CN108923426B - Load identification method, device, equipment and computer readable storage medium - Google Patents
Load identification method, device, equipment and computer readable storage medium Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for AC mains or AC distribution networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for AC mains or AC distribution networks
- H02J3/003—Load forecast, e.g. methods or systems for forecasting future load demand
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Abstract
The application discloses a load identification method, a device, equipment and a computer readable storage medium, wherein the method comprises the following steps: acquiring a total consumed power curve of the electric meter; determining a plurality of powers to be decomposed and time characteristics corresponding to each power to be decomposed according to the step-type characteristics of the total consumed power curve, wherein the time characteristics comprise: a start time and an end time; in an electrical appliance power database, determining an electrical appliance power group corresponding to each power to be decomposed according to each power to be decomposed and the corresponding time characteristic thereof, wherein the electrical appliance power database comprises: the electric appliance power control method comprises electric appliance power groups formed by electric appliance powers and time characteristics corresponding to the electric appliance powers in each electric appliance power group. The technical problem that the existing load identification has higher requirements on the computing capacity of equipment due to huge data volume is solved.
Description
Technical Field
The present application belongs to the field of power technologies, and in particular, to a load identification method, apparatus, device, and computer-readable storage medium.
Background
With the development of society, the proportion of resident electricity consumption to the total electricity consumption of a power distribution network is larger and larger, and the load identification of a user side is widely concerned by researchers. The load identification means that the total power consumption of the electric meter is decomposed into various household appliances in a home scene, and the power grid can know the power utilization habits of users according to the load identification result, so that the management level of the users is improved.
However, the existing load identification method has huge data volume and has higher requirements on the computing capacity of equipment, such as: when the load decomposition condition in one day is analyzed, 24 × 60 — 86400 points are needed to be analyzed, and the data volume is huge.
Disclosure of Invention
The application provides a load identification method, a device, equipment and a computer readable storage medium, which are used for load identification of power consumption of a user side and solve the technical problem that the existing load identification has higher requirements on the computing capacity of the equipment due to huge data volume.
In view of the above, a first aspect of the present application provides a load identification method, including:
acquiring a total consumed power curve of the electric meter;
determining a plurality of powers to be decomposed and time characteristics corresponding to each power to be decomposed according to the step-type characteristics of the total consumed power curve, wherein the time characteristics comprise: a start time and an end time;
in an electrical appliance power database, determining an electrical appliance power group corresponding to each power to be decomposed according to each power to be decomposed and the corresponding time characteristic thereof, wherein the electrical appliance power database comprises: the electric appliance power control method comprises electric appliance power groups formed by electric appliance powers and time characteristics corresponding to the electric appliance powers in each electric appliance power group.
Preferably, the step-type characteristic of the total consumed power curve is used to determine a plurality of powers to be decomposed and a time characteristic corresponding to each power to be decomposed, where the time characteristic includes: opening time and end time:
determining a power average value of each step on the total consumed power curve and a time characteristic corresponding to each step according to the step-shaped characteristic of the total consumed power curve, wherein the time characteristic comprises opening time and ending time;
and taking the power average value of a plurality of steps as a plurality of powers to be decomposed, and taking the time characteristic of each step as the time characteristic of the corresponding power to be decomposed.
Preferably, the determining, in the electrical power database, the electrical power group corresponding to each power to be split according to each power to be split and the corresponding time characteristic thereof includes:
determining all power groups of the electric appliances to be matched corresponding to each power to be decomposed and time characteristics corresponding to each power group of the electric appliances to be matched in an electric appliance power database, wherein each power to be decomposed is equal to the sum of the powers of all electric appliances in each power group of the electric appliances to be matched corresponding to the power to be decomposed;
and determining the electric appliance power group corresponding to each power to be decomposed according to the time characteristic of each power to be decomposed and the time characteristic of each corresponding electric appliance power group to be matched.
Preferably, the determining, according to the time characteristic of each power to be split and the time characteristic of each corresponding electrical appliance power group to be matched, the electrical appliance power group corresponding to each power to be split specifically includes:
calculating the starting probability of each electric appliance power group to be matched on the starting time of the power to be decomposed corresponding to the electric appliance power group to be matched according to the starting time of each power to be decomposed and the starting time of each electric appliance power group to be matched corresponding to the starting time of the power to be decomposed, and determining the electric appliance power groups to be matched with the maximum first preset number of starting probabilities;
and determining the electric appliance power group to be matched with the maximum likelihood according to the end time of each electric appliance power group to be matched based on a maximum likelihood estimation method in the first preset number of electric appliance power groups to be matched of each power to be decomposed, wherein the electric appliance power group to be matched with the maximum likelihood is the electric appliance power group with the power to be decomposed corresponding to the electric appliance power group to be matched.
Preferably, the method further comprises:
collecting the power of each electric appliance in the household of a user when the electric appliance operates independently and the time characteristics corresponding to the power of each electric appliance;
and determining the working power with the same time characteristic to form an electric appliance power group according to each working power and the time characteristic of each working power to obtain an electric appliance power database.
Preferably, the acquiring the power of each electric appliance in the user's home when the electric appliance operates independently and the time characteristic corresponding to the power of each electric appliance specifically includes:
acquiring a working power curve of each electric appliance in the user's home when the electric appliances operate independently;
and obtaining the electric appliance power corresponding to the working power curve of each electric appliance when the electric appliance operates independently and the time characteristic of each electric appliance power according to an unsupervised clustering algorithm.
Preferably, the obtaining of the total consumed power curve of the electricity meter further includes:
and preprocessing the total consumed power curve.
A second aspect of the present application provides a load recognition apparatus, including:
the acquisition unit is used for acquiring a total consumed power curve of the electric meter;
a first unit, configured to determine, according to a step-like feature of the total consumed power curve, a plurality of powers to be decomposed and a time feature corresponding to each of the powers to be decomposed, where the time feature includes: a start time and an end time;
a second unit, configured to determine, in an electrical appliance power database, an electrical appliance power group corresponding to each power to be split according to each power to be split and a time characteristic corresponding to the power to be split, where the electrical appliance power database includes: the electric appliance power control method comprises electric appliance power groups formed by electric appliance powers and time characteristics corresponding to the electric appliance powers in each electric appliance power group.
A third aspect of the present application provides a load identification device, the device comprising a processor and a memory:
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is used for executing the load identification method according to the instructions in the program codes.
A fourth aspect of the present application provides a computer-readable storage medium for storing program code for executing the load identification method described above.
According to the technical scheme, the embodiment of the application has the following advantages:
the application provides a load identification method, a device, equipment and a computer readable storage medium, wherein the method comprises the following steps: firstly, acquiring a total power consumption curve of an electric meter, wherein each step corresponds to a power value because the total power consumption curve is in stepped change, each power value corresponds to the use state of a group of household appliances, and the use state of the household appliances can not be changed when the total power consumption value is not changed, so that a plurality of powers to be decomposed are determined according to the stepped characteristics of the total power consumption curve, and then the powers to be decomposed are only needed to be decomposed to obtain the corresponding appliance power groups (the use states of the household appliances), namely, the use states of the household appliances of the whole total power consumption curve corresponding to the powers to be decomposed can be obtained, all points on the total power consumption curve are not needed to be analyzed, the data volume during calculation is reduced, so that load identification can be carried out on equipment with low calculation capacity, and the problem that the existing load identification is huge in data volume is solved, the technical problem of high requirements on the computing power of the equipment.
Drawings
Fig. 1 is a schematic flowchart of a first embodiment of a load identification method in an embodiment of the present application;
fig. 2 is a schematic flowchart of a second embodiment of a load identification method in the embodiment of the present application;
FIG. 3 is a schematic structural diagram of a load identification apparatus according to an embodiment of the present application;
fig. 4 is a diagram illustrating a total power consumption curve of the electricity meter according to the embodiment of the present application.
Detailed Description
The embodiment of the application provides a load identification method, a load identification device, load identification equipment and a computer readable storage medium, which are used for load identification of power consumption of a user side and solve the technical problem that the existing load identification has high requirements on the computing capacity of the equipment due to huge data volume.
In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Referring to fig. 1, a schematic flow chart of a first embodiment of a load identification method in an embodiment of the present application includes:
In order to identify the load, first, a total power consumption curve of the electric meter is acquired. It will be appreciated that the power consumption curve is plotted on the abscissa for time and on the ordinate for power, as shown in fig. 4.
It should be noted that, because the total power consumption curve shows a step-like change, each step corresponds to a power value, each power value corresponds to a usage state of a group of home appliances, and when the total power consumption value is not changed, the usage state of the home appliances is not changed, so that a plurality of powers to be decomposed and the time characteristic of each power to be decomposed are determined according to the step-like characteristic of the total power consumption curve.
103, determining an electric appliance power group corresponding to each power to be decomposed according to each power to be decomposed and the corresponding time characteristic in an electric appliance power database, wherein the electric appliance power database comprises: the electric appliance power group formed by the electric appliance powers and the time characteristics corresponding to the electric appliance powers in each electric appliance power group.
It should be noted that, after determining a plurality of powers to be decomposed on the total consumed power curve, determining, in an electrical appliance power database, an electrical appliance power group corresponding to each power to be decomposed according to each power to be decomposed and a time characteristic corresponding to the power to be decomposed, where the electrical appliance power database includes: the electric appliance power group formed by the electric appliance powers and the time characteristics corresponding to the electric appliance powers in each electric appliance power group.
In the embodiment, the total power consumption curve of the electric meter is firstly obtained, each step corresponds to one power value because the total power consumption curve is in step-like change, each power value corresponds to the use state of a group of household appliances, and the use states of the household appliances are not changed when the total power consumption value is not changed, so that a plurality of powers to be decomposed are determined according to the step-like characteristics of the total power consumption curve, and then the powers to be decomposed are decomposed to obtain the corresponding appliance power groups (the use states of the household appliances), so that the use states of the household appliances of the whole total power consumption curve corresponding to the powers to be decomposed can be obtained, all points on the total power consumption curve are not required to be analyzed, the data volume during calculation is reduced, the load identification can also be carried out on equipment with weak calculation capacity, and the problem that the existing load identification is huge in data volume is solved, the technical problem of high requirements on the computing power of the equipment.
The above is a first embodiment of a load identification method provided in the embodiments of the present application, and the following is a second embodiment of a load identification method provided in the embodiments of the present application.
Referring to fig. 2, a flowchart of a second embodiment of a load identification method in the embodiment of the present application includes:
It should be noted that, in order to create the electrical appliance power database, first, the electrical appliance power of each electrical appliance in the user's home when operating alone and the time characteristics corresponding to each electrical appliance power are collected.
Further, collecting the power of each electrical appliance in the user's home when the electrical appliance operates alone and the time characteristic corresponding to the power of each electrical appliance specifically includes: acquiring a working power curve of each electric appliance in the user's home when the electric appliances operate independently; and obtaining the electric appliance power corresponding to the working power curve of each electric appliance when the electric appliance operates independently and the time characteristic of each electric appliance power according to an unsupervised clustering algorithm. It is understood that the abscissa of the operating power curve of each appliance is time and the ordinate is power. It can be understood that although a single electrical appliance has a fixed working power, when the working power curve of the electrical appliance is collected, each power value may fluctuate, so that the working power of each electrical appliance during independent operation and the time characteristic corresponding to each working power are obtained according to an unsupervised clustering algorithm. Specifically, obtaining the working power of each electrical appliance when operating independently and the time characteristics corresponding to each working power according to the unsupervised clustering algorithm includes: and obtaining the possible working power of each electric appliance and the time characteristics corresponding to each possible working power according to a complete clustering algorithm, and then fusing the possible working power according to a class center fusion algorithm to obtain the electric appliance power of each electric appliance when the electric appliance operates independently and the time characteristics of each electric appliance power.
It should be noted that, after the power of each electrical appliance in the user's home when operating alone and the time characteristics corresponding to the power of each electrical appliance are collected, the operating powers with the same time characteristics can be determined to form an electrical appliance power group, and the combination of all the electrical appliance power groups obtains an electrical appliance power database.
It should be noted that the total consumed power curve may be preprocessed, and the preprocessing includes, but is not limited to, filtering using an averaging filter.
And 204, taking the power average value of the steps as a plurality of powers to be decomposed, and taking the time characteristic of each step as the time characteristic of the corresponding power to be decomposed.
It can be understood that, in order to make the calculation faster, the power and the equal appliance power in the appliance database may be first combined into a class group, for example, the appliance power group with all power sums being 200W is a class group, and the appliance power group with all power sums being 300W is a class group, when the appliance power group corresponding to the power to be decomposed is decomposed, after the power value of the power to be decomposed is known, only the power value needs to be searched in the class group corresponding to the value, thereby significantly reducing the calculation time.
And step 206, determining the electric appliance power group corresponding to each power to be decomposed according to the time characteristics of each power to be decomposed and the time characteristics of each corresponding electric appliance power group to be matched.
It should be noted that, in order to increase the calculation speed, the start probability of each to-be-matched electrical appliance power group at the start time of the to-be-matched power group corresponding to the to-be-matched electrical appliance power group may be calculated according to the start time of each to-be-decomposed power and the start time of each to-be-matched electrical appliance power group corresponding to the to-be-matched power group, and the to-be-matched electrical appliance power group with the maximum first preset number of start probabilities may be determined; for example, when the power to be decomposed is 200W, it may be determined that the power group of the electrical appliance to be matched corresponding to the power group to be decomposed is: the power set of the electric appliance to be matched is composed of a desk lamp and a television, and the power set of the electric appliance to be matched is composed of a computer and an air conditioner. It will be appreciated that the first preset number may be set according to actual needs.
And determining the likelihood of each electric appliance power group to be matched according to the end time of each electric appliance power group to be matched based on a maximum likelihood estimation method in the electric appliance power groups to be matched with the first preset number of each power to be decomposed, and taking the electric appliance power group to be matched with the maximum likelihood as the electric appliance power group with the power to be decomposed corresponding to the electric appliance power group to be matched. For example, in the 2 electric appliance power groups to be matched obtained in the previous step, the likelihood of the end time of each electric appliance power group to be matched is calculated, the maximum likelihood of the electric appliance power group to be matched formed by the computer and the air conditioner is obtained, and at this time, the electric appliance power group to be matched formed by the computer and the air conditioner is used as the electric appliance power group. It is understood that the maximum likelihood estimation method belongs to the prior art and is not described in detail herein.
In the embodiment, the total power consumption curve of the electric meter is firstly obtained, each step corresponds to one power value because the total power consumption curve is in step-like change, each power value corresponds to the use state of a group of household appliances, and the use states of the household appliances are not changed when the total power consumption value is not changed, so that a plurality of powers to be decomposed are determined according to the step-like characteristics of the total power consumption curve, and then the powers to be decomposed are decomposed to obtain the corresponding appliance power groups (the use states of the household appliances), so that the use states of the household appliances of the whole total power consumption curve corresponding to the powers to be decomposed can be obtained, all points on the total power consumption curve are not required to be analyzed, the data volume during calculation is reduced, the load identification can also be carried out on equipment with weak calculation capacity, and the problem that the existing load identification is huge in data volume is solved, the technical problem of high requirements on the computing power of the equipment.
The above is a second embodiment of the load identification method provided in the embodiment of the present application, and the following is an embodiment of a load identification device provided in the embodiment of the present application, please refer to fig. 3.
The load recognition device provided in the embodiment of the present application includes:
an obtaining unit 301, configured to obtain a total power consumption curve of an electric meter;
a first unit 302, configured to determine, according to a step-like feature of a total power consumption curve, a plurality of powers to be decomposed and a time feature corresponding to each power to be decomposed, where the time feature includes: a start time and an end time;
a second unit 303, configured to determine, in an electrical appliance power database, an electrical appliance power group corresponding to each power to be split according to each power to be split and a time characteristic corresponding to the power to be split, where the electrical appliance power database includes: the electric appliance power group formed by the electric appliance powers and the time characteristics corresponding to the electric appliance powers in each electric appliance power group.
In the embodiment, the total power consumption curve of the electric meter is firstly obtained, each step corresponds to one power value because the total power consumption curve is in step-like change, each power value corresponds to the use state of a group of household appliances, and the use states of the household appliances are not changed when the total power consumption value is not changed, so that a plurality of powers to be decomposed are determined according to the step-like characteristics of the total power consumption curve, and then the powers to be decomposed are decomposed to obtain the corresponding appliance power groups (the use states of the household appliances), so that the use states of the household appliances of the whole total power consumption curve corresponding to the powers to be decomposed can be obtained, all points on the total power consumption curve are not required to be analyzed, the data volume during calculation is reduced, the load identification can also be carried out on equipment with weak calculation capacity, and the problem that the existing load identification is huge in data volume is solved, the technical problem of high requirements on the computing power of the equipment.
An embodiment of the present application further provides a load identification device, where the device includes a processor and a memory: the memory is used for storing the program codes and transmitting the program codes to the processor; the processor is used for executing the load identification method according to instructions in the program codes.
An embodiment of the present application further provides a computer-readable storage medium, which is used for storing a program code, and the program code is used for executing the load identification method.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, 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 application 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 unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should 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; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.
Claims (8)
1. A method for load identification, comprising:
acquiring a total consumed power curve of the electric meter;
determining a plurality of powers to be decomposed and time characteristics corresponding to each power to be decomposed according to the step-type characteristics of the total consumed power curve, wherein the time characteristics comprise: a start time and an end time;
in an electrical appliance power database, determining an electrical appliance power group corresponding to each power to be decomposed according to each power to be decomposed and the corresponding time characteristic thereof, wherein the electrical appliance power database comprises: the method comprises the following steps of (1) forming an electric appliance power group by electric appliance powers and time characteristics corresponding to the electric appliance powers in each electric appliance power group;
the step of determining, in the electrical power database, the electrical power group corresponding to each power to be split according to each power to be split and the time characteristic corresponding to the power to be split specifically includes:
determining all power groups of the electric appliances to be matched corresponding to each power to be decomposed and time characteristics corresponding to each power group of the electric appliances to be matched in an electric appliance power database, wherein each power to be decomposed is equal to the sum of the powers of all electric appliances in each power group of the electric appliances to be matched corresponding to the power to be decomposed;
determining an electrical appliance power group corresponding to each power to be decomposed according to the time characteristics of each power to be decomposed and the time characteristics of each electrical appliance power group to be matched corresponding to the power to be decomposed;
the determining the electric appliance power group corresponding to each power to be decomposed according to the time characteristic of each power to be decomposed and the time characteristic of each electric appliance power group to be matched corresponding to the power to be decomposed specifically comprises:
calculating the starting probability of each electric appliance power group to be matched on the starting time of the power to be decomposed corresponding to the electric appliance power group to be matched according to the starting time of each power to be decomposed and the starting time of each electric appliance power group to be matched corresponding to the starting time of the power to be decomposed, and determining the electric appliance power groups to be matched with the maximum first preset number of starting probabilities;
and determining the electric appliance power group to be matched with the maximum likelihood according to the end time of each electric appliance power group to be matched based on a maximum likelihood estimation method in the first preset number of electric appliance power groups to be matched of each power to be decomposed, wherein the electric appliance power group to be matched with the maximum likelihood is the electric appliance power group with the power to be decomposed corresponding to the electric appliance power group to be matched.
2. The method according to claim 1, wherein the step-type characteristic of the total consumed power curve is used to determine a plurality of powers to be decomposed and a time characteristic corresponding to each power to be decomposed, and the time characteristic includes: opening time and end time:
determining a power average value of each step on the total consumed power curve and a time characteristic corresponding to each step according to the step-shaped characteristic of the total consumed power curve, wherein the time characteristic comprises opening time and ending time;
and taking the power average value of a plurality of steps as a plurality of powers to be decomposed, and taking the time characteristic of each step as the time characteristic of the corresponding power to be decomposed.
3. The method of claim 1, further comprising:
collecting the power of each electric appliance in the household of a user when the electric appliance operates independently and the time characteristics corresponding to the power of each electric appliance;
and determining the electric appliance power with the same time characteristic to form an electric appliance power group according to the electric appliance power and the time characteristic of the electric appliance power to obtain an electric appliance power database.
4. The method according to claim 3, wherein the collecting of the power of each electrical appliance in the user's home when the electrical appliance operates alone and the time characteristics corresponding to the power of each electrical appliance specifically comprises:
acquiring a working power curve of each electric appliance in the user's home when the electric appliances operate independently;
and obtaining the electric appliance power corresponding to the working power curve of each electric appliance when the electric appliance operates independently and the time characteristic of each electric appliance power according to an unsupervised clustering algorithm.
5. The method of claim 1, wherein obtaining the total power consumption curve of the electricity meter further comprises:
and preprocessing the total consumed power curve.
6. A load recognition device, comprising:
the acquisition unit is used for acquiring a total consumed power curve of the electric meter;
a first unit, configured to determine, according to a step-like feature of the total consumed power curve, a plurality of powers to be decomposed and a time feature corresponding to each of the powers to be decomposed, where the time feature includes: a start time and an end time;
a second unit, configured to determine, in an electrical appliance power database, an electrical appliance power group corresponding to each power to be split according to each power to be split and a time characteristic corresponding to the power to be split, where the electrical appliance power database includes: the method comprises the following steps of (1) forming an electric appliance power group by electric appliance powers and time characteristics corresponding to the electric appliance powers in each electric appliance power group;
the step of determining, in the electrical power database, the electrical power group corresponding to each power to be split according to each power to be split and the time characteristic corresponding to the power to be split specifically includes:
determining all power groups of the electric appliances to be matched corresponding to each power to be decomposed and time characteristics corresponding to each power group of the electric appliances to be matched in an electric appliance power database, wherein each power to be decomposed is equal to the sum of the powers of all electric appliances in each power group of the electric appliances to be matched corresponding to the power to be decomposed;
determining an electrical appliance power group corresponding to each power to be decomposed according to the time characteristics of each power to be decomposed and the time characteristics of each electrical appliance power group to be matched corresponding to the power to be decomposed;
the determining the electric appliance power group corresponding to each power to be decomposed according to the time characteristic of each power to be decomposed and the time characteristic of each electric appliance power group to be matched corresponding to the power to be decomposed specifically comprises:
calculating the starting probability of each electric appliance power group to be matched on the starting time of the power to be decomposed corresponding to the electric appliance power group to be matched according to the starting time of each power to be decomposed and the starting time of each electric appliance power group to be matched corresponding to the starting time of the power to be decomposed, and determining the electric appliance power groups to be matched with the maximum first preset number of starting probabilities;
and determining the electric appliance power group to be matched with the maximum likelihood according to the end time of each electric appliance power group to be matched based on a maximum likelihood estimation method in the first preset number of electric appliance power groups to be matched of each power to be decomposed, wherein the electric appliance power group to be matched with the maximum likelihood is the electric appliance power group with the power to be decomposed corresponding to the electric appliance power group to be matched.
7. A load recognition device, the device comprising a processor and a memory:
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is configured to perform the load identification method of any one of claims 1 to 5 according to instructions in the program code.
8. A computer-readable storage medium for storing a program code for executing the load identification method according to any one of claims 1 to 5.
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| CN201810915986.3A CN108923426B (en) | 2018-08-13 | 2018-08-13 | Load identification method, device, equipment and computer readable storage medium |
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| CN201810915986.3A CN108923426B (en) | 2018-08-13 | 2018-08-13 | Load identification method, device, equipment and computer readable storage medium |
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| CN108923426B true CN108923426B (en) | 2021-09-03 |
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