requirements based on absolute savings

Monitoring and control of energy stocks and costs

Understanding trends in energy consumption

Energy consumption (kWh) for lighting

Fuel consumption (GJ) of boilers

Electricity consumption (KWh) during peak hours

Peak demand (KW) in month

Total energy saved (GJ) from energy efficiency related programs

Does not take into account the effects of relevant variables

Does not measure energy efficiency

Ratio of measured values

Monitoring energy efficiency of systems that have only one relevant variable

Monitoring systems where there is little or no base load (i.e. where there is little or no fixed consumption)

Standardizing comparisons across multiple facilities or organizations (benchmarking)

Meeting regulatory requirements based on energy efficiency

Understanding energy consumption trends

kWh/ton of production

GJ/unit of product

kWh/m2 of floor space

GJ/man-day

liters of fuel per passenger kilometer

Conversion efficiency of a boiler (%)

Input energy/output energy (for instance, “heat rate” in power generation facilities)

kWh/MJ for cooling systems

kW/Nm3 for compressed air

Does not account for base load energy use effects; may be misleading for facilities with a large base load

Since only one relevant variable is taken into account, multiple EnPIs may be needed


systems

L/100km

kWh/value-added in unit of currency

kWh/unit of sales

Statistical Model

System with several relevant variables

System with base load energy consumption

Where comparison requires normalization

Modeling complex systems where the relationship between energy performance and the relevant variables can be quantified;

Organizational level energy performance with several relevant variables

Energy performance of a production facility with two or more product types

Energy performance of a facility having a base load

Energy performance of a hotel with variable occupancy rate and outside temperature

Relationship between the energy consumption of a pump/fan and the flow rate

For models with multiple variables relationships can be difficult to determine and models can take time to create an can be difficult to ensure accuracy

May not be clear if any residual error is due to modeling error or lack of control over energy consumption

May be inaccurate if not confirmed by statistical tests

Requires a detailed system understanding to define the correct functional form of relationship expected when data are not linear

Models must be maintained to ensure valid results

Engineering model

Evaluating energy performance from operational changes where variables are numerous.

Transient processes and/or systems involving dynamic feedback loops

For systems with interdependent relevant variables (such as temperature and pressure)

Estimating energy performance at a design stage

Industrial or power generation systems where engineering calculations or simulations enable accounting for changes in relevant variables and their interactions

Model of the electricity consumption of a chiller using the demand for cooling, the outside temperature (condensing temperature) and inside temperature(evaporating temperature)

Whole building models that account for hours of operation, centralized versus distributed HVAC systems, and varying tenant needs

Models must be maintained to ensure valid results

Generally high costs

NOTE 1 The list of examples is not exhaustive.

NOTE 2 The type of EnPIs would also apply to the corresponding EnBs.

NOTE 3 In the building environment, kWh/m2 of floor space is commonly used, but it is sub-optimal because floor space is rarely a relevant variable. A better building EnPI would be kWh/occupant-hour.

NOTE 4 In some cases, an organization may need to combine EnPIs into a single EnPI. For example, a factory with multiple activities may need to submit a single EnPI value to meet a government program requirement.

Annex C provides supplemental information about selecting EnPIs.

Annex D provides information about normalization of EnPIs and corresponding EnBs.


4.4 Establishing energy baselines and data collection

4.4.1 General

An EnB is a quantitative reference that provides a basis for comparison of energy performance for a period of time. It is the energy reference against which future energy information will be measured in order to identify any changes in energy performance. The EnB should provide an indication of what the ongoing energy performance would be if no changes were introduced.

When establishing an EnB, the organization should understand its energy consumption characteristics such as base load as well as variable loads due to production, occupancy, weather, or other variables. This understanding may lead to the opportunity for improvement. The EnB serves as the reference point against which to measure an organization‟s energy performance improvement efforts resulting from the EnMS action plans.

The establishment of the EnBs is linked to the identification of EnPIs. An EnB is simply the value of the EnPI during the baseline period. A comparison between the EnB and reporting period EnPIs can be used to illustrate progress towards objectives and targets.

The following steps should be taken to establish an EnB:

determine the specific purpose and corresponding EnPIs for which the EnB will be used;

determine a suitable data period;

data collection;

calculate and test the EnB.

The chosen EnB should be a value, ratio or model that characterizes energy performance for a selected period of time. A „measured value‟ EnB is derived by measuring the energy consumption of a system using a meter, with or without a conversion factor. A „ratio or measured values‟ EnB is a form of expression for the energy efficiency of a system. EnBs derived through regression analyses or other engineering modeling approaches define the relationship between energy and other relevant factors that influence energy performance during the baseline period.

4.4.2 Determining a suitable data period

The organization should determine a suitable data period in consideration of the nature of its operations.

The frequency with which an organization acquires data is an important factor in determining a suitable data period. The data period should be of sufficient duration to capture variations in relevant variables, such as seasonality in production, weather patterns, etc.

Typical periods to be considered are:

One Year: the most common EnB duration is one year, likely due to alignment with energy management and business objectives, such as reducing energy consumption from a previous year. One year also includes the full range of seasons and hence can capture the impact of relevant variables such as weather on energy use and consumption. It can also capture a full range of business operating cycles where production may vary during the year due to annual market demand patterns.

Less than One Year: EnB duration of less than one year can be suitable in cases where energy use and consumption are steady throughout the year and shorter operating periods capture a reasonable range of operating patterns. In these instances, monthly production rates should be stable enough throughout the year to enable monthly or quarterly tracking. Short EnB durations may also be necessary for situations in which there is an insufficient quantity of reliable or available historical data, or when changes to the organization, policies or processes make only current data appropriate. Where an EnB is based on a short period of data due to lack of data availability, adjustments may be needed.

More than One Year: seasonality and business trends can combine to make a multi-year EnB optimal. Specifically, custom multi-year EnB periods are useful for extremely short annual production cycles where a business manufactures for a few months each year and is relatively dormant for the remainder of the year.


Example: a winery might want to track energy performance only during the crushing and fermentation period of each year, over multiple years.

4.4.3 Gathering data and testing EnPIs and EnBs

4.4.3.1 General

An organization should specify the elements of each EnPI and its corresponding EnB to be quantified. The type of energy consumed should be specified, (e.g. electricity, high pressure steam) together with relevant variables, such as production volume (or units produced), flow rate, pressure, temperature and weather conditions. Once the potential relevant variables have been identified, the first step is to gather data that will be used to develop EnPIs and the corresponding EnB.

4.4.3.2 Data collection

Energy and relevant variables data are typically collected using meters and sub-meters either on a permanently installed, temporary or spot measurement basis. Challenges to energy data collection include:

a lack of detailed metered data from energy suppliers,

a lack of data on relevant variables,

data in a form that is incompatible with the energy data, for example where energy data comes from monthly supplier invoices but production data is captured weekly.

Where estimated values are used in calculating EnPIs, the assumptions and methods used should be documented.

An organization may discover that some of the EnPIs that were earlier identified as significant may not be measurable due to data limitations or other barriers. In this case the organization will need to assess, and consequently refine the EnPIs or introduce additional meters or monitoring.

4.4.3.3 Measurement

The organization should take measurements for each energy value and relevant variable necessary to calculate the selected EnPIs and the corresponding EnB.

NOTE In many cases, the quantity of energy consumed has to be measured indirectly. This may require measuring a flow, volume or mass of fuel supplied and may vary with factors such as composition, outdoor temperature, pressure and other factors. Multipliers or factors are commonly applied to the actual measured flow of gas or liquid fuel to calculate the quantity of energy contained in the fuel.

Measurements should be taken either on a spot basis (e.g. using mobile/portable meters), on a temporary basis (e.g. using data loggers), or continuously (e.g. using data from a supervisory control and data acquisition - SCADA system or a data acquisition and handling system – DAHS). Energy values and relevant variables used to calculate each EnPI should be measured at the same time and frequency. If continuous measurement is not possible, the organization should ensure that spot or temporary measurements are made during periods that are representative of the typical pattern of operation.

The organization should analyze what relevant variables need to be measured. For example, where energy use per unit of production is being measured, counting the number of final products may provide a misleading result if there are intermediate outputs produced, and whether these intermediate outputs are waste, value added, or recycled.

4.4.3.4 Data collection frequency

The organization should select an adequate acquisition frequency for each energy value and relevant variable included in the EnPI and the corresponding EnB. The data collection frequency should be sufficient to capture operating conditions and provide an adequate number of data points for analysis.

The data acquisition frequency may be much higher than the frequency of reporting in order to measure and try to understand the impact of relevant variables on energy performance. For example, hourly, daily or weekly


data collection may be needed at the operational level to address significant deviations. Such energy values and relevant variables may then be aggregated for monthly reviews at the organizational level.

Organizations should also collect data more frequently when they desire higher statistical accuracy. The higher the data acquisition frequency, the more flexibility there will be to analyze data in different ways.

If new measurement systems are to be installed, the organization should consider the frequency of data needed to meet its energy monitoring needs.

4.4.3.5 Data quality

Prior to calculating EnPIs and corresponding EnBs, it is recommended that the set of measured energy values and relevant variables is reviewed to determine the quality of the data. Significant outliers, which are typically a result of faulty metering or data capture or atypical operating conditions need to be examined. Practical help box 3 describes one way to identify and analyze outliers.

If some outlying measurements are excluded, care should be taken that this does not introduce bias into the EnPI model or corresponding EnB.

Inaccuracies in the measuring devices used can undermine the validity of the data collected. The organization should consider calibrating the equipment periodically according to the manufacturer‟s recommendation to reduce the risk of inaccurate data.

Measurement accuracy and the level of uncertainty should be taken into account when interpreting and reporting on EnPIs.

Practical help box 3: Identifying and analyzing outliers

Typically, outliers will be identified from looking at a scatter diagram. This may be by reference to a trend line or function of the relevant variables, with the mean, standard deviation and standard error (standard deviation of the mean) of the data calculated. Data points in excess of a pre-determined number of standard deviations from expected value of the trend line or function may be considered to be outliers.

Outliers may exist as a result of faulty measurement, data handling errors or simply extreme values resulting from atypical operations. For example, an annual plant shutdown will result in a significant variation in energy consumption that will appear as an outlier in any analysis. Before excluding an outlier, investigations should be carried out to determine if there is a legitimate reason for the outlier, and if excluding, reasons for this should be documented.

4.4.3.6 Calculating and testing energy baselines

To develop the EnB, the corresponding EnPI should be calculated using the energy consumption and relevant variable data from the baseline period. If appropriate, the EnB should be tested for validity to ensure that it is an appropriate reference for comparison. There are many statistical tests that can be used, such as the F-Test and deriving R-Squared. The testing results should be recorded.

4.5 Using energy performance indicators and energy baselines

4.5.1 General

To assess changes in energy performance, organizations should quantify EnPIs measured during the reporting period and compare these values to the corresponding EnBs. The organization also should compare the quantified energy performance to its targets and take action.

4.5.2 Calculating changes in energy performance

There are many approaches and techniques for organizations to monitor and measure energy performance. However, three common approaches for measuring energy performance improvement are shown below. Defining baseline EnPI value as “B” and the reporting EnPI value as “R”, these approaches are:


a) Energy difference: this is the difference between the baseline period EnPI value and the reporting period EnPI values.

Example Difference = R – B

b) Percent change: This is the change in values from the baseline period to the reporting period, expressed as a percentage of the EnB value.

Example Percent Change = [(R – B) / B] x 100

c) Current ratio: This is a ratio of the reporting period value divided by the baseline period value.

Example Current Ratio = (R/B)

These three common approaches can be used for all types of EnPIs and EnBs.

4.5.3 Determining when energy baselines should be normalized

Direct comparison of an EnPIs' value to its corresponding EnB allows for a simple measurement of energy performance improvement progress or change. This direct or un-normalized method reflects the results from all activities that occurred during the reporting period and includes the contributions from all relevant variables present.

At times however, the organization may have a need to determine the performance change resulting from specific selected activities and conditions as distinct from the effect of certain variables. A typical example is looking at building energy usage between two periods where the outdoor temperature in the two periods was different. In cases where an organization wishes to compare its energy consumption between two periods, taking into account the effect of the relevant variables, it may choose to normalize the EnB. The organization would use the relevant variables in question to normalize the EnB, which would enable comparisons of energy consumption over the two periods.

Cases where organizations may wish to normalize their EnBs using variables in order to obtain useful information related to energy performance may include situations where variables impact energy consumption such as:

outdoor temperature;

building occupancy percent or usage type;

hours of operation;

production variations;

raw material variations;

product type variations;

process changes;

volumes and quantity changes;

geographical location;

environmental condition;

equipment to use in installation;

legal factors.

Direct measures of EnPIs give their value at, or over, a specific period of time. For example:


energy consumption for a site in 2010 was 1,200,000 kwh;

energy consumed for lighting during a month was 24 mwh.

A potential issue with EnPIs is that unless the user has some prior knowledge of the EnPI, and of the goals of the organization, a direct value can have limited utility. Direct measures can be trended over time, and it is the trend value of the EnPI that is informative rather than the number at a specific point in time.

Comparative measures go some way to addressing the limitations of direct measures. Comparative measures look at performance over a period of time.

Practical help box 4: Evaluating comparative measures

Example: Energy Consumption at the site level electricity consumption fell by 200,000 kWh / year between 2008 and 2012.

Without additional information about changes that occurred between 2008 and 2012, it would be difficult to determine whether progress has been made towards meeting the organization‟s goals and targets.

For example, if market demand required a change in the mix of products produced during 2011 and 2012, the drop in consumption cited above might or might not, in fact, be related to improvements in energy performance. If the organization established improvement targets based on efficiency or intensity or total consumption, excluding effects attributed to changes in product mix, and not on gross reductions from all causes or actions, then the direct comparison results showing improvement might be misleading.

Annex D provides information about normalizing EnBs using variables.

4.5.4 Communicating changes in energy performance

EnPIs should be shown to fit its purpose and users. It should be shown with an EnB and a target value. These should be visualized or reported. Examples of visualization include the following:

printed trend charts and pie charts on notice boards;

trend chart of EnPIs displayed on large-screen;

inter-section competition of common EnPI;

led signs;

company intranet;

text messages to mobile phones;

specific analytical report.

For information on ways to monitor and report energy performance, see Annex E.

4.6 Maintaining and adjusting energy performance indicators and energy baselines

When organizations make changes to their facilities, systems or processes, energy use, consumption and relevant variables are generally impacted. The organization should ensure the current EnPIs and the corresponding boundaries and EnBs are still appropriate and effective in measuring energy performance. If they are no longer appropriate, the organization should change or develop new EnPIs or adjust the EnB. Examples of such changes are presented in Table 5.


Table 5 – Types of EnPI and EnB changes Type of Change Changes required

Energy use change When an organization makes a fundamental change to the forms of energy it is using, it may need to modify what is tracked (EnPIs) and how those factors are weighted in its EnB.

Operational changes When an organization makes significant operational changes it is possible that EnPIs and EnBs may be impacted. For example, if an organization introduces a new process the organization may consider creating a new EnB following that change.

Data availability

Improvements to the facility‟s metering and data collection system may result in better quality data becoming available or new relevant variables coming to light. Changes to EnPIs and EnBs may then be desirable.

Target changes

Organizations may wish to update the EnB period in order to lock in accomplishments to date and focus on improving against the current energy performance instead of a past period. A strategic decision of such a nature would necessitate the updating of the EnB to a recent period (such as the last year) to serve as the new reference point.

Static factor changes If static factors that were identified during the EnB establishment activity change and become relevant variables that impact energy consumption, then to the extent data are available for the static factors, the EnB can be adjusted. If such data do not exist, then the EnB may need to be updated to reflect a period which includes the relevant variables. An example would be moving from a 3 shift per day to a 1 shift per day operation or changing from a 7-day week to a 5-day week. When the hours of operation of a facility change, this may require an adjustment to the EnB.

According to a predetermined method

The organization may find it useful to identify conditions in advance that would require a change to the EnPIs or an adjustment to EnBs. The organization can also predetermine the rules and methods that will be used in making adjustments. An example might be for EnPIs and EnBs that are established to comply with legal or other requirements (e.g. to external organizations). Rules and methods should be established on when and how EnPIs and EnBs will be set and adjusted to meet those requirements.

Management Review One of the inputs to Management Review is the review of EnPIs. Therefore, a corollary output is potential changes to EnPIs.

A significant change in EnPI values may signal an underlying change in energy performance, or relevant variables that merits an adjustment to the EnB.

When using model-based EnPI, an organization should test the current EnPI and EnB to see if they still represent a valid comparison for calculating energy performance. The values of the relevant variables in the reporting period should be compared to the baseline period to determine if they are statistically valid. There are several different ways of comparing these values (see 4.4.3).

Example: In the first instance, an organization may look at the statistical mean of the values of the relevant variables in the reporting period to see if they are within a predetermined number of standard deviations of the baseline period. If not, then the organization may decide to develop a new EnB. Other organizations may look at confidence intervals and possibly perform additional statistical tests.

It is important to note that the methodology for determining and updating the EnPIs needs to be recorded and reviewed regularly.


Annex A (informative)

Information generated through the energy review to identify EnPIs and

establish EnBs

ISO 50001 requires an energy review to be undertaken. Table A.1 presents further details on activities resulting from the energy review.

Table A.1 – Examples of energy review activities Energy review Typical activities resulting from the energy review

a) analyze energy use and consumption based on measurement and other data

a1) identify current energy sources Create a list: energy source and energy value (consumption, peak power, etc.)

a2) evaluate past and present energy use and consumption

Create energy value trend charts by use (purpose)

Create energy value trend charts by source of energy

b) based on the analysis of energy use and consumption, identify the areas of SEU

b1) identify the facilities, equipment, systems, processes and personnel working for, or on behalf of, the organization that significantly affect energy use and consumption

Create a list: facilities, equipment, systems, processes

Add personnel information to this list

Add energy values to this list

Add SEU candidate information to this list

b2) identify other relevant variables affecting SEUs

Identify relevant valuables affecting energy value (see 4.2.4, define and quantify relevant variables)

b3) determine the current energy performance of facilities, equipment, systems and processes related to identified SEUs

Create a list: management purpose in each management level and prioritize (see 4.3.2)

Set EnMS boundary and EnPI boundary (see 4.2.2)

Identify EnPIs in each EnPI boundaries (see 4.3)

Establish EnBs corresponding EnPIs (see 4.4)

b4) estimate future energy use and consumption

Estimate energy value using the trend chart (A2)

Estimate energy value using EnB model in case of using model-based EnPI (see Annex C)

c) identify, prioritize and record opportunities for improvement in energy performance

Examine EPIA and create a list

Add target EnPI value (or measure) to this list

Estimate investment roughly

Prioritize a list by investing affect and identify opportunities

Make an implementation plan and record


Annex B (informative)

EnPI boundaries in the production process

In the process of energy performance improvement, it is important to find the most inefficient portion in the production system. An EnPI boundary can be used effectively to focus on this portion by narrowing the boundary. As a first step the EnPI boundary is the entire factory. For the entire factory, the points may appear as a random cloud, as in X-Y diagram shown in section 4.2.4. In such case, the target boundary should be divided into several EnPI boundaries. As a next step, the EnPI boundary should be narrowed on the SEU of the production system to find a more detailed point for the energy efficiency improvement. Figure B.1 shows the EnPI boundary division process.

Figure B.1 – EnPI boundaries division process

EnPI boundaries division could be performed as follows:

a) The number of divisions should be minimized.

It is first recommended that the boundary be divided into two parts such as SEU and other.

b) Facilities that work in the same way should be categorized together.

The facility should be divided into some parts (e.g. facilities for product X, facilities for product Y, utility facilities)

c) The EnBs should be established for each operational status of the EnPI boundary.

The operational status refers to production ramp-up, normal operation, production hold, production stop, etc. At a minimum, it is recommended that organizations establish at least two EnB operational status conditions: under production conditions, and under stop conditions.

With the above procedures, the energy characteristics of the organization can be modeled easily. This method divides a boundary into sub-boundaries and models them according to their status. This method is easier than analyzing miscellaneous data and creating a non-linear regression model.


Annex C (informative)

Further guidance on energy performance indicators and energy

baselines

C.1 Examples of static factors and relevant variables

Additional examples of static factors and relevant variables include production rate, product mix, raw material type or quality, number of shutdowns and start-ups, different modes of operation, the reliability of systems, environmental conditions such as humidity or temperature, occupancy levels, and the proportion of rooms or floors that are climate conditioned.

C.2 Types of energy performance indicators

C.2.1 Measured energy value

If an organization establishes objectives, targets and action plans for achieving absolute energy savings, then it would choose EnPIs that monitor absolute energy consumption. The EnB would simply need to contain the energy consumption data for a chosen data period that was representative of the organization‟s energy consumption patterns.

Many organizations may choose to target improvement in absolute energy consumption and therefore select appropriate EnPIs and establish a corresponding EnB suitable for comparing energy consumption changes.

Examples:

energy consumption per year;

energy consumption by kind of energy.

Some examples of cases where absolute measured value EnPIs may be relevant and adequate are:

a national passenger railroad, where the number of trains operated annually will not vary by much; or, if a new high speed service is initiated, this effect can be treated by adjusting the EnB;

an owner-occupied office or retail building;

a refrigerated warehouse owned by a supermarket chain;

a municipal waste water treatment plant in a location with relatively stable rainfall patterns.

When energy consumption is affected by relevant variables, model-based EnPI should be used for calculating energy savings (see C.2.3).

C.2.2 Ratio

Many organizations choose to look at energy relative to its relationship to a specific variable such as production or square meters of building space etc. Organizations operating many facilities of a similar nature use such indicators in order to monitor energy performance improvement over time, compare facility energy performance across multiple facilities and/or benchmark against competitors or industry standards. Such indicators are referred to as energy efficiency or energy ratios. In such cases, energy is divided by a production unit or other relevant measure (e.g. for a commercial building square meters of floor area may be appropriate).

EXAMPLE Quantity of energy used per unit product.


C.2.3 Model-based EnPI

The final class of indicators refers to circumstances where energy performance depends on multiple variables. Models can be derived through linear regression, non-linear regression (e.g. the non-linear relationships that link energy to throughput in fans), or can be constructed using engineering based theory. Engineering based theory is likely to be used where the relationship between energy and other variables involves complex relationships that cannot be accurately captured with regression.

Model-base EnPIs are useful also for examination and evaluation of an energy performance improvement action.

Examples:

influence of external temperature on energy consumption;

impact of regular maintenance on efficiency of production processes;

impact of changes in consumption of one energy source on the consumption of other energy types.

Table C.1 provides further descriptions about common EnPI types.

Table C.1 — Examples of EnPI types and applications

Item Example 1

Measured energy value

Example 2

Ratio of measured value

Example 3

Statistical model

Company type Pulp and paper company Steel company Hotel company

Process Steam generation by

(1) biomass boiler (2) oil boiler

Electric arc furnace Heating by oil boiler

Intention Eliminate oil use to cut cost Achieve world class SEC and remain in business

Cost down

Improvement action

Increase energy efficiency of biomass boiler

Many improvement actions Operator training of boiler

EnPI and corresponding EnB

Oil consumption (kL/month) SEC (kWh/ton) Energy efficiency (L/degree-day)

Target EnPI = 0 (kL/month) Reduce SEC 2% per year and achieve world class by 4 years.

Improve energy efficiency 5%

Note The company does not care about outdoor temperature and production change

This hotel set energy cost to EnPI at first. However, energy performance improvement action‟s effect could not be confirmed. Because unit price of oil was up and average temperature in baseline period was high. Thus this company decided to use energy efficiency as EnPI.


C.3 How to define an energy baseline

An EnB represents reference EnPI values at a given point or period of time against which future energy performance will be assessed. An EnB estimates energy value in the condition of the baseline period by using relevant variables.

An EnB can be expressed as:

a relational expression (e.g. a formula relating the energy efficiency of a system to daily temperature and daily production); or

a set of raw energy data in a spreadsheet.

An EnB should be devised using measured values for EnPIs and other relevant variables. In many cases, output values from facilities will not change over a short time period. To obtain the EnB with the desired accuracy, the baseline period should have a suitable quantity of measurements to capture normal variations in production volume and seasonal factors.

In many cases, the most complete EnB will be determined using model-based analysis. Nevertheless, regression analysis is only appropriate in cases where adequate data are available. In cases where data are insufficient or unavailable, an EnB based on alternative EnPI types, such as absolute energy consumption or energy efficiency, could be used (see Table 4). If there are multiple relevant variables, dividing the EnPI boundary using the method described in Annex B should be useful.

C.4 Using model-based EnPI to define an energy baseline

If adequate data describing energy use and all of the variables thought to influence energy use are available, regression analysis may be an appropriate approach for determining an EnB. The nature of the data available as well as the relationships between the data determines the type of regression analysis that should be performed. Statistical software packages are available that allow researchers to construct regression models using large quantities of data.

To determine if regression analysis is appropriate for establishing an EnB, the person responsible for developing the EnB should have knowledge of statistical methods or should consult colleagues or external resources with this knowledge. Without knowledge of statistics, regression models may be incorrectly defined and/or misinterpreted, which could lead to inappropriate decisions and actions being taken in response to erroneous findings.

C.5 Case study

An organization produces two lines of products: A and B.

After completing a thorough energy review of its manufacturing facility, the organization‟s Energy Management Team draws the following conclusions:

the facility uses electricity, purchased from an external supplier, as the only source of energy;

the production rate (run-rate) of each production line can be varied from zero to 100%;

the output of each production line is measured independently in kilograms;

SEC (energy consumption per kilograms) of line B is 10 times higher than that of line A and production volume of each line is almost same;

raw material quality varies; and

there is a project scheduled to upgrade all of the motors on production line A.

The different functions within the organization include a business/marketing manager, the facilities operations manager, the accounting department, the production line A engineer and the production line B engineer, as well as the operating technicians for each line. The Energy Management Team holds discussions with each of these functions, and based on these discussions, the team determines that, because of the multi-level nature


of the organization, with each level having specific responsibility for energy performance at its own level and sphere of control, a tiered set of EnPIs should be established in order to provide the organization with the information it needs to effectively manage and improve energy performance. Each functional group will require different levels of information to meet management requirements and to respond to specific energy management questions. Since two production lines have quite different SEC, they decide energy consumption per value of production (energy intensity) as the facility level EnPI.

The team then collects time-series data at the facility level and production line level for energy consumption, energy costs, raw material quality and quantity, production for each line, and weather conditions. The team uses the collected data to model the facility and two production lines. Through analysis of the data and model, the team determines that there is a correlation between changes in some of the variables and energy consumption. The team identifies the following as the relevant variables: production quantity, production rate, product mix and air humidity.

Raw material quality does not cause a significant change in energy consumption. The team establishes the following EnPIs in a hierarchy, with higher level EnPIs (e.g. 1.1) geared toward higher level information requirements, with more specific EnPIs (e.g. 2.1.1.1) aimed at line engineers and technicians, showed at Table C.2

Table C.2 — EnPI examples

EnPI EnPI levels

1 Facility business level EnPIs

1.1 Facility level energy consumption (kWh/day)

1.1.1 Facility level energy consumption per value of production (kWh/US$) – normalized by values of production

2 Product line A EnPIs 2.1 Line A energy consumption (kWh/day)

2.1.1 Line A energy consumption per kg of product output (kWh/kg)

2.1.1.1 Line A energy consumption per kg of product output (kWh/kg) – normalized for air humidity

2.1.1.2 Line A energy consumption per kg of product output (kWh/kg) – normalized for run-rate

2.1.1.2.1 Line A energy consumption per kg of product output (kWh/kg) – normalized for air humidity and run-rate

3 Product line B EnPIs 2.1 Line B energy consumption (kWh/day)

2.1.1 Line B energy consumption per kg of product output (kWh/kg)

2.1.1.1 Line B energy consumption per kg of product output (kWh/kg) – normalized for air humidity

2.1.1.2 Line B energy consumption per kg of product output (kWh/kg) – normalized for run-rate

2.1.1.2.1 Line B energy consumption per kg of product output (kWh/kg) – normalized for air humidity and run-rate

The Energy Management Team refers to Table C.3 to guide the use and purpose of the EnPIs.

Table C.3 — Use and purpose of EnPIs

EnPI levels Purpose/Need EnPI Type EnPI users

1.1 Facility level energy consumption (kWh/day)

- Total production cost control

- Budgeting

Measured energy value - Top Management

- The accounting department

- Business Leaders

- Budget Managers

1.1.1 Facility level energy consumption per volume of production (kWh/US$)

- Total energy efficiency control

- Evaluate the effect the improvement action


- Facility decision makers

- Marketing manager

- Sales department


- Manufacturing manager

- Business manager

- Facilities owner

2.1 Line A energy consumption (kWh/day)

-Total production cost control of line A

-Budgeting

Measured energy value EnPI

- Plant A Engineer

- Budgeting manager

- Accounting department

2.1.1 Line A energy consumption per kg of product output (kWh/kg)

-Energy efficiency control of line A

-Evaluate energy performance improvement action effect


- Marketing Manager

- Sales department

- Business Manager

- Plant A Engineer

- Budgeting manager

- Accounting department

2.1.1.1 Line A energy consumption per kg of product output (kWh/kg) – normalized for air humidity

- Evaluate air humidity effect Ratio of measured values

- Plant A Engineer

- Plant A Operating Technicians

2.1.1.2 Line A energy consumption per kg of product output (kWh/kg) – normalized for run-rate

- Evaluate run-rate effect Ratio of measured values

Same as 2.1.1.1

2.1.1.2.1 Line A energy consumption per kg of product output (kWh/kg) – normalized for air humidity and run-rate

- Evaluate run-rate and air humidity effect


Same as 2.1.1.1

Repeated for Line B

ISO/DIS 50006


Annex D (informative)

Normalizing energy baselines using relevant variables

In some cases, organizations may choose to normalize their energy baselines using variables. Such cases typically involve situations where the values of the relevant variables in the baseline period and the performance or reporting periods are substantially different. Typical examples of relevant variables that might affect energy consumption include outdoor weather, building occupancy, facility operating hours, product mix variations, production volumes etc. The point of normalization is to make the values of the relevant variables comparable to each other in the baseline period and the reporting period in order to neutralize the effect of the differences in the values of the relevant variables in the two periods.

Normalization is a term that is used broadly for many activities and which can have substantially different meanings in different fields and applications. In this context, normalization of an energy baseline is being used to describe the process of estimating the energy consumption of the baseline using the values of the variables in the EnPIs during the reporting periods. This is in order to calculate an adjusted EnB energy consumption value (expected energy consumption) against which the EnPI energy consumption value can be compared on a basis that renders the values for the variables in the two periods equal. The concept is illustrated in Figure D.1.

The dashed line in the figure below shows absolute energy consumption and data on relevant variables during the performance period. The organization may also choose to evaluate the performance only during a specified reporting period within the reporting period in accordance with its requirements. The dotted line is the normalized energy consumption. The normalized energy consumption is a calculated energy consumption value (or series of values) that inputs the values for relevant variables from the reporting period into the EnB equation.

Figure D.1 – Normalization

This results in a calculated energy consumption value (or estimate of the energy) “that would have been consumed in the performance period, had the mathematical relationship between energy and the relevant variables been equal to that of the baseline period.


The EnB performance equation quantifies the mathematical relationship between energy and the relevant variables for the EnB dataset. An example EnB equation may take the form:

Energy (kWh/week) = A (kWh/week) + B * Product A (units per week) + C * AvT (average temperature per week)

Where:

A = A fixed component of energy consumption (sometimes called the base-load);

B = the SEC unit of product A (kWh/unit);

Product A = a relevant variable (RV1);

C = the SEC per degree of average temperature per week (kWh week/degC);

AvT = a relevant variable (RV2).

The factors A, B and C will be derived from linear or non-linear regression or from some engineering theory-based system understanding.

The normalized EnB energy consumption (NEnBEC) would be calculated as follows:

NEnBEC = A + B* Product A (PP) + C* AvT (PP)

Where:

A, B and C values are as per the EnB performance equation derived from the EnB dataset;

Product A (PP) = the measured value for RV1 from the reporting period;

AvT (PP) = the measured value for RV2 from the reporting period.

The concept of the above calculation process is illustrated in the Figure D.2.

where E: energy consumption P: production suffix base: baseline period suffix rep: reporting period suffix est: estimated suffix act: actual (measured )

Figure D.2 – Normalization calculation process


Annex E (informative)

Monitoring and reporting energy performance

E.1 General

The Figure E.1 shows an overview of the energy performance monitoring and reporting methods. The measured results are displayed according to the user‟s needs. A roll up of the results for the whole organization is suitable for top management. For the operator, the result of any specific action is needed. To the engineer, the detailed result is required to find opportunities for energy improvement actions.

The current energy value and their relevant variables are represented by the EnPIs directly. Moreover, information on the baseline period is recorded to a data set and provided for comparison. The estimated values of the EnB are also provided if model-based EnPIs are used.

Figure E.1 Overview of monitoring and reporting energy performance

E.2 Types of monitoring methods and reports

Organizations can use a variety of reports various kinds of monitoring and reporting methods for energy performance, including:

comparing current performance against target performance Comparison chart of target and current EnPI;

trend chart of EnPIs (and relevant valuables);

X-Y chart (e.g. energy consumption and production);

assessing variance (Variance);

cumulative summation chart (Cusum);


visualization using various analytical tools (e.g. Cumulative summation chart (Cusum));

Monitoring can also be carried out using an alarm chart for detecting abnormalities in real time EnPI values.

multidimensional graphics with internal benchmarking

In each case, the information can be represented graphically or in tables.

E.3 Target and current EnPI comparison

Examples of EnPIs for the three elements of energy performance are shown below.

energy consumption (see figure 4 in 4.1.7): Energy consumption of the baseline period and reporting period are compared;

energy efficiency (see figure E.2a): Specific energy consumption (SEC) of the baseline period and reporting period are compared;

energy use (see figure E.2b): The percentage of a specific energy source in the baseline period and reporting period are compared.

Figure E.2 a Figure E.2 b

Figure E.2 Example of EnPIs comparison for energy efficiency and energy use

An example of display of the EnB, current EnPI, and target EnPI are shown in Figure E.3. The difference between the target EnPI and the current EnPI is also displayed. A facility manager or an operator can assess the impacts of his/her work on energy performance and take actions if necessary.

Figure E.3 EnPI and Target


E.4 Trend chart

Energy Performance Indicators (EnPIs) should be measured for individual facilities and equipment that represents significant energy use. These individually-measured EnPIs should be monitored continuously and may vary over time. EnPIs (e.g. energy consumption, SER) and relevant variables can be displayed together as a real time trend chart. EnPI will continuously vary due to various causes.

By investigating the causes of the variation, unnecessary energy use can be identified. As shown in Figure E.4, visualization of monitoring and measurement results facilitates identification of variations of the EnPIs, or failures of equipment.

Figure E.4 — SEC trend chart

E.5 X-Y chart

The relation of the energy consumption and the quantity of production every day or every week can be shown in an X-Y chart, (Figure E.5) and any energy performance improvement effect can be checked visually. In 2011, a certain production facility was always working to 100% of capacity. In 2012, this production facility was retrofitted to consume energy according to the quantity of production. Therefore, the base load energy consumption was greatly reduced.

Figure E.5 X-Y chart

E.6 Reporting units

The above graphs present the energy units or percentages as reporting units. The potential problem with this approach is that, in general, people have little appreciation of the scale or value of a typical energy unit – i.e. just how much is 10 GJ worth? To overcome this barrier and to provide a sense of scale to the graphs, it is possible to convert the energy units into monetary values.


Again there are two possible approaches: to use a budgetary value for energy which does not change or to use actual utility purchase costs. The first approach is clearly far simpler to implement, though less accurate. In the second approach, tariff information for the utility and information on the generation and distribution efficiency is required where secondary utilities such as steam are being used.

ISO 50006

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Transcript of ISO 50006