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The diagnosis method of energy efficiency in industry automation
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GB/T 41571-2022: PDF in English (GBT 41571-2022) GB/T 41571-2022
NATIONAL STANDARD OF THE
PEOPLE’S REPUBLIC OF CHINA
ICS 25.040
CCS N 10
The diagnosis method of energy efficiency in industry
automation
ISSUED ON: JULY 11, 2022
IMPLEMENTED ON: FEBRUARY 01, 2023
Issued by: State Administration for Market Regulation;
Standardization Administration of the People's Republic of China.
Table of Contents
Foreword ... 3
1 Scope ... 4
2 Normative references ... 4
3 Terms and definitions ... 4
4 Abbreviations ... 5
5 Overview of energy efficiency diagnosis ... 5
6 Energy efficiency diagnosis process ... 8
7 Assessment of energy efficiency improvement potential ... 10
8 Determination of energy efficiency improvement target ... 13
9 Energy efficiency improvement plan ... 14
Bibliography ... 16
The diagnosis method of energy efficiency in industry
automation
1 Scope
This document specifies the general method for energy efficiency diagnosis for industry
automation.
This document is applicable to energy efficiency analysis and energy efficiency
diagnosis of industry automation.
2 Normative references
There are no normative references in this document.
3 Terms and definitions
For the purposes of this document, the following terms and definitions apply.
3.1 energy
Electricity, fuel, steam, heat, compressed air and other similar media.
NOTE: Energy includes various forms including renewable energy. It can be purchased, stored,
disposed of, used in equipment or processes and recycled.
[Source: GB/T 23331-2020, 3.5.1]
3.2 energy consumption
The amount of energy used.
[Source: GB/T 23331-2020, 3.5.2, modified]
3.3 energy efficiency
The ratio or other quantitative relationship of output performance, service, product,
commodity or energy to input energy.
Example 1: Conversion efficiency: Energy demand/energy actual use.
Example 2: Output/input: Energy amount of theoretical operation/energy amount of
actual operation.
[Source: GB/T 23331-2020, 3.5.3, modified]
3.4 energy efficiency benchmark line
Provide quantitative reference basis for energy efficiency comparison.
3.5 efficiency indicator
Indicative value of energy efficiency.
3.6 energy management
A coordinated activity that directs and controls the energy use of an entity.
3.7 specific energy consumption
Energy consumption per physical unit output.
4 Abbreviations
The following abbreviations apply to this document.
DCS: Distributed Control System
MES: Manufacturing Execution System
PLC: Programmer Logic Controller
SCADA: Supervisory Control And Data Acquisition
5 Overview of energy efficiency diagnosis
5.1 Energy efficiency diagnosis model
Energy efficiency diagnosis is a key link in implementing energy efficiency
improvement. For manufacturing enterprises to carry out energy efficiency diagnosis,
it is necessary to consider the production organization status, status quo of enterprise
and industry status quo, and to have sufficient energy efficiency data as the support to
complete the energy efficiency diagnosis. The production organization status includes
production process, production execution, personnel management, material
management. The status quo of the enterprise refers to the enterprise's operation,
manufacturing level, and funds that can be invested in energy efficiency improvement.
The industry status quo refers to the manufacturing level and energy efficiency level of
the industry divided by product or process. The production status quo can be formed by
the aspects of production status, management status, and informatization status.
First, review the production status, mainly including production process flow,
production takt and production efficiency of each process/equipment, material flow and
energy flow around the production process, production equipment around the process
flow, energy production or supply equipment. Second, review the management status,
mainly including total energy consumption and expenses, energy consumption of
various media, production energy consumption, production auxiliary energy
consumption, personnel usage in production and production auxiliary links, effective
use of materials, equipment maintenance. Last, review the informatization status,
mainly including enterprise-level management, workshop-level operation management,
energy management, on-site monitoring and other information system deployment,
equipment digitization capabilities, on-site data collection, integration between
information systems, integration between information system and equipment.
In the process of reviewing the status quo of the enterprise according to the above
content, quantitative data or indicators shall be obtained as the goal. If part of the
content of the status quo of the enterprise may not be available due to the insufficient
degree of refinement of enterprise management and incomplete relevant data,
communicate with enterprise management, workshop management, production
operators. Through the comparison and analysis of the status quo of related industries,
qualitatively describe and judge some of the contents of the status quo of the enterprise.
5.2.2 Energy efficiency data collection
Energy efficiency data is the basis and premise of developing enterprise energy
efficiency diagnosis. The requirement for energy efficiency data is to cover all aspects
related to energy efficiency, not only energy consumption data, but also equipment,
production process and other data related to energy efficiency. In addition to the internal
data of the factory, energy efficiency data shall also include related data of similar
industries and enterprises. These data can help enterprises determine energy efficiency
benchmark lines and position their energy efficiency in the industry. From the
perspective of timeliness, energy efficiency data shall include historical data and real-
time field data. It is required to ensure data accuracy and meet certain clock
synchronization requirements, so as to establish time correlation between data. Energy
efficiency data shall be processed, analyzed and managed uniformly. An energy
efficiency data model shall be established, so as to facilitate the management and
integration of energy efficiency data.
There are two main ways to collect energy efficiency data. One is to collect through the
existing system. For example, obtain energy efficiency-related equipment, units,
production lines and other data through equipment communication interfaces, PLC,
DCS, SCADA. Obtain relevant data of production operation management through MES
system. The other is that, for data that cannot be obtained, data collection needs to be
realized by modifying the equipment or deploying new devices or equipment. For
example, deploy energy measurement devices on the device. Deploy flow measuring
instruments, pressure measuring instruments on pipelines. For the inability to deploy
an installation, equipment or system due to reasons such as reduced economic input or
physical environmental conditions which may cause multiple devices or units to share
energy efficiency data, it may conduct statistical analysis of the data. Combined with
the working conditions of equipment and units, carry out the quantitative analysis of
different equipment or units.
The types of energy efficiency data collected shall include but are not limited to: At the
equipment and manufacturing unit level: various energy consumption, various material
consumption, average operating time, auxiliary processing time, number of unplanned
equipment downtime, equipment working status, rework rate, defective product rate. At
the auxiliary unit level: various energy supply, energy conversion efficiency, lighting
energy consumption, air conditioning energy consumption. At the industry level:
advanced value of energy efficiency of similar processes, advanced value of energy
consumption per unit product, and per capita labor productivity of enterprises.
6 Energy efficiency diagnosis process
The general process of industrial automation energy efficiency diagnosis is shown in
Figure 2.
The general process of energy efficiency diagnosis is mainly divided into 4 stages:
preparation for energy efficiency diagnosis, assessment of energy efficiency
improvement potential, determination of energy efficiency improvement target, energy
efficiency improvement plan.
The preparation for energy efficiency diagnosis is the basic work that needs to be
completed before carrying out energy efficiency diagnosis. First, complete energy
efficiency data collection. Energy efficiency data types include energy consumption
data of various manufacturing equipment, auxiliary equipment in the production
process, as well as data in the production process related to energy efficiency. The main
ways to obtain energy efficiency data are: through equipment communication interface,
adding sensors and instrumentation, workshop manufacturing operation management
system or similar information system. Secondly, it is necessary to analyze the
influencing factors of energy efficiency. It is divided into 3 levels to sort out the
influencing factors of energy efficiency. At the equipment level, analyze the impact on
energy efficiency from factors such as equipment working mode, equipment utilization,
and key process parameters. At the production process level, analyze the impact on
energy efficiency from factors such as technological process and workshop production
operation management. At the energy supply level, analyze the impact on energy
efficiency from factors such as energy consumption, energy supply and demand balance.
The assessment of energy efficiency improvement potential is to calculate and evaluate
the energy efficiency improvement potential as a whole. It is the basis for subsequent
determination of energy efficiency improvement goals and energy efficiency
single product structure, the ideal unit energy consumption or reference unit energy
consumption recognized by the industry can be used as the benchmark line value.
For enterprises with multiple product varieties but stable output results but no
obvious difference in the production energy efficiency of different products, the
ideal unit energy consumption or reference unit energy consumption of all products
recognized by the industry can be used as the benchmark line value. For enterprises
with multiple product varieties, but the output is unstable or different product
varieties have a greater impact on energy efficiency, product variety and product
quantity can be used as influencing factors. The energy efficiency reference value
is obtained by data fitting. The total energy consumption benchmark line of the
enterprise can also be calculated based on the number of enterprise products.
Example 1: Iron and steel production enterprises usually use standard coal per ton
of steel as an indicator to compare the overall energy efficiency level. Auto parts
processing enterprises usually use the energy consumption per unit number as the
benchmark indicator of energy efficiency.
b) Process-level energy efficiency benchmark line
A process can consist of a single production process or multiple production
processes. The following methods can be used to determine the energy efficiency
benchmark line at the process level: reference value method, mechanism modeling
method, data fitting method. The reference value method can refer to the reference
energy consumption per unit output of the production process provided by the
relevant industry associations and organizations, or the energy consumption per
unit output of the theoretical design or take energy efficiency optimization as the
energy efficiency benchmark line. The mechanism modeling method is based on
the production process principle of the process and considers the constraints such
as materials and energy to establish a process energy efficiency model. Calculate
the reference value of process energy efficiency based on the process energy
efficiency model. The data fitting method is based on the relevant status data and
product data during the operation of the production process. Determine the
influencing factors that affect the production process. The relationship between
process energy efficiency and influencing factors is obtained by mathematical
regression method. Based on the relationship, the reference value of process energy
efficiency can be obtained. Determination of process-level energy efficiency
benchmark line needs to consider their applicable operating conditions.
Example 2: For atmospheric and vacuum processes in oil refining production, the
"heat balance method" based on process mechanism is used to calculate the
benchmark energy efficiency. For the hot rolling process in metallurgical
production, considering the thickness of incoming materials, the thickness of the
rolled piece exit and other factors, the polynomial regression method is used to
calculate the benchmark energy efficiency.
c) Equipment-level energy efficiency benchmark line
The following methods can be used to determine the equipment-level energy
efficiency benchmark line: reference value method, mechanism modeling method,
data fitting method. The reference value method is based on parameters such as the
rated power of the equipment provided by the equipment manufacturer and the
energy consumption data of typical operating conditions. Through the verification
of relevant parameters and data in the actual working environment, it is used as the
energy efficiency benchmark line of the equipment. The mechanism modeling
method is to establish the energy efficiency model of the equipment based on the
working principle of the equipment and the physical or chemical change
mechanism during the operation process. Based on the energy efficiency model,
the energy efficiency of the equipment under ideal conditions can be calculated
and used as the energy efficiency benchmark line of the equipment. The data fitting
method is based on the state data during the operation of the equipment and the
analysis of the factors affecting the energy efficiency of the equipment. The
relationship between influencing factors and energy efficiency is obtained by
mathematical regression method. Based on the established mathematical
relationship, the reference value of equipment energy efficiency under different
working conditions can be obtained as the energy efficiency benchmark line of the
equipment.
Example 3: CNC machine tools, based on the working principle, are divided into
load-independent energy consumption subsystems (including lubrication and
cooling systems, auxiliary systems, peripheral systems, hydraulic systems) and
load-related energy consumption subsystems (including main drive system, feed
system). Establish a CNC machine tool energy consumption model including the
above components. For ball mill, establish a regression model including grinding
particle size, mill parameters, mill energy consumption and other data. The
relationship between the key influencing factors and the energy consumption of
the mill is formed.
7.2 Assessment of energy efficiency improvement potential
Evaluate the energy efficiency improvement potential of energy efficiency diagnostic
objects such as equipment, processes, and enterprises. It needs to determine the
indicators that describe the energy efficiency improvement potential first. Evaluate the
energy efficiency improvement potential through indicator calculation. Formula (1) is
the calculation formula of the energy efficiency improvement potential indicator.
Where,
EER - The indicator for energy efficiency improvement potential;
Es - The actual energy consumption of the manufacturing enterprise, or process, or
energy efficiency are determined. Finally, the overall energy efficiency improvement
potential assessment, the positioning of key processes and main influencing factors in
the production process, and the positioning of key equipment and key influencing
factors at the equipment level are formed.
8.3 Determination of energy efficiency improvement goals
Based on the accurate positioning of the energy efficiency problems of manufacturing
enterprises, through effective communication with the management of the enterprise,
considering the current economic status quo, operation status quo, technology status
quo, and personnel status quo of the enterprise, develop a corporate energy efficiency
improvement plan. The enterprise energy efficiency improvement plan shall include but
not limited to technical transformation for equipment, process and energy supply
system, energy management or energy efficiency management information system
construction or upgrade, management optimization for energy efficiency, qualitative
and quantitative evaluation of the effect after the implementation of energy efficiency
improvement. The completion period of the enterprise energy efficiency improvement
plan can be set at 3 to 5 years. Energy efficiency improvement goals can be divided into
long-term goals and periodic goals. A long-term goal can help enterprises better achieve
energy-saving goals, avoid short-term behavior, and be sustainable. Periodic goals are
usually achieved annually and shall be coordinated with long-term goals. Energy
efficiency improvement goals shall be qualitatively and quantitatively measured. It may
conduct quantitative calculation of technical transformation of equipment, process and
energy supply system. Carry out qualitative analysis and effect estimation of energy
management or information system construction or upgrade of energy efficiency
management. This is used as the basis for formulating energy efficiency improvement
goals. In addition, it is necessary to calculate the economic input and evaluate the effect
of input and output on the energy efficiency improvement plan and energy efficiency
improvement goal. If the input and output expectations of the enterprise are not met,
the energy efficiency improvement plan and energy efficiency improvement goals can
be adjusted.
9 Energy efficiency improvement plan
Based on the energy efficiency improvement plan and energy efficiency improvement
goals of the enterprise, the energy efficiency improvement plan is formulated around
the technical transformation of equipment/process/energy supply system, the
construction or upgrade of energy management or energy efficiency management
information system, and the management optimization for energy efficiency.
For the technical transformation of equipment, processes and energy supply systems,
improvement plans shall be formulated from the following aspects: improvement of
digital capabilities, provision of data collection and communication interfaces for
equipment, processes, and energy supply systems; replacement or energy-saving
transformation of high-energy-consuming equipment, such as the use of energy-saving
......
Source: Above contents are excerpted from the PDF -- translated/reviewed by: www.chinesestandard.net / Wayne Zheng et al.
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