CN111582569A - Energy consumption optimization analysis method and device - Google Patents
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Abstract
The invention is suitable for the technical field of energy-saving service analysis, and provides an energy consumption optimization analysis method and device, which comprise the following steps: acquiring real-time energy consumption data of a user; acquiring the maximum energy demand value of a user within a period time; comparing the real-time energy consumption data with the maximum demand value, and if the real-time energy consumption data is higher than the maximum demand value and an energy consumption unit with a high energy consumption level is started currently, acquiring the energy consumption valley time of a user; and prompting the user to start the energy utilization unit of the high energy utilization level at the energy utilization valley time. The method can analyze and suggest each platform user according to the actual situation of the platform user, firstly predict the load curve, then regulate and control the peak value equipment starting strategy according to the load curve, finally realize peak clipping and valley filling by combining the regulation strategy and the manual regulation after reminding, and comprehensively analyze the energy consumption data of the user by combining the energy consumption and the production data of the user, thereby realizing the accurate grasp of the capacity demand and further realizing the optimization of the energy consumption and the control of the cost.
Description
Technical Field
The invention belongs to the technical field of energy-saving service analysis, and particularly relates to an energy consumption optimization analysis method and device.
Background
At present, value-added services provided for energy-consuming users are the key concerns of many energy-saving service providers, and in many energy-saving operation and maintenance services, because real energy-consuming data of users cannot be mastered and cannot be close to the users, only one gateway table can be set for each user to monitor the energy-consuming conditions of the users. However, some users have many production lines and energy utilization devices under the jurisdiction, and the use of different production lines and energy utilization devices has great difference, and the statistics performed by only one general gateway table is very rough. If the production of enterprises is suddenly increased, effective control cannot be realized, so that the use condition of the user cannot be accurately grasped.
Meanwhile, most energy-saving operation and maintenance service providers perform energy consumption optimization analysis on users through the control of electricity price, and do not analyze the energy consumption condition of the most basic production line or energy consumption equipment, so that the services only can reduce the energy consumption cost properly, and the help to the production condition of the users is limited.
Disclosure of Invention
In view of this, embodiments of the present invention provide an energy consumption optimization analysis method and apparatus, which perform comprehensive analysis by combining energy consumption of a user and production data, and grasp the energy consumption data of the user more accurately, thereby implementing accurate grasp of capacity demand, and further implementing energy consumption optimization and cost control.
The first aspect of the embodiments of the present invention provides an energy consumption optimization analysis method, including:
acquiring real-time energy consumption data of a user;
acquiring the maximum energy demand value of a user within a period time;
comparing the real-time energy consumption data with the maximum demand value, and if the real-time energy consumption data is higher than the maximum demand value and an energy consumption unit with a high energy consumption level is started currently, acquiring the energy consumption valley time of a user;
and prompting the user to start the energy utilization unit of the high energy utilization level at the energy utilization valley time.
A second aspect of an embodiment of the present invention provides an energy consumption optimization analysis apparatus, including:
the first acquisition module is used for acquiring real-time energy consumption data of a user;
the second acquisition module is used for acquiring the maximum energy demand value of the user within the period time;
the comparison and analysis module is used for comparing the real-time energy consumption data with the maximum demand value, and if the real-time energy consumption data is higher than the maximum demand value and an energy consumption unit with a high energy consumption level is started currently, the energy consumption valley time of a user is obtained;
and the analysis output module is used for prompting a user to start the energy utilization unit of the high energy utilization level at the energy utilization valley time.
A third aspect of the embodiments of the present invention provides a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the method when executing the computer program.
A fourth aspect of embodiments of the present invention provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements the steps of the above-described method.
Compared with the prior art, the embodiment of the invention has the following beneficial effects:
according to the embodiment of the invention, the load curve can be analyzed and suggested according to the actual conditions of each platform user, the load curve is predicted, then the peak value equipment starting strategy is regulated and controlled according to the load curve, finally the peak clipping and valley filling are realized by combining the regulation and control strategy and the manual regulation and control after reminding, the user energy consumption data is more accurately grasped by combining the comprehensive analysis of the user energy consumption and production data, so that the accurate grasping of the capacity demand is realized, and the energy consumption optimization and the cost control are further realized.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed for the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
FIG. 1 is a schematic flow chart of an energy consumption optimization analysis method according to an embodiment of the present invention;
fig. 2 is a schematic flow chart illustrating a method for analyzing energy consumption optimization according to an embodiment of the present invention to obtain a maximum energy consumption value of a user within a period time;
FIG. 3 is a schematic flow chart of an energy consumption optimization analysis method according to a second embodiment of the present invention;
FIG. 4 is a schematic diagram of an energy use optimization analysis apparatus provided by an embodiment of the present invention;
FIG. 5 is a schematic diagram of a second obtaining module in the energy consumption optimization analysis apparatus according to an embodiment of the present invention;
fig. 6 is a schematic diagram of a terminal device according to an embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail. All other embodiments, which can be derived by a person skilled in the art from the described embodiments of the invention, are within the scope of the invention. Unless otherwise specified, the technical means used in the examples are conventional means well known to those skilled in the art.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the present application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in the specification of the present application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to a determination" or "in response to a detection". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted contextually to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]".
The energy system platform is an energy ecological platform which interconnects and intercommunicates energy facilities of a plurality of users, provides intelligent support for each participant of energy ecology by utilizing a digital technology, provides value service for the users and realizes information-guided energy ordered flow, such as an universal energy network. The energy system platform can more effectively acquire detailed energy utilization data of the user, so that the energy utilization condition of the user can be effectively analyzed.
Therefore, the embodiment of the present invention mainly uses an energy system platform to serve a user, and for explaining the technical solution of the present invention, the following description is given by using a specific embodiment.
The first embodiment is as follows:
referring to fig. 1, a method for energy consumption optimization analysis according to an embodiment of the present invention includes:
step S11: acquiring real-time energy consumption data of a user;
step S12: acquiring the maximum energy demand value of a user within a period time;
step S13: comparing the real-time energy consumption data with the maximum demand value, and if the real-time energy consumption data is higher than the maximum demand value and an energy consumption unit with a high energy consumption level is started currently, acquiring the energy consumption valley time of a user;
step S14: and prompting the user to start the energy utilization unit of the high energy utilization level at the energy utilization valley time.
When a user on the platform interconnects and intercommunicates the energy facility of the user and the system platform, the platform can accurately and quickly acquire detailed data of the user, such as real-time energy consumption data, historical energy consumption data and more specific conditions of respective energy consumption of equipment at each level.
Therefore, the maximum demand value in a period of time can be analyzed through historical energy consumption data, the period of time can be set to be one month, one quarter or half a year and the like, the embodiment is preferably set to be 90 days, and the energy consumption situation of each level of equipment of the user can determine which units with higher energy consumption belong to energy consumption units, namely energy consumption units with high energy consumption levels, the energy consumption units can be the whole production line, or energy consumption equipment with serious energy consumption or important use under any production line, and the platform pays attention to the energy consumption units with high energy consumption levels. Once the current real-time energy usage data exceeds the historical maximum demand value, the user needs to be prompted, for example: the current energy consumption exceeds the historical maximum energy consumption, and the energy consumption unit of the high energy consumption level is not started temporarily. If the energy unit with the high energy level is still determined to be running or started, the user needs to be reminded whether to change the running time of the energy unit, such as the energy consumption valley period in the historical data, and the user can decide whether to adjust the energy unit with the high energy level to the energy consumption valley time to start.
Therefore, the platform can analyze and suggest each platform user according to the actual situation of the platform user, firstly predicts the load curve, then regulates and controls the peak value equipment starting strategy according to the load curve, finally realizes peak clipping and valley filling by combining the regulation strategy and manual regulation after reminding, and comprehensively analyzes the energy consumption data of the user by combining the energy consumption and the production data of the user, thereby realizing accurate grasp of energy demand and further realizing energy consumption optimization and cost control.
In this embodiment, preferably, in step S13: before comparing the real-time energy consumption data with the maximum demand value, the method further comprises the following steps:
step S10: user's energy level-used partition data is acquired.
The obtained division condition may be that the platform performs statistics on the electricity consumption data of the user through an internet of things meter of the user, for example: grading and monitoring key data of a gateway table, secondary energy consumption data and large energy consumption equipment data of an enterprise user on a metering scheme of the electricity consumption data; or the user can divide the platform for uploading. The division of the energy level for the enterprise is generally performed by the enterprise itself, and after the division, registration of the energy level is kept unchanged unless the energy level is updated or changed by an energy device, a production line is updated, or the like.
In this embodiment, the user is preferably an enterprise user, and the dividing data by energy level includes:
a first energy level representing a total gateway energy usage for the enterprise;
the second energy level represents the energy utilization of each production line of the enterprise;
the third energy level represents the energy consumption of key energy consumption equipment in each production line;
wherein the second energy level and the third energy level are both high energy levels.
The division basis is that the scale of the enterprise energy consumption is divided: the primary energy consumption refers to the total gateway table data of the enterprise, represents the total energy consumption of the whole enterprise and is a first energy level; the secondary energy consumption refers to energy consumption data of enterprise production lines, production and manufacturing are divided for industrial enterprises, and each production line is marked as secondary energy consumption data and is a second energy level; the three-level energy utilization refers to some key energy utilization equipment on each production line, and for some high-power energy utilization equipment which has a large influence on the whole load, the three-level energy utilization is a third energy level, and the third energy level is usually the power utilization equipment with the power consumption of more than 100 kW. The secondary energy consumption is regarded as the integral opening of a production line, and the change of the secondary energy consumption and the tertiary energy consumption of large energy consumption equipment to the integral demand value is larger and more serious, so the two factors are monitored, and the influence of the small energy consumption equipment to the integral demand value can be ignored generally.
Referring to fig. 2, in the present embodiment, step S12: the obtaining of the maximum energy demand value of the user within the period time includes:
step S121: counting energy consumption data of the user within a period time;
step S122: recording the maximum demand in unit time with the maximum energy consumption in the period time as the maximum demand value;
step S123: and updating the latest energy data in unit time every time the user increases one energy data in unit time, and correspondingly rejecting the energy data in the earliest unit time in the cycle time.
In this embodiment, the energy consumption data of the energy consumption enterprise is counted and analyzed by taking 90 days as a unit, that is, the earliest day in the 90-day counting period is removed every day when the electricity consumption data of the enterprise increases, the energy consumption data of the latest day is added, and then the day of counting the maximum demand in the 90 days is recorded as the maximum electricity consumption value of the enterprise.
Example two:
referring to fig. 3, a method for energy consumption optimization analysis according to an embodiment of the present invention includes:
step S10: acquiring energy level division data of a user;
step S11: acquiring real-time energy consumption data of a user;
step S12: acquiring the maximum energy demand value of a user within a period time;
step S13: comparing the real-time energy consumption data with the maximum demand value, and if the real-time energy consumption data is higher than the maximum demand value and an energy consumption unit with a high energy consumption level is started currently, acquiring the energy consumption valley time of a user;
step S14: prompting a user to turn on an energy utilization unit of the high energy utilization level at the energy utilization valley time;
step S15: judging whether the energy consumption data of the energy consumption unit for starting the high energy consumption level by the user at the energy consumption valley time is higher than the maximum demand value;
step S16: and if the energy consumption data is higher than the maximum demand value, normally starting an energy consumption unit of the high energy consumption level, and updating the energy consumption data to a new maximum demand value.
The difference between this embodiment and the first embodiment is that, after the platform helps the user to analyze and remind the user to adjust the high energy level start time, the platform also helps to analyze whether the start time is still higher than the maximum demand value after adjustment, if not, the user can normally adjust the start time, and if so, the user is still allowed to normally adjust the start, but the historical maximum demand value is updated to the new energy consumption data after adjustment, so as to meet the new demand of the user.
The invention further provides a strategy through the energy system platform for carrying out auxiliary analysis on the user, whether the strategy is executed or not is finally determined by the user, the strategy can be controlled manually by the user, and the platform can be used for assisting optimization, so that the energy utilization condition of the user is optimized, the power utilization cost can be properly reduced, and the method is irrelevant to the actual peak-valley power charge.
In this embodiment, the energy level division data of the user is acquired and set by the user, and the platform is acquired once when the user initializes, and then the user uploads the data again if the platform is changed.
Preferably, in this embodiment, the user is a production line user, and the dividing data by energy level includes:
a first energy level representing a total energy usage of the production line;
the second energy level represents the energy consumption of key energy consumption equipment in the production line;
wherein the second energy level is a high energy level.
Similarly, the first energy level is regarded as the overall start of a production line, and some important energy utilization devices on the production line, which generally refer to power utilization devices with power consumption greater than 100kW, belong to high-power energy utilization devices which have a large influence on the overall load, and belong to the important attention objects of the platform as the second energy level.
Example three:
referring to fig. 4, an energy consumption optimization analysis apparatus according to an embodiment of the present invention includes: a first acquisition module 21, a second acquisition module 22, a comparison and analysis module 23 and an analysis output module 24, wherein,
the first obtaining module 21 is configured to obtain real-time energy consumption data of a user;
the second obtaining module 22 is configured to obtain a maximum demand value of the user energy in the cycle time;
the comparing and analyzing module 23 is configured to compare the real-time energy consumption data with the maximum demand value, and if the real-time energy consumption data is higher than the maximum demand value and an energy consumption unit with a high energy consumption level is currently started, obtain an energy consumption valley time of a user;
the analysis output module 24 is configured to prompt the user to turn on the energy usage unit of the high energy usage level at the energy usage valley time.
As shown in fig. 5, the second obtaining module 22 may further include: a counting unit 221, a marking unit 222, and an updating unit 223;
the statistic unit 221 is configured to count the energy consumption data of the user within a period time;
the marking unit 222 is configured to mark the maximum demand in the unit time with the maximum available energy in the cycle time as the maximum demand value;
the updating unit 223 is configured to update the latest energy data per unit time every time the user adds one energy data per unit time, and correspondingly remove the energy data in the earliest unit time in the cycle time.
Fig. 6 is a schematic diagram of the terminal device 3 according to an embodiment of the present invention. As shown in fig. 6, the terminal device 3 of this embodiment includes a processor 31, a memory 31, and a computer program 32, such as an energy optimization analysis program, stored in the memory 31 and executable on the processor 31. The processor 30, when executing the computer program 32, implements the steps in the various method embodiments described above, such as the steps S10-S14 shown in fig. 1. Alternatively, the processor 30, when executing the computer program 32, implements the functions of the modules/units in the above-mentioned device embodiments, such as the functions of the modules 21 to 24 shown in fig. 4.
Illustratively, the computer program 32 may be partitioned into one or more modules/units that are stored in the memory 31 and executed by the processor 30 to implement the present invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution process of the computer program 32 in the terminal device 3.
The terminal device 3 may be a desktop computer, a notebook, a palm computer, a cloud server, or other computing devices. The terminal device 3 may include, but is not limited to, a processor 30 and a memory 31. It will be understood by those skilled in the art that fig. 6 is only an example of the terminal device 3, and does not constitute a limitation to the terminal device 3, and may include more or less components than those shown, or combine some components, or different components, for example, the terminal device 3 may further include an input-output device, a network access device, a bus, etc.
The Processor 30 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 31 may be an internal storage unit of the terminal device 3, such as a hard disk or a memory of the terminal device 3. The memory 31 may also be an external storage device of the terminal device 3, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the terminal device 3. Further, the memory 31 may also include both an internal storage unit and an external storage device of the terminal device 3. The memory 31 is used for storing the computer programs and other programs and data required by the terminal device 3. The memory 31 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Of course, the units and modules may be replaced by a processor containing a computer program, and the work of each part can be completed in a pure software form.
Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other ways. For example, the above-described embodiments of the apparatus/terminal device are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
Claims (10)
1. An energy use optimization analysis method, comprising:
acquiring real-time energy consumption data of a user;
acquiring the maximum energy demand value of a user within a period time;
comparing the real-time energy consumption data with the maximum demand value, and if the real-time energy consumption data is higher than the maximum demand value and an energy consumption unit with a high energy consumption level is started currently, acquiring the energy consumption valley time of a user;
and prompting the user to start the energy utilization unit of the high energy utilization level at the energy utilization valley time.
2. The energy usage optimization analysis method of claim 1, wherein the step of prompting the user to turn on the energy usage unit of the high energy usage level at the energy usage valley time is followed by:
judging whether the energy consumption data of the energy consumption unit for starting the high energy consumption level by the user at the energy consumption valley time is higher than the maximum demand value;
and if the energy consumption data is higher than the maximum demand value, normally starting an energy consumption unit of the high energy consumption level, and updating the energy consumption data to a new maximum demand value.
3. The energy consumption optimization analysis method of claim 1, wherein before comparing the real-time energy consumption data with the maximum demand value, further comprising:
user's energy level-used partition data is acquired.
4. The energy consumption optimization analysis method of claim 3, wherein the user is an enterprise user, and wherein the partitioning data with energy levels comprises:
a first energy level representing a total gateway energy usage for the enterprise;
the second energy level represents the energy utilization of each production line of the enterprise;
the third energy level represents the energy consumption of key energy consumption equipment in each production line;
wherein the second energy level and the third energy level are both high energy levels.
5. The energy consumption optimization analysis method of claim 3, wherein the user is a production line user, and the dividing data by energy level comprises:
a first energy level representing a total energy usage of the production line;
the second energy level represents the energy consumption of key energy consumption equipment in the production line;
wherein the second energy level is a high energy level.
6. The energy consumption optimization analysis method of claim 1, wherein the obtaining of the maximum demand value of the user energy consumption in the cycle time comprises:
counting energy consumption data of the user within a period time;
and recording the maximum demand in the unit time with the maximum energy consumption in the period time as the maximum demand value.
7. The energy consumption optimization analysis method of claim 6, wherein counting the energy consumption data of the user within a period time further comprises:
and updating the latest energy data in unit time every time the user increases one energy data in unit time, and correspondingly rejecting the energy data in the earliest unit time in the cycle time.
8. An energy use optimization analysis apparatus, comprising:
the first acquisition module is used for acquiring real-time energy consumption data of a user;
the second acquisition module is used for acquiring the maximum energy demand value of the user within the period time;
the comparison and analysis module is used for comparing the real-time energy consumption data with the maximum demand value, and if the real-time energy consumption data is higher than the maximum demand value and an energy consumption unit with a high energy consumption level is started currently, the energy consumption valley time of a user is obtained;
and the analysis output module is used for prompting a user to start the energy utilization unit of the high energy utilization level at the energy utilization valley time.
9. A terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.
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