CN114971388B - Power distribution network line loss fine management system based on big data - Google Patents
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Abstract
The invention provides a power distribution network line loss refined management system based on big data, which comprises the following steps: the management server is internally provided with a plurality of distributed management modules; the system comprises a configuration module, a line loss estimation module, an ageing line loss estimation module, a line loss combination module and an artificial intelligent system, wherein the artificial intelligent system is used for carrying out iterative training on the basis of line incoming current components and line outgoing current components of a line incoming position and a line outgoing position of key equipment nodes acquired by a sensing device, so as to obtain a line loss result caused by the key equipment nodes, and carrying out difference value calculation on the line loss result and the total amount of line loss lower limit and the total amount of line loss upper limit respectively so as to revise loss parameters of each key equipment node.
Description
Technical Field
The invention relates to the technical field of high-voltage line damage management, in particular to a power distribution network line damage refined management system based on big data.
Background
The existing high-voltage line loss basically shows three aspects, namely fixed loss, variable loss and line loss, and the general fixed loss is the basic loss caused by the operation of equipment, such as iron loss of a transformer and medium loss of a line. The fluctuation loss increases with the increase of the load, and is mainly represented by copper loss of equipment such as transformers and voltage regulators. Line losses are mainly caused by grid wiring, such as power transmission distances, aging between various devices, and the like.
The fixed loss is generally better calculated, and the change loss and the line loss have certain difficulty in specific calculation, for example, in daily maintenance, a certain key device may be updated, the change loss and the line loss brought by the key device are obviously lower than those before the key device is updated, and the place where the line loss is relatively large in the line cannot be known.
Disclosure of Invention
In view of the above, the main purpose of the present invention is to provide a power distribution network line loss refinement management system based on big data.
The technical scheme adopted by the invention is as follows:
a power distribution network line loss refinement management system based on big data comprises:
the management server is internally provided with a plurality of distributed management modules;
the configuration module is used for configuring all key equipment nodes on the branch line into each distributed management module according to equipment node attributes, and configuring loss parameters of each key equipment node and loss parameters of the branch line;
the line loss estimation module is provided with a plurality of line loss estimation units, and each line loss estimation unit is matched with a corresponding key equipment node according to the equipment node attribute; the line loss estimation unit is used for estimating the lower loss limit and the upper loss limit of the corresponding key equipment nodes based on the loss parameters of the corresponding key equipment nodes;
the aging line loss estimation module records the operation years and theoretical aging parameters of the key equipment nodes, and estimates an aging loss upper limit component and an aging loss lower limit component based on the operation years and the theoretical aging parameters of the key equipment nodes;
the line loss combination module is used for respectively combining the aging loss upper limit component and the aging loss lower limit component with the loss lower limit and the loss upper limit so as to obtain the total line loss lower limit and the total line loss upper limit of the key equipment node;
the artificial intelligence system is used for carrying out iterative training on the basis of the incoming current components and the outgoing current components of the incoming positions and the outgoing positions of the key equipment nodes acquired by the sensing device, so as to acquire line loss results caused by the key equipment nodes, and carrying out difference calculation on the line loss results and the total amount of the lower limit and the total amount of the upper limit of the line loss respectively so as to revise the loss parameters of each key equipment node.
Further, on the same branch line, at least one group of the same key equipment nodes are provided with sensing devices, each sensing device is provided with two synchronous receiving rings, and the two receiving rings penetrate through the wire inlet position and the wire outlet position of the same key equipment nodes and are used for respectively collecting the wire inlet current components and the wire outlet current components of the wire inlet position and the wire outlet position; and transmitting the obtained incoming line current component and outgoing line current component to the management server through a communication module.
Further, the configuration module has:
the first acquisition unit is used for acquiring the identification of each distributed management module;
the identification unit is used for identifying the identification, linking a plurality of distributed management modules according to the identification to form a distributed matrix based on the identification, and using at least one distributed management module in the same matrix module for representing the same branch line;
the dividing unit is used for dividing the branch line into branch line segments with corresponding numbers according to the number of the distributed management modules;
a second acquisition unit acquiring key equipment nodes on each branch line segment,
and the configuration unit is used for configuring all the key equipment nodes on the branch line segment into each distributed management module according to the equipment node attribute, and configuring the loss parameter of each key equipment node and the loss parameter of the branch line segment.
Further, the configuration method of the configuration module is as follows:
1) Acquiring the identification of the distributed management modules, forming a plurality of distributed management modules into a distributed matrix based on the identification, wherein the distributed management modules in the same matrix module are used for representing the same branch line;
2) Dividing branch lines into corresponding branch segments according to the number of the distributed management modules, and acquiring key equipment nodes on each branch segment;
3) And configuring all the key equipment nodes on the branch line segment into each distributed management module according to the equipment node attribute, and configuring the loss parameter of each key equipment node and the loss parameter of the branch line segment.
Further, the device node attribute comprises the type of the device and the code formed by the operation years.
Further, the device node attributes are established by:
acquiring all key equipment nodes on the branch line segment, and constructing a type ledger of the key equipment nodes, wherein the type ledger comprises types and position data of all equipment positioned on the branch line segment;
establishing a main identifier for representing each key equipment node based on a type ledger call template library, establishing a plurality of equipment templates based on the type ledger, wherein each equipment template corresponds to one key equipment node, and corresponding the equipment templates to the main identifier;
constructing a plurality of sub-identifiers linked with the main identifier according to the main identifier, wherein the sub-identifiers are used for representing the operation years of the corresponding key equipment nodes;
and inputting the main identifier and the sub-identifiers linked with the main identifier into a coding unit to construct codes corresponding to the key equipment nodes under the loading coding rule, and reflecting the equipment node attributes by using the codes.
Further, when any one key equipment node is updated on the branch line segment, acquiring the equipment node attribute of the key equipment node before updating; and obtaining the position data by inverse solution, wherein the main identifier corresponding to the updated position data is unchanged, and the sub identifier linked with the main identifier is changed correspondingly.
Further, the aging line loss estimation module is connected with an interaction interface, and maintenance data of the corresponding key equipment node is loaded from the interaction interface so as to correspondingly modify the theoretical aging parameters.
The method comprises the steps of dividing a high-voltage transmission line into a plurality of branch lines with approximately the same length, dividing the branch lines into a plurality of branch segments, configuring all key equipment nodes on the branch segments into each distributed management module according to equipment node attributes, and configuring loss parameters of each key equipment node and loss parameters of the branch segments in the distributed management modules. Estimating the lower loss limit and the upper loss limit of the corresponding key equipment nodes based on the loss parameters of the corresponding key equipment nodes through a line loss estimation unit; estimating an aging loss upper limit component and an aging loss lower limit component based on the operation years and theoretical aging parameters of the key equipment nodes by an aging line loss estimation module; and combining the aging loss upper limit component and the aging loss lower limit component with the loss lower limit and the loss upper limit respectively to obtain the total line loss lower limit and the total line loss upper limit of the key equipment node.
In the above, the loss parameters of the key equipment nodes are theoretical loss parameters set on the basis of the type of the equipment and the equipment, and the theoretical loss parameters and the actual loss parameters have larger differences along with the influence of variables such as time, external environment, maintenance and the like, therefore, the application is provided with a sensing device at least one group of key equipment nodes of the same type (the codes are consistent, the codes are consistent and reflect the conditions such as the type and the running time are consistent) on the same branch line, the sensing device is provided with two synchronous receiving rings, and the two receiving rings penetrate through the incoming line position and the outgoing line position of the same key equipment node and are used for respectively collecting the incoming line current component and the outgoing line current component of the incoming line position and the outgoing line position; and obtaining loss values of the key equipment nodes based on the difference between the incoming line current component and the outgoing line current component, and respectively carrying out difference calculation with the total line loss lower limit and the total line loss upper limit based on the loss values so as to revise the loss parameters of each key equipment node.
Drawings
The following drawings are illustrative of the invention and are not intended to limit the scope of the invention, in which:
FIG. 1 is a system configuration diagram of the present invention;
FIG. 2 is a schematic diagram of a system configuration module of the present invention;
FIG. 3 is a flow chart of a configuration method of a configuration module in the present invention;
fig. 4 is a flowchart of a method for establishing a device node attribute in the present invention.
Detailed Description
The present invention will be further described in detail with reference to the following specific examples, which are given by way of illustration, in order to make the objects, technical solutions, design methods and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Referring to fig. 1 to 4, the present invention provides a power distribution network line loss refinement management system based on big data, including:
the management server is internally provided with a plurality of distributed management modules;
the configuration module is used for configuring all key equipment nodes on the branch line into each distributed management module according to equipment node attributes, and configuring loss parameters of each key equipment node and loss parameters of the branch line;
the line loss estimation module is provided with a plurality of line loss estimation units, and each line loss estimation unit is matched with a corresponding key equipment node according to the equipment node attribute; the line loss estimation unit is used for estimating the lower loss limit and the upper loss limit of the corresponding key equipment nodes based on the loss parameters of the corresponding key equipment nodes;
the aging line loss estimation module records the operation years and theoretical aging parameters of the key equipment nodes, and estimates an aging loss upper limit component and an aging loss lower limit component based on the operation years and the theoretical aging parameters of the key equipment nodes;
the line loss combination module is used for respectively combining the aging loss upper limit component and the aging loss lower limit component with the loss lower limit and the loss upper limit so as to obtain the total line loss lower limit and the total line loss upper limit of the key equipment node;
the line loss of the branch line is directly obtained by the loss parameter of the branch line;
the artificial intelligence system is used for carrying out iterative training on the basis of the incoming current components and the outgoing current components of the incoming positions and the outgoing positions of the key equipment nodes acquired by the sensing device, so as to acquire line loss results caused by the key equipment nodes, and carrying out difference calculation on the line loss results and the total amount of the lower limit and the total amount of the upper limit of the line loss respectively so as to revise the loss parameters of each key equipment node.
Further, on the same branch line, at least one group of the same key equipment nodes are provided with sensing devices, each sensing device is provided with two synchronous receiving rings, and the two receiving rings penetrate through the wire inlet position and the wire outlet position of the same key equipment nodes and are used for respectively collecting the wire inlet current components and the wire outlet current components of the wire inlet position and the wire outlet position; and transmitting the obtained incoming line current component and outgoing line current component to the management server through a communication module.
Further, the configuration module has:
the first acquisition unit is used for acquiring the identification of each distributed management module;
the identification unit is used for identifying the identification, linking a plurality of distributed management modules according to the identification to form a distributed matrix based on the identification, and using at least one distributed management module in the same matrix module for representing the same branch line;
the dividing unit is used for dividing the branch line into branch line segments with corresponding numbers according to the number of the distributed management modules;
a second acquisition unit acquiring key equipment nodes on each branch line segment,
and the configuration unit is used for configuring all the key equipment nodes on the branch line segment into each distributed management module according to the equipment node attribute, and configuring the loss parameter of each key equipment node and the loss parameter of the branch line segment.
Further, the configuration method of the configuration module is as follows:
1) Acquiring the identification of the distributed management modules, forming a plurality of distributed management modules into a distributed matrix based on the identification, wherein the distributed management modules in the same matrix module are used for representing the same branch line;
2) Dividing branch lines into corresponding branch segments according to the number of the distributed management modules, and acquiring key equipment nodes on each branch segment;
3) And configuring all the key equipment nodes on the branch line segment into each distributed management module according to the equipment node attribute, and configuring the loss parameter of each key equipment node and the loss parameter of the branch line segment.
Further, the device node attribute comprises the type of the device and the code formed by the operation years.
Further, the device node attributes are established by:
acquiring all key equipment nodes on the branch line segment, and constructing a type ledger of the key equipment nodes, wherein the type ledger comprises types and position data of all equipment positioned on the branch line segment;
establishing a main identifier for representing each key equipment node based on a type ledger call template library, establishing a plurality of equipment templates based on the type ledger, wherein each equipment template corresponds to one key equipment node, and corresponding the equipment templates to the main identifier;
constructing a plurality of sub-identifiers linked with the main identifier according to the main identifier, wherein the sub-identifiers are used for representing the operation years of the corresponding key equipment nodes;
and inputting the main identifier and the sub-identifiers linked with the main identifier into a coding unit to construct codes corresponding to the key equipment nodes under the loading coding rule, and reflecting the equipment node attributes by using the codes.
Further, when any one key equipment node is updated on the branch line segment, acquiring the equipment node attribute of the key equipment node before updating; and obtaining the position data by inverse solution, wherein the main identifier corresponding to the updated position data is unchanged, and the sub identifier linked with the main identifier is changed correspondingly.
In some embodiments, in order to reduce the line loss statistical error, the aging line loss estimation module is connected with an interaction interface, and maintenance data of the corresponding key equipment node is loaded from the interaction interface to correspondingly modify the theoretical aging parameter.
The method comprises the steps of dividing a high-voltage transmission line into a plurality of branch lines with approximately the same length, dividing the branch lines into a plurality of branch segments, configuring all key equipment nodes on the branch segments into each distributed management module according to equipment node attributes, and configuring loss parameters of each key equipment node and loss parameters of the branch segments in the distributed management modules. Estimating the lower loss limit and the upper loss limit of the corresponding key equipment nodes based on the loss parameters of the corresponding key equipment nodes through a line loss estimation unit; estimating an aging loss upper limit component and an aging loss lower limit component based on the operation years and theoretical aging parameters of the key equipment nodes by an aging line loss estimation module; and combining the aging loss upper limit component and the aging loss lower limit component with the loss lower limit and the loss upper limit respectively to obtain the total line loss lower limit and the total line loss upper limit of the key equipment node.
In the above, the loss parameters of the key equipment nodes are theoretical loss parameters set on the basis of the type of the equipment and the equipment, and the theoretical loss parameters and the actual loss parameters have larger differences along with the influence of variables such as time, external environment, maintenance and the like, therefore, the application is provided with a sensing device at least one group of key equipment nodes of the same type (the codes are consistent, the codes are consistent and reflect the conditions such as the type and the running time are consistent) on the same branch line, the sensing device is provided with two synchronous receiving rings, and the two receiving rings penetrate through the incoming line position and the outgoing line position of the same key equipment node and are used for respectively collecting the incoming line current component and the outgoing line current component of the incoming line position and the outgoing line position; and obtaining loss values of the key equipment nodes based on the difference between the incoming line current component and the outgoing line current component, and respectively carrying out difference calculation with the total line loss lower limit and the total line loss upper limit based on the loss values so as to revise the loss parameters of each key equipment node.
The invention can also achieve the purpose of inquiring the loss on each branch line or branch line segment based on the correspondence of the management server, and particularly, the distributed management modules are used for representing the same branch line by acquiring the identifiers of the distributed management modules and forming a distributed matrix based on the identifiers; the branch lines are divided into corresponding branch segments according to the number of the distributed management modules, so that each branch line can be inquired through a unique identifier, and the corresponding branch segments can be inquired according to the setting of the distributed management modules.
In addition to the above, the present application may further implement query for a specific loss of a certain key device node, and based on the above description, configure all the key device nodes on the branch segment to each of the distributed management modules according to the device node attribute, and configure a loss parameter of each key device node and a loss parameter of the branch segment. In order to better determine the change loss and the line loss of each key equipment node, each key equipment node is further encoded so as to carry out fine management, and the running state is considered in the encoding process. In order to enable the codes to have consistency and uniqueness, the application provides a building mode of equipment node attributes (directly obtained by the codes), specifically, all key equipment nodes on the branch line segments are obtained, and a type ledger of the key equipment nodes is built, wherein the type ledger comprises types and position data of all equipment positioned on the branch line segments; establishing a main identifier for representing each key equipment node based on a type ledger call template library, establishing a plurality of equipment templates based on the type ledger, wherein each equipment template corresponds to one key equipment node, and corresponding the equipment templates to the main identifier; constructing a plurality of sub-identifiers linked with the main identifier according to the main identifier, wherein the sub-identifiers are used for representing the operation years of the corresponding key equipment nodes; and inputting the main identifier and the sub-identifiers linked with the main identifier into a coding unit to construct codes corresponding to the key equipment nodes under the loading coding rule, and reflecting the equipment node attributes by using the codes. When any one key equipment node is updated on the branch line segment, acquiring equipment node attributes of the key equipment node before updating; and obtaining the position data by inverse solution, wherein the main identifier corresponding to the updated position data is unchanged, and the sub identifier linked with the main identifier is changed correspondingly.
According to the invention, the branch line can be taken as one device in branch line eliminating equipment, so that current data of an end point (without any data in the middle and with the length generally larger than 1000 m) between two points of the branch line with a certain length can be acquired through the sensing device, the actual line loss condition is acquired, and the loss parameters of the branch line are revised based on the current data and the actual line loss condition.
The foregoing description of embodiments of the invention has been presented for purposes of illustration and description, and is not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the various embodiments described. The terminology used herein was chosen in order to best explain the principles of the embodiments, the practical application, or the technical improvements in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (8)
1. A power distribution network line loss fine management system based on big data is characterized by comprising:
the management server is internally provided with a plurality of distributed management modules;
the configuration module is used for configuring all key equipment nodes on the branch line into each distributed management module according to equipment node attributes, and configuring loss parameters of each key equipment node and loss parameters of the branch line;
the line loss estimation module is provided with a plurality of line loss estimation units, and each line loss estimation unit is matched with a corresponding key equipment node according to the equipment node attribute; the line loss estimation unit is used for estimating the lower loss limit and the upper loss limit of the corresponding key equipment nodes based on the loss parameters of the corresponding key equipment nodes;
the aging line loss estimation module records the operation years and theoretical aging parameters of the key equipment nodes, and estimates an aging loss upper limit component and an aging loss lower limit component based on the operation years and the theoretical aging parameters of the key equipment nodes;
the line loss combination module is used for respectively combining the aging loss upper limit component and the aging loss lower limit component with the loss lower limit and the loss upper limit so as to obtain the total line loss lower limit and the total line loss upper limit of the key equipment node;
the artificial intelligence system is used for carrying out iterative training on the basis of the incoming current components and the outgoing current components of the incoming positions and the outgoing positions of the key equipment nodes acquired by the sensing device, so as to acquire line loss results caused by the key equipment nodes, and carrying out difference calculation on the line loss results and the total amount of the lower limit and the total amount of the upper limit of the line loss respectively so as to revise the loss parameters of each key equipment node.
2. The line loss refinement management system of a distribution network based on big data according to claim 1, wherein on the same branch line, at least one group of same key equipment nodes are provided with a sensing device, the sensing device is provided with two synchronous receiving rings, and the two receiving rings penetrate through a line inlet position and a line outlet position of the same key equipment nodes and are used for respectively collecting line inlet current components and line outlet current components of the line inlet position and the line outlet position; and transmitting the obtained incoming line current component and outgoing line current component to the management server through a communication module.
3. The big data based power distribution network line loss refinement management system of claim 1, wherein the configuration module has:
the first acquisition unit is used for acquiring the identification of each distributed management module;
the identification unit is used for identifying the identification, linking a plurality of distributed management modules according to the identification to form a distributed matrix based on the identification, and using at least one distributed management module in the same matrix module for representing the same branch line;
the dividing unit is used for dividing the branch line into branch line segments with corresponding numbers according to the number of the distributed management modules;
a second acquisition unit acquiring key equipment nodes on each branch line segment,
and the configuration unit is used for configuring all the key equipment nodes on the branch line segment into each distributed management module according to the equipment node attribute, and configuring the loss parameter of each key equipment node and the loss parameter of the branch line segment.
4. The line loss refinement management system for a power distribution network based on big data according to claim 3, wherein the configuration method of the configuration module is as follows:
1) Acquiring the identification of the distributed management modules, forming a plurality of distributed management modules into a distributed matrix based on the identification, wherein the distributed management modules in the same matrix module are used for representing the same branch line;
2) Dividing branch lines into corresponding branch segments according to the number of the distributed management modules, and acquiring key equipment nodes on each branch segment;
3) And configuring all the key equipment nodes on the branch line segment into each distributed management module according to the equipment node attribute, and configuring the loss parameter of each key equipment node and the loss parameter of the branch line segment.
5. The system for fine management of line loss of distribution network based on big data according to claim 4, wherein the equipment node attribute comprises a code composed of type and operation age of equipment.
6. The big data based power distribution network line loss refinement management system of claim 5, wherein the device node attributes are established by:
acquiring all key equipment nodes on the branch line segment, and constructing a type ledger of the key equipment nodes, wherein the type ledger comprises types and position data of all equipment positioned on the branch line segment;
establishing a main identifier for representing each key equipment node based on a type ledger call template library, establishing a plurality of equipment templates based on the type ledger, wherein each equipment template corresponds to one key equipment node, and corresponding the equipment templates to the main identifier;
constructing a plurality of sub-identifiers linked with the main identifier according to the main identifier, wherein the sub-identifiers are used for representing the operation years of the corresponding key equipment nodes;
and inputting the main identifier and the sub-identifiers linked with the main identifier into a coding unit to construct codes corresponding to the key equipment nodes under the loading coding rule, and reflecting the equipment node attributes by using the codes.
7. The line loss refinement management system of a distribution network based on big data according to claim 5, wherein when any one of the key device nodes is updated on the branch line segment, the device node attribute of the key device node before the update is acquired; and obtaining the position data by inverse solution, wherein the main identifier corresponding to the updated position data is unchanged, and the sub identifier linked with the main identifier is changed correspondingly.
8. The line loss refinement management system of a distribution network based on big data according to claim 1, wherein the aging line loss estimation module is connected to an interaction interface, and maintenance data of a corresponding key device node is loaded from the interaction interface to correspondingly modify theoretical aging parameters.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111178657A (en) * | 2019-08-21 | 2020-05-19 | 中民新能投资集团有限公司 | AC-DC hybrid distributed system electric loss and energy efficiency evaluation method based on star |
| CN111398885A (en) * | 2020-03-27 | 2020-07-10 | 天津大学 | Intelligent electric meter operation error monitoring method combining line loss analysis |
| CN113805138A (en) * | 2021-10-18 | 2021-12-17 | 国网湖南省电力有限公司 | Intelligent electric meter error estimation method and device based on parameter directed traversal |
| CN113991652A (en) * | 2021-10-27 | 2022-01-28 | 浙江大学 | Data-driven multi-output calculation method for short-circuit current of IIDG-containing power distribution network |
| CN114358566A (en) * | 2021-12-29 | 2022-04-15 | 泰豪软件股份有限公司 | Line loss management method and device based on topology rectification, storage medium and equipment |
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111178657A (en) * | 2019-08-21 | 2020-05-19 | 中民新能投资集团有限公司 | AC-DC hybrid distributed system electric loss and energy efficiency evaluation method based on star |
| CN111398885A (en) * | 2020-03-27 | 2020-07-10 | 天津大学 | Intelligent electric meter operation error monitoring method combining line loss analysis |
| CN113805138A (en) * | 2021-10-18 | 2021-12-17 | 国网湖南省电力有限公司 | Intelligent electric meter error estimation method and device based on parameter directed traversal |
| CN113991652A (en) * | 2021-10-27 | 2022-01-28 | 浙江大学 | Data-driven multi-output calculation method for short-circuit current of IIDG-containing power distribution network |
| CN114358566A (en) * | 2021-12-29 | 2022-04-15 | 泰豪软件股份有限公司 | Line loss management method and device based on topology rectification, storage medium and equipment |
Non-Patent Citations (1)
| Title |
|---|
| 配电网线损的精细化管理;李姝等;《供用电》;第25卷(第5期);第[65]-[68]页 * |
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