CN112288598A - Method and system for determining composition of load element of transformer substation - Google Patents
Method and system for determining composition of load element of transformer substation Download PDFInfo
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Abstract
The invention provides a method and a system for determining the composition of load elements of a transformer substation, which establish a load classification mapping table reflecting the corresponding relation between marketing load classification and line load types of outgoing line loads on a main transformer side and a load element composition mapping table reflecting the corresponding relation between the load classification of outgoing line lines on the main transformer side and the composition of load elements in different load use seasons; and then, acquiring the voltage, the current and the power factor of a main transformer side outgoing line of the transformer substation in the power grid to determine the active power of the line, acquiring marketing load classification data in the power grid, and determining the composition of a load element of the transformer substation by combining the load classification mapping table and the load element composition mapping table. The method and the system of the invention carry out intelligent matching on the load element composition of the transformer substation, thereby providing accurate load element data for load modeling and improving the simulation accuracy of the power system.
Description
Technical Field
The present invention relates to the field of power system data analysis, and more particularly, to a method and system for determining the composition of load elements of a substation.
Background
The construction and development of the intelligent power grid put higher requirements on the accuracy of real-time simulation calculation analysis of the power system. In order to meet the requirements of operation and control of the smart power grid, the safety and stability analysis of the power system needs dynamic model parameters capable of reflecting the actual characteristics of the power grid more accurately, and a load model is one of the most critical simulation models. However, due to the geographical dispersion and random time variation of the load nodes, it is difficult to determine the configuration of the load elements of each load node and obtain a comprehensive load model for reasonably describing each load node, so that the configuration becomes an important factor affecting the improvement of the simulation accuracy of the power system. With the rapid development of load modeling research work at home and abroad in recent years, researchers have proposed that various measurement means are adopted to determine the structure of load elements of each load node in a power grid so as to perform load modeling, wherein one of the measurement means is a statistical comprehensive load modeling method based on survey statistics. However, the survey statistics based approach faces two challenges in practical applications: firstly, the time and labor spent on investigation and statistics are huge, and moreover, due to the limitation of numerous conditions, the accuracy of investigation results is difficult to ensure; and secondly, the load composition of the power utilization industry and the power utilization industry composition survey of the transformer substation can only be static, the composition characteristics of the actual comprehensive load change along with time and have randomness, the characteristics of the change along with the time are hardly reflected on the basis of the survey statistics, the time-varying property of the load cannot be considered, and the dynamic process of the load cannot be accurately simulated.
Disclosure of Invention
In order to solve the technical problems that time and labor are huge, the accuracy of a result cannot be guaranteed and the change of a load along with time cannot be considered when the composition of the load element of each load node is determined by a method based on survey statistics in the prior art, the invention provides a method for determining the composition of the load element of a transformer substation, which comprises the following steps:
acquiring voltage, current and power factors of outgoing lines of main transformer sides of all transformer substations in a power grid, and acquiring marketing load classification data in the power grid;
calculating the active power of the outgoing line at the main transformer side of the transformer substation according to the voltage, the current and the power factor;
determining the line load classification of the outgoing line at the main transformer side of the transformer substation according to the marketing load classification data and a pre-established load classification mapping table;
determining a first load component configuration according to the line load classification and a pre-established load component configuration mapping table;
a second load element configuration is determined based on the active power and the first load element configuration.
Further, before collecting the voltage, the current and the power factor of an outgoing line of a main transformer side of each transformer substation in the power grid and collecting marketing load classification data in the power grid, the method further comprises the following steps:
the method comprises the steps of collecting marketing load classification historical data in an outgoing line of a main transformer side of a transformer substation as first historical data, and collecting load element types of the outgoing line of the main transformer side of the transformer substation in different load use seasons and the proportion of load elements in all load elements of the outgoing line as second historical data;
according to the set line load type and the first historical data, a load classification mapping table reflecting the corresponding relation between the marketing load classification of the outgoing line load of the main transformer side and the line load type is established;
and based on the second historical data and the load classification in the load classification mapping table, adopting a deep learning algorithm to establish a load element composition mapping table reflecting the corresponding relation between the load classification of the outgoing line at the main transformer side and the composition of the load elements in different load use seasons.
Further, the method further comprises:
updating first historical data of a main transformer side outgoing line of the transformer substation, and establishing an updated load classification mapping table reflecting the corresponding relation between marketing load classification and load types of main transformer side outgoing line loads based on the updated first historical data; and updating second historical data of the outgoing line at the main transformer side of the transformer substation, and establishing an updated load element composition mapping table reflecting the corresponding relation between the load classification of the outgoing line at the main transformer side and the composition of the load element according to the updated second historical data and the load classification in the updated classification mapping table.
Further, the collecting voltage, current and power factor of each transformer substation main transformer side outgoing line in the power grid, and collecting marketing load classification data in the power grid include:
voltage of outgoing line of main transformer side of each transformer substation in power grid is collected based on intelligent power grid dispatching system and distribution automation system
Current of
And power factor
Wherein, in the step (A),
,
the number is a natural number and represents the total number of the outgoing lines of the transformer substation; and
and acquiring marketing load classification data in the power grid based on the power grid marketing service system.
Further, the active power of the outgoing line on the main transformer side of the transformer substation is calculated according to the voltage, the current and the power factor, and the calculation formula is as follows:
in the formula (I), the compound is shown in the specification,
for the main transformer side of the transformer substation
Active power of the strip outgoing line.
Further, determining a second load element configuration from the active power and the first load element configuration comprises:
regarding a first load element type in the first load element configuration as a second load element type in the second load element configuration, the expression is:
in the formula (I), the compound is shown in the specification,
is a second load element type, representing the load element type of the substation,
the first load element type represents the load element type of the outgoing line at the main transformer side of the transformer substation,
is the first of the first load element type
The type of the load member is selected such that,
,
the load element type is a natural number and represents the total number of the load element types in the outgoing line on the main transformer side of the transformer substation;
determining a second load element proportion in a second load element composition according to the active power and a first load element proportion in a first load element composition, wherein the first load element proportion is the proportion of each type of load element in a first load element type in all load elements of the outgoing line, the second load element proportion is the proportion of each type of load element in a second load element type in all load elements of the substation, and the calculation formula of the second load element proportion is as follows:
in the formula (I), the compound is shown in the specification,
for the first in the main transformer side outgoing line of the transformer substation
A first load member proportion of one load member type,
to the substation
A second load member proportion of the load member type,
for the main transformer side of the transformer substation
Active power of the strip outgoing line.
According to another aspect of the invention, the invention provides a system for determining the composition of a load element of a substation, the system comprising:
the data acquisition unit is used for acquiring the voltage, the current and the power factor of an outgoing line of a main transformer side of each transformer substation in the power grid and acquiring marketing load classification data in the power grid;
the power calculation unit is used for calculating active power of an outgoing line on the main transformer side of the transformer substation according to the voltage, the current and the power factor;
the load classification unit is used for determining the line load classification of the outgoing line at the main transformer side of the transformer substation according to the marketing load classification data and a pre-established load classification mapping table;
a first configuration unit for determining a first load component configuration from the line load classification and a pre-established load component configuration mapping table;
a second configuration unit for determining a second load element configuration from the active power and the first load element configuration.
Further, the system further comprises:
the system comprises a historical data unit, a data processing unit and a data processing unit, wherein the historical data unit is used for collecting marketing load classification historical data in an outgoing line at a main transformer side of a transformer substation as first historical data, and collecting load element types of the outgoing line at the main transformer side of the transformer substation in different load use seasons and the proportion of load elements in all load elements of the outgoing line as second historical data;
the first mapping table unit is used for establishing a load classification mapping table reflecting the corresponding relation between the marketing load classification of the outgoing line load of the main transformer side and the line load type according to the set line load type and the first historical data;
and the second mapping table unit is used for establishing a load element composition mapping table reflecting the corresponding relation between the load classification of the outgoing line at the main transformer side and the composition of the load elements in different load use seasons by adopting a deep learning algorithm based on the second historical data and the load classification in the load classification mapping table.
Further, the system further comprises:
the system updating unit is used for updating first historical data of the outgoing line on the main transformer side of the transformer substation and establishing an updated load classification mapping table reflecting the corresponding relation between marketing load classification and load types of the outgoing line load on the main transformer side based on the updated first historical data; and updating second historical data of the outgoing line at the main transformer side of the transformer substation, and establishing an updated load element composition mapping table reflecting the corresponding relation between the load classification of the outgoing line at the main transformer side and the composition of the load element according to the updated second historical data and the load classification in the updated classification mapping table.
Further, the data acquisition unit includes:
a first acquisition unit for acquiring the voltage of the outgoing line of the main transformer side of each transformer substation in the power grid based on the smart power grid dispatching system and the distribution automation system
Current of
And power factor
Wherein, in the step (A),
,
the number is a natural number and represents the total number of the outgoing lines of the transformer substation; and
and the second acquisition unit is used for acquiring marketing load classification data in the power grid based on the power grid marketing service system.
Further, the power calculation unit calculates the active power of the outgoing line at the main transformer side of the transformer substation according to the voltage, the current and the power factor, and the calculation formula is as follows:
in the formula (I), the compound is shown in the specification,
for the main transformer side of the transformer substation
Active power of the strip outgoing line.
Further, the second constituent unit includes:
a second type unit for regarding the first load member type in the first load member configuration as a second load member type in the second load member configuration, the expression of which is:
in the formula (I), the compound is shown in the specification,
is a second load element type, representing the load element type of the substation,
the first load element type represents the load element type of the outgoing line at the main transformer side of the transformer substation,
is the first of the first load element type
The type of the load member is selected such that,
,
the load element type is a natural number and represents the total number of the load element types in the outgoing line on the main transformer side of the transformer substation;
a second proportion unit, configured to determine a second load element proportion in a second load element configuration according to the active power and a first load element proportion in a first load element configuration, where the first load element proportion is a proportion of each type of load element in a first load element type in all load elements in the outgoing line, the second load element proportion is a proportion of each type of load element in a second load element type in all load elements in the substation, and a calculation formula of the second load element proportion is:
in the formula (I), the compound is shown in the specification,
for the first in the main transformer side outgoing line of the transformer substation
A first load member proportion of one load member type,
to the substation
A second load member proportion of the load member type,
for the main transformer side of the transformer substation
Active power of the strip outgoing line.
The method and the system for determining the composition of the load element of the transformer substation, which are provided by the technical scheme of the invention, are characterized in that a load classification mapping table reflecting the corresponding relation between marketing load classification of outgoing line load at a main transformer side and line load types is established by acquiring first historical data and second historical data in a power grid and based on set line load classification and the first historical data, and a load element composition mapping table reflecting the corresponding relation between the load classification of the outgoing line at the main transformer side and the composition of the load element in different load use seasons is established by adopting a deep learning algorithm based on the second historical data and the load classification in the load classification mapping table; and then, acquiring the voltage, the current and the power factor of a main transformer side outgoing line of the transformer substation in the power grid to determine the active power of the line, acquiring marketing load classification data in the power grid, and determining the composition of a load element of the transformer substation by combining the load classification mapping table and the load element composition mapping table. The method and the system for determining the composition of the load elements of the transformer substation establish a load classification mapping table reflecting marketing load classification data and line load types through the set line load types, then collect the information of the load elements (electric equipment) of each transformer substation based on a big data technology and adopt an artificial intelligence algorithm to carry out mining analysis, determine the load element types and proportions of outgoing lines of a main transformer side of the transformer substation, generate a load element composition mapping table, and on the basis, carry out intelligent matching on the composition of the load elements of the transformer substation by combining with real-time collected outgoing line real-time data of the main transformer side of the transformer substation, thereby providing accurate load element data for load modeling and improving the simulation accuracy of an electric power system.
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A more complete understanding of exemplary embodiments of the present invention may be had by reference to the following drawings in which:
fig. 1 is a flow chart of a method of determining the composition of a load element of a substation according to a preferred embodiment of the invention;
fig. 2 is a schematic configuration diagram of a system for determining the composition of load elements of a substation according to a preferred embodiment of the present invention.
Detailed Description
The exemplary embodiments of the present invention will now be described with reference to the accompanying drawings, however, the present invention may be embodied in many different forms and is not limited to the embodiments described herein, which are provided for complete and complete disclosure of the present invention and to fully convey the scope of the present invention to those skilled in the art. The terminology used in the exemplary embodiments illustrated in the accompanying drawings is not intended to be limiting of the invention. In the drawings, the same units/elements are denoted by the same reference numerals.
Unless otherwise defined, terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Further, it will be understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense.
Fig. 1 is a flow chart of a method of determining the composition of a load element of a substation according to a preferred embodiment of the invention. As shown in fig. 1, the method 100 of determining the configuration of load elements of a substation according to the preferred embodiment starts with step 101.
In step 101, marketing load classification historical data in an outgoing line of a main transformer side of a transformer substation is collected as first historical data, and load element types of the outgoing line of the main transformer side of the transformer substation in different load use seasons and the proportion of load elements occupying all load elements of the outgoing line are collected as second historical data.
In step 102, according to the set line load type and the first historical data, a load classification mapping table reflecting the corresponding relation between the marketing load classification of the outgoing line load of the main transformer side and the line load type is established.
Marketing load classification in power grid marketing service is complex, and the classification quantity is huge due to the fact that users are constructed from multiple angles of industries, power utilization purposes and user properties to which the users belong, and great difficulty is caused for load modeling. According to the method, loads are divided into three major categories, namely an industrial category, an agricultural category and a residential category, then specific load subtypes are divided for each major category, and automatic matching of marketing load classification and a load site outgoing line is achieved by establishing a load classification mapping table. Table 1 shows the excerpts of the load classification mapping table.
TABLE 1 load Classification mapping table excerpt
| Serial number | CODE_VALUE | CODE_NAME | CODE_LOAD_ID | LOAD_CODE_NAME |
| 1 | 35B1 | Industrial robot manufacturing | 1027 | Industrial load-manufacturing industry |
| 2 | 35B2 | Special work robot manufacture | 1027 | Industrial load-manufacturing industry |
| 3 | 35B3 | Additive manufacturing equipment manufacturing | 1027 | Industrial load-manufacturing industry |
| 4 | 35B9 | Other general equipment manufacturing industries not yet listed | 1027 | Industrial load-manufacturing industry |
| 5 | 3770 | Urban rail transit equipment manufacturing | 1027 | Industrial load-manufacturing industry |
| 6 | 3780 | Manufacturing of power-assisted vehicles | 1027 | Industrial load-manufacturing industry |
| 7 | 37A0 | Off-highway recreational vehicle and spare and accessory part manufacturing | 1027 | Industrial load-manufacturing industry |
| 8 | 37B0 | Manufacture of diving salvage and other unlawful transport equipment | 1027 | Industrial load-manufacturing industry |
| 9 | 3800 | Automobile manufacturing industry | 1027 | Industrial load-manufacturing industry |
| 10 | 3810 | Manufacturing of whole automobile | 1027 | Industrial load-manufacturing industry |
| 72 | 6561 | Charging and replacing service industry | 2013 | Load of general commercial residents |
| 73 | 6562 | Other automobiles, motorcycles, accessories, and fuel and other power sales | 2013 | Load of general commercial residents |
| 74 | 6830 | Non-monetary banking service | 2013 | Load of general commercial residents |
| 75 | 6840 | Bank financing service | 2013 | Load of general commercial residents |
| 76 | 6850 | Bank supervision service | 2013 | Load of general commercial residents |
| 77 | 6950 | Publicly recruiting securities investment funds | 2013 | Load of general commercial residents |
| 78 | 6960 | Non-overt recruitment of securities investment funds | 2013 | Load of general commercial residents |
| 79 | 6970 | Futures market service | 2013 | Load of general commercial residents |
| 80 | 6980 | Security futures supervision service | 2013 | Load of general commercial residents |
| 81 | 6990 | Capital investment service | 2013 | Load of general commercial residents |
| 163 | 300 | Electricity for agricultural production | 3001 | Agricultural loadElectric motor for irrigation |
| 165 | 301 | Agricultural irrigation and drainage | 3001 | Agricultural load-motor for irrigation |
| 166 | 302 | Electricity for agricultural irrigation and drainage in poverty county | 3001 | Agricultural load-motor for irrigation |
| 176 | A | Agriculture, forestry, animal husbandry and fishery | 3001 | Agricultural load-motor for irrigation |
| 177 | C | Manufacturing industry | 1027 | Industrial load-manufacturing industry |
| 178 | D | Electric power, gas and water production and supply industry | 1009 | Industrial load-electricity |
| 179 | E | Construction industry | 1028 | Industrial load-construction industry |
| 180 | F | Transportation, storage and postal industry | 1008 | Industrial load-transportation |
As shown in table 1, a large number of marketing load classifications are divided into the same load classifications according to the industry properties, so that the complexity of the load classifications is greatly reduced, and meanwhile, different situations under the same load classification are further subdivided, for example, industrial loads are subdivided into manufacturing industry, electric power, building industry, transportation and the like, so that the diversity of the loads during modeling is ensured, and the modeling accuracy is improved.
In step 103, based on the second historical data and the load classification in the load classification mapping table, a deep learning algorithm is adopted to establish a load element composition mapping table reflecting the corresponding relationship between the load classification of the outgoing line on the main transformer side and the composition of the load elements in different load use seasons. Table 2 shows the load element constituent map table excerpt.
Table 2 load element constituent mapping table excerpt
As shown in table 2, for the load classification into the load of the general commercial residents and the sub-classification into the electricity of the general commercial residents, the types of the electric devices and the occupation ratios of the electric devices are listed according to different seasons, so that the types and occupation ratios of the electric devices can be automatically matched according to the line load type of the load site.
In step 104, the voltage, current and power factor of the outgoing line of the main transformer side of each transformer substation in the power grid are collected, and marketing load classification data in the power grid are collected.
In step 105, calculating the active power of the outgoing line on the main transformer side of the transformer substation according to the voltage, the current and the power factor.
And step 106, determining the line load classification of the outgoing line at the main transformer side of the transformer substation according to the marketing load classification data and a pre-established load classification mapping table.
In step 107, a first load component configuration is determined from the line load classification and a pre-established load component configuration mapping table.
At step 108, a second load element configuration is determined based on the active power and the first load element configuration.
In step 109, updating first historical data of the outgoing line at the main transformer side of the transformer substation, and establishing an updated load classification mapping table reflecting the corresponding relation between the marketing load classification and the load type of the outgoing line load at the main transformer side based on the updated first historical data; and updating second historical data of the outgoing line at the main transformer side of the transformer substation, and establishing an updated load element composition mapping table reflecting the corresponding relation between the load classification of the outgoing line at the main transformer side and the composition of the load element according to the updated second historical data and the load classification in the updated classification mapping table.
The process of establishing a load model suitable for an actual power grid based on a survey statistic method is quite complicated, preliminary investigation is needed, the power grid range covered by load modeling work is determined, loads of load stations are generally investigated in the range, the load type of a main transformer side line of a transformer substation is determined by arranging general investigation data, a typical load station is selected, and detailed investigation is conducted on the load element structure of the line of the transformer substation. Through the establishment of the big data platform, the transformer substations of the power distribution networks can feed back the change of the load in time, so that the time-varying structure of the load elements can be ensured, the real load structure of the load stations can be reflected more accurately in time, and an accurate data source is provided for the online establishment of the load model.
Preferably, the acquiring the voltage, the current and the power factor of the outgoing line of the main transformer side of each transformer substation in the power grid, and the acquiring the marketing load classification data in the power grid include:
voltage of outgoing line of main transformer side of each transformer substation in power grid is collected based on intelligent power grid dispatching system and distribution automation system
Current of
And power factor
Wherein, in the step (A),
,
the number is a natural number and represents the total number of the outgoing lines of the transformer substation; and
and acquiring marketing load classification data in the power grid based on the power grid marketing service system.
Preferably, the active power of the outgoing line on the main transformer side of the transformer substation is calculated according to the voltage, the current and the power factor, and the calculation formula is as follows:
in the formula (I), the compound is shown in the specification,
for the main transformer side of the transformer substation
Active power of the strip outgoing line.
Preferably, determining the second load element configuration from the active power and the first load element configuration comprises:
regarding a first load element type in the first load element configuration as a second load element type in the second load element configuration, the expression is:
in the formula (I), the compound is shown in the specification,
is a second load element type, representing the load element type of the substation,
the first load element type represents the load element type of the outgoing line at the main transformer side of the transformer substation,
is the first of the first load element type
The type of the load member is selected such that,
,
the load element type is a natural number and represents the total number of the load element types in the outgoing line on the main transformer side of the transformer substation;
determining a second load element proportion in a second load element composition according to the active power and a first load element proportion in a first load element composition, wherein the first load element proportion is the proportion of each type of load element in a first load element type in all load elements of the outgoing line, the second load element proportion is the proportion of each type of load element in a second load element type in all load elements of the substation, and the calculation formula of the second load element proportion is as follows:
in the formula (I), the compound is shown in the specification,
for the first in the main transformer side outgoing line of the transformer substation
A first load member proportion of one load member type,
to the substation
A second load member proportion of the load member type,
for the main transformer side of the transformer substation
Active power of the strip outgoing line.
Fig. 2 is a schematic configuration diagram of a system for determining the composition of load elements of a substation according to a preferred embodiment of the present invention. As shown in fig. 2, a system 200 for determining the configuration of a load element of a substation according to the preferred embodiment includes:
and the historical data unit 201 is used for collecting marketing load classification historical data in the outgoing line of the main transformer side of the transformer substation as first historical data, and collecting load element types of the outgoing line of the main transformer side of the transformer substation in different load use seasons and the proportion of load elements in all load elements of the outgoing line as second historical data.
A first mapping table unit 202, configured to establish a load classification mapping table reflecting a correspondence between a marketing load classification of a line load on an outgoing line of a main transformer side and a line load type according to a set line load type and the first historical data;
and a second mapping table unit 203, configured to establish a load element composition mapping table reflecting a correspondence relationship between the load classification of the outgoing line on the main transformer side and the composition of the load element in different load use seasons by using a deep learning algorithm based on the second history data and the load classification in the load classification mapping table.
And the data acquisition unit 204 is used for acquiring the voltage, the current and the power factor of an outgoing line at the main transformer side of each transformer substation in the power grid and acquiring marketing load classification data in the power grid.
A power calculating unit 205, configured to calculate active power of the outgoing line on the main transformer side of the substation according to the voltage, the current and the power factor;
the load classification unit 206 is configured to determine a line load classification of the outgoing line on the main transformer side of the substation according to the marketing load classification data and a pre-established load classification mapping table;
a first construction unit 207 for determining a first load component construction from said line load classification and a pre-established load component composition mapping table.
A second composition unit 208 for determining a second load element composition from the active power and the first load element composition.
The system updating unit 209 is used for updating first historical data of the outgoing line on the main transformer side of the transformer substation, and establishing an updated load classification mapping table reflecting the corresponding relation between the marketing load classification and the load type of the outgoing line load on the main transformer side based on the updated first historical data; and updating second historical data of the outgoing line at the main transformer side of the transformer substation, and establishing an updated load element composition mapping table reflecting the corresponding relation between the load classification of the outgoing line at the main transformer side and the composition of the load element according to the updated second historical data and the load classification in the updated classification mapping table.
Preferably, the data acquisition unit 204 includes:
a first collecting unit 241 for collecting the voltage of the outgoing line of the main transformer side of each transformer substation in the power grid based on the smart grid dispatching system and the distribution automation system
Current of
And power factor
Wherein, in the step (A),
,
the number is a natural number and represents the total number of the outgoing lines of the transformer substation; and
and a second collecting unit 242, configured to collect marketing load classification data in the power grid based on the power grid marketing service system.
Preferably, the power calculating unit 205 calculates the active power of the outgoing line on the main transformer side of the transformer substation according to the voltage, the current and the power factor, and the calculation formula is as follows:
in the formula (I), the compound is shown in the specification,
for the main transformer side of the transformer substation
Strip lineActive power of the circuit.
Preferably, the second constituting unit 209 includes:
a second type unit 291 for regarding the first load element type in the first load element configuration as a second load element type in the second load element configuration, the expression of which is:
in the formula (I), the compound is shown in the specification,
is a second load element type, representing the load element type of the substation,
the first load element type represents the load element type of the outgoing line at the main transformer side of the transformer substation,
is the first of the first load element type
The type of the load member is selected such that,
,
the load element type is a natural number and represents the total number of the load element types in the outgoing line on the main transformer side of the transformer substation;
a second proportion unit 292, configured to determine a second load element proportion in a second load element configuration according to the active power and a first load element proportion in a first load element configuration, where the first load element proportion is a proportion of each type of load element in the first load element type in all load elements in the outgoing line, the second load element proportion is a proportion of each type of load element in the second load element type in all load elements in the substation, and a calculation formula of the second load element proportion is:
in the formula (I), the compound is shown in the specification,
for the first in the main transformer side outgoing line of the transformer substation
A first load member proportion of one load member type,
to the substation
A second load member proportion of the load member type,
for the main transformer side of the transformer substation
Active power of the strip outgoing line.
The invention has been described with reference to a few embodiments. However, other embodiments of the invention than the one disclosed above are equally possible within the scope of the invention, as would be apparent to a person skilled in the art from the appended patent claims.
Generally, all terms used in the claims are to be interpreted according to their ordinary meaning in the technical field, unless explicitly defined otherwise herein. All references to "a/an/the [ device, component, etc ]" are to be interpreted openly as referring to at least one instance of said device, component, etc., unless explicitly stated otherwise. The steps of any method disclosed herein do not have to be performed in the exact order disclosed, unless explicitly stated.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (12)
1. A method of determining the composition of a load element of a substation, characterized in that the method comprises:
acquiring voltage, current and power factors of outgoing lines of main transformer sides of all transformer substations in a power grid, and acquiring marketing load classification data in the power grid;
calculating the active power of the outgoing line at the main transformer side of the transformer substation according to the voltage, the current and the power factor;
determining the line load classification of the outgoing line at the main transformer side of the transformer substation according to the marketing load classification data and a pre-established load classification mapping table;
determining a first load component configuration according to the line load classification and a pre-established load component configuration mapping table;
a second load element configuration is determined based on the active power and the first load element configuration.
2. The method of claim 1, further comprising, prior to collecting the voltage, current and power factor of each substation main transformer side outgoing line in the power grid, and collecting marketing load classification data in the power grid:
the method comprises the steps of collecting marketing load classification historical data in an outgoing line of a main transformer side of a transformer substation as first historical data, and collecting load element types of the outgoing line of the main transformer side of the transformer substation in different load use seasons and the proportion of load elements in all load elements of the outgoing line as second historical data;
according to the set line load type and the first historical data, a load classification mapping table reflecting the corresponding relation between the marketing load classification of the outgoing line load of the main transformer side and the line load type is established;
and based on the second historical data and the load classification in the load classification mapping table, adopting a deep learning algorithm to establish a load element composition mapping table reflecting the corresponding relation between the load classification of the outgoing line at the main transformer side and the composition of the load elements in different load use seasons.
3. The method of claim 2, further comprising:
updating first historical data of a main transformer side outgoing line of the transformer substation, and establishing an updated load classification mapping table reflecting the corresponding relation between marketing load classification and load types of main transformer side outgoing line loads based on the updated first historical data; and updating second historical data of the outgoing line at the main transformer side of the transformer substation, and establishing an updated load element composition mapping table reflecting the corresponding relation between the load classification of the outgoing line at the main transformer side and the composition of the load element according to the updated second historical data and the load classification in the updated classification mapping table.
4. The method of claim 1, wherein the collecting voltage, current and power factor of each substation main transformer side outgoing line in the power grid and the collecting marketing load classification data in the power grid comprises:
voltage of outgoing line of main transformer side of each transformer substation in power grid is collected based on intelligent power grid dispatching system and distribution automation system
Current of
And power factor
Wherein, in the step (A),
,
the number is a natural number and represents the total number of the outgoing lines of the transformer substation; and
and acquiring marketing load classification data in the power grid based on the power grid marketing service system.
5. The method according to claim 4, wherein the active power of the outgoing line on the main transformer side of the transformer substation is calculated according to the voltage, the current and the power factor, and the calculation formula is as follows:
in the formula (I), the compound is shown in the specification,
for the main transformer side of the transformer substation
Active power of the strip outgoing line.
6. The method of claim 5, wherein determining a second load element configuration from the active power and a first load element configuration comprises:
regarding a first load element type in the first load element configuration as a second load element type in the second load element configuration, the expression is:
in the formula (I), the compound is shown in the specification,
is a second load element type, representing the load element type of the substation,
the first load element type represents the load element type of the outgoing line at the main transformer side of the transformer substation,
is the first of the first load element type
The type of the load member is selected such that,
,
the load element type is a natural number and represents the total number of the load element types in the outgoing line on the main transformer side of the transformer substation;
determining a second load element proportion in a second load element composition according to the active power and a first load element proportion in a first load element composition, wherein the first load element proportion is the proportion of each type of load element in a first load element type in all load elements of the outgoing line, the second load element proportion is the proportion of each type of load element in a second load element type in all load elements of the substation, and the calculation formula of the second load element proportion is as follows:
in the formula (I), the compound is shown in the specification,
for the first in the main transformer side outgoing line of the transformer substation
A first load member proportion of one load member type,
to the substation
A second load member proportion of the load member type,
for the main transformer side of the transformer substation
Active power of the strip outgoing line.
7. A system for determining the composition of a load element of a substation, characterized in that the system comprises:
the data acquisition unit is used for acquiring the voltage, the current and the power factor of an outgoing line of a main transformer side of each transformer substation in the power grid and acquiring marketing load classification data in the power grid;
the power calculation unit is used for calculating active power of an outgoing line on the main transformer side of the transformer substation according to the voltage, the current and the power factor;
the load classification unit is used for determining the line load classification of the outgoing line at the main transformer side of the transformer substation according to the marketing load classification data and a pre-established load classification mapping table;
a first configuration unit for determining a first load component configuration from the line load classification and a pre-established load component configuration mapping table;
a second configuration unit for determining a second load element configuration from the active power and the first load element configuration.
8. The system of claim 7, further comprising:
the system comprises a historical data unit, a data processing unit and a data processing unit, wherein the historical data unit is used for collecting marketing load classification historical data in an outgoing line at a main transformer side of a transformer substation as first historical data, and collecting load element types of the outgoing line at the main transformer side of the transformer substation in different load use seasons and the proportion of load elements in all load elements of the outgoing line as second historical data;
the first mapping table unit is used for establishing a load classification mapping table reflecting the corresponding relation between the marketing load classification of the outgoing line load of the main transformer side and the line load type according to the set line load type and the first historical data;
and the second mapping table unit is used for establishing a load element composition mapping table reflecting the corresponding relation between the load classification of the outgoing line at the main transformer side and the composition of the load elements in different load use seasons by adopting a deep learning algorithm based on the second historical data and the load classification in the load classification mapping table.
9. The system of claim 8, further comprising:
the system updating unit is used for updating first historical data of the outgoing line on the main transformer side of the transformer substation and establishing an updated load classification mapping table reflecting the corresponding relation between marketing load classification and load types of the outgoing line load on the main transformer side based on the updated first historical data; and updating second historical data of the outgoing line at the main transformer side of the transformer substation, and establishing an updated load element composition mapping table reflecting the corresponding relation between the load classification of the outgoing line at the main transformer side and the composition of the load element according to the updated second historical data and the load classification in the updated classification mapping table.
10. The system of claim 7, wherein the data acquisition unit comprises:
a first acquisition unit for acquiring the voltage of the outgoing line of the main transformer side of each transformer substation in the power grid based on the smart power grid dispatching system and the distribution automation system
Current of
And power factor
Wherein, in the step (A),
,
the number is a natural number and represents the total number of the outgoing lines of the transformer substation; and
and the second acquisition unit is used for acquiring marketing load classification data in the power grid based on the power grid marketing service system.
11. The system according to claim 10, wherein the power calculating unit calculates the active power of the outgoing line on the main transformer side of the transformer substation according to the voltage, the current and the power factor, and the calculation formula is as follows:
in the formula (I), the compound is shown in the specification,
for the main transformer side of the transformer substation
Active power of the strip outgoing line.
12. The system according to claim 11, wherein the second constituent unit includes:
a second type unit for regarding the first load member type in the first load member configuration as a second load member type in the second load member configuration, the expression of which is:
in the formula (I), the compound is shown in the specification,
is a second load element type, representing the load element type of the substation,
the first load element type represents the load element type of the outgoing line at the main transformer side of the transformer substation,
is the first of the first load element type
The type of the load member is selected such that,
,
the load element type is a natural number and represents the total number of the load element types in the outgoing line on the main transformer side of the transformer substation;
a second proportion unit, configured to determine a second load element proportion in a second load element configuration according to the active power and a first load element proportion in a first load element configuration, where the first load element proportion is a proportion of each type of load element in a first load element type in all load elements in the outgoing line, the second load element proportion is a proportion of each type of load element in a second load element type in all load elements in the substation, and a calculation formula of the second load element proportion is:
in the formula (I), the compound is shown in the specification,
for the first in the main transformer side outgoing line of the transformer substation
A first load member proportion of one load member type,
to the substation
A second load member proportion of the load member type,
for the main transformer side of the transformer substation
Active power of the strip outgoing line.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113987848A (en) * | 2021-12-28 | 2022-01-28 | 中国电力科学研究院有限公司 | Intelligent load composition identification and accurate load modeling method and system |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101777765A (en) * | 2010-01-27 | 2010-07-14 | 中国电力科学研究院 | On-line load simulation method of power system |
| CN103177188A (en) * | 2013-04-02 | 2013-06-26 | 东南大学 | Electric system load dynamic characteristic classifying method based on characteristic mapping |
| CN105429131A (en) * | 2015-12-07 | 2016-03-23 | 中国电力科学研究院 | Load model building method of considering load frequency characteristics |
| CN110287762A (en) * | 2019-04-03 | 2019-09-27 | 江苏林洋能源股份有限公司 | A kind of non-intrusion type load discrimination method and device based on data mining technology |
| CN110458314A (en) * | 2019-03-26 | 2019-11-15 | 国网辽宁省电力有限公司 | A kind of load prediction data decomposition method for power grid Tidal forecasting a few days ago |
| CN110707692A (en) * | 2019-10-16 | 2020-01-17 | 济南荣耀合创电力科技有限公司 | Online load analysis and modeling system and method for power system |
| CN111539657A (en) * | 2020-05-30 | 2020-08-14 | 国网湖南省电力有限公司 | Typical electricity consumption industry load characteristic classification and synthesis method combined with user daily electricity consumption curve |
| US20200280185A1 (en) * | 2014-01-24 | 2020-09-03 | Utopus Insights, Inc. | Generating electric substation load transfer control parameters |
| CN111898694A (en) * | 2020-08-07 | 2020-11-06 | 广东电网有限责任公司计量中心 | Non-invasive load identification method and device based on random tree classification |
-
2020
- 2020-12-24 CN CN202011543254.XA patent/CN112288598A/en active Pending
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101777765A (en) * | 2010-01-27 | 2010-07-14 | 中国电力科学研究院 | On-line load simulation method of power system |
| CN103177188A (en) * | 2013-04-02 | 2013-06-26 | 东南大学 | Electric system load dynamic characteristic classifying method based on characteristic mapping |
| US20200280185A1 (en) * | 2014-01-24 | 2020-09-03 | Utopus Insights, Inc. | Generating electric substation load transfer control parameters |
| CN105429131A (en) * | 2015-12-07 | 2016-03-23 | 中国电力科学研究院 | Load model building method of considering load frequency characteristics |
| CN110458314A (en) * | 2019-03-26 | 2019-11-15 | 国网辽宁省电力有限公司 | A kind of load prediction data decomposition method for power grid Tidal forecasting a few days ago |
| CN110287762A (en) * | 2019-04-03 | 2019-09-27 | 江苏林洋能源股份有限公司 | A kind of non-intrusion type load discrimination method and device based on data mining technology |
| CN110707692A (en) * | 2019-10-16 | 2020-01-17 | 济南荣耀合创电力科技有限公司 | Online load analysis and modeling system and method for power system |
| CN111539657A (en) * | 2020-05-30 | 2020-08-14 | 国网湖南省电力有限公司 | Typical electricity consumption industry load characteristic classification and synthesis method combined with user daily electricity consumption curve |
| CN111898694A (en) * | 2020-08-07 | 2020-11-06 | 广东电网有限责任公司计量中心 | Non-invasive load identification method and device based on random tree classification |
Non-Patent Citations (1)
| Title |
|---|
| 白勇涛: "基于云计算平台的统计综合法负荷建模的研究", 《中国优秀硕士学位论文全文数据库》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113987848A (en) * | 2021-12-28 | 2022-01-28 | 中国电力科学研究院有限公司 | Intelligent load composition identification and accurate load modeling method and system |
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