CN111582717A - Active power distribution network planning method based on big data technology - Google Patents
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Abstract
The invention discloses an active power distribution network planning method based on a big data technology, and belongs to the field of intelligent power grid planning. Fusing the initial database and the detection data of the power distribution network, planning data fusion modes in different scenes, and planning the positions and the scales of nodes in the active power distribution network by using the initial database; fusing various indexes and an electronic map by adopting a mature technical framework on the service index data, the geographic space data and the network topology data of the active power distribution network, and integrating the fused active power distribution network data; establishing the fused model and solving; scheduling and configuring the known data, and establishing a data analysis database; and establishing an effective index system, and carrying out comprehensive detection and abnormal motion detection. According to the invention, the active power distribution network is combined with big data, so that sound data information is collected and the information is in the same latitude; the established effective index system realizes comprehensive detection and abnormal motion detection.
Description
Technical Field
The invention belongs to the field of intelligent power distribution networks, and particularly relates to an active power distribution network planning method based on a big data technology.
Background
The distribution network is the most direct and key link for realizing the supply and consumption of electric energy, and has important significance on the safety, reliability and economy of power supply. The active power distribution network is used as one of power distribution network power distribution modes, adopts a mode of actively managing a distributed power supply, energy storage equipment and client bidirectional loads, and has a flexible topological structure. The power distribution network planning is a key for solving various operation problems of the power distribution network, an intelligent auxiliary decision-making platform for power distribution network planning based on big data is constructed under the guidance of big data wave, and mass data value is fully exerted and lean and intelligent power distribution network planning management is realized for the construction of an informationized and intelligent power distribution network planning system.
Due to the characteristics of various types, large quantity and wide distribution of the power distribution network, the data in the power distribution network structurally comprises structured data and unstructured data, only few pieces of information in a large amount of data can reflect available information in the operation condition of equipment, and in addition, the power distribution network does not operate constantly, so that various generated index parameters, the equipment, network topology and other data are changed in real time.
In order to meet the ever-increasing power requirements and the rapidly-increasing feeder scale in the existing power distribution network planning, in the process of planning the power distribution network, because the data to be acquired is huge, the information processing effect of the power grid voltage class configuration data category at the fixed acquisition point in the power grid system is poor, and in the acquisition process of the power grid configuration data, due to the fact that the acquisition point scales are different, the planning sections of the power grid information are different, the acquired data information is prone to be imperfect, and the system has the phenomena of errors, mistransmission, omission and the like in the process of processing the configuration data.
Disclosure of Invention
The purpose of the invention is as follows: the active power distribution network planning method based on the big data technology is provided, and the problems in the prior art are solved.
The technical scheme is as follows: an active power distribution network planning method based on big data technology comprises the following steps
The first step is as follows: fusing the initial database and the detection data of the power distribution network, analyzing data fusion levels, carrying out classification comparison on the data fusion method, and planning data fusion modes in different scenes;
the second step is that: planning the positions and scales of nodes in the active power distribution network by using an initial database, wherein the planning of the active power distribution network is divided into a project storage module and a management module;
the third step: fusing various indexes and an electronic map by adopting a mature technical framework on the service index data, the geographic space data and the network topology data of the active power distribution network, and integrating the fused active power distribution network data;
the fourth step: establishing a planning model containing the fused active power distribution network data, and solving the planning model
The fifth step: searching and extracting network signal characteristics under the normal operation state of the active power distribution network, recording the network signal characteristics into a database, classifying, judging and storing the data of the active power distribution network by adopting a CIM (common information model) algorithm, scheduling and configuring known data, and establishing a data analysis database;
and a sixth step: and establishing an effective index system, and carrying out comprehensive detection and abnormal motion detection.
In a further embodiment, the project storage module and the management module are evaluated, planned and constructed in the step 2, and the functions and the operation effects of the storage module and the management module can be evaluated, planned and constructed according to the acquired data, so that the efficient operation of the active power distribution network system is facilitated.
In a further embodiment, in step 3, a network topology data client of the active power distribution network can utilize the smart meter to query information and store voltage load data in the active power distribution network, so that the data information can be transmitted to the storage module and the management module, and load prediction can be performed on the voltage of the active power distribution network at a later stage.
In a further embodiment, in step 6, starting from a system substation tracking node, a deep neural network optimization method is combined, information of a starting end and a terminal of a power transmission path is searched and detected along a fixed line in an active power distribution network structure, and the acquired information is transmitted through a branch path, so that information relationships of path nodes of the branch can be registered, and investigation can be performed at any time.
In a further embodiment, in step 6, the information is searched and collected through the trunk line path until the search and storage of the trunk path node information are completed, and the information relationship of the path node of the trunk line can be registered, so that the investigation can be performed at any time.
In a further embodiment, the geographic space data in the step 3 is combined with a GIS system to optimize the active power distribution network planning system, so that the load voltage in the active power distribution network can be accurately predicted, and the problems of high power failure frequency and weak power grid equipment in the traditional power distribution network are solved.
In a further embodiment, the data analysis library in step 5 converts the data into a graph or an image through computer graphics and image processing technologies, and displays the graph or the image on a receiving end of the data, so that the data presentation effect can be enhanced, a user can observe the data more intuitively, and hidden information in the data can be found.
In a further embodiment, the index system in step 6 includes power supply quality, grid structure, equipment level, power supply capacity, grid efficiency and grid benefit, and can be strictly in accordance with relevant regulations and standards of active power distribution network operation, so as to facilitate realization of actual demand of power consumption in the active power distribution network.
In a further embodiment, the management module in step 2 implements quality management on the conceptual data model, the logical data model and the physical data model, thereby implementing functions of filling in the empty space and removing abnormal data.
Has the advantages that: the invention relates to an active power distribution network planning method based on big data technology, which can collect sound data information by planning the fusion mode of the initial database and the power distribution network detection data under different scenes, wherein the collected information has the same scale, and can be compared on the same dimension, so that the active power distribution network is planned on a uniform level, and the phenomenon that the active power distribution network information planning sections are different is reduced; by adopting a mature technical framework, various indexes are fused with the electronic map, and the formed active power distribution network data can reduce the problems of power failure and the like and relieve the weak condition of power grid equipment; by establishing an effective index system, comprehensive detection and abnormal motion detection can be realized, so that the phenomena of errors, error transmission and omission of configuration data are reduced.
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FIG. 1 is a flow chart of the method of the present invention.
FIG. 2 is a schematic diagram of the structure of the index system of the present invention.
Detailed Description
In the following description, numerous specific details are set forth in order to provide a more thorough understanding of the present invention. It will be apparent, however, to one skilled in the art, that the present invention may be practiced without one or more of these specific details. In other instances, well-known features have not been described in order to avoid obscuring the invention.
The invention relates to an active power distribution network planning method based on big data technology, which comprises the steps of fusing an initial database with a power distribution network detection database, planning data fusion modes under different scenes, dividing an active power distribution network into a storage module and a management module, classifying, judging and storing data of the active power distribution network by using a CIM (common information model) algorithm, and carrying out comprehensive detection and abnormal movement detection on the obtained active power distribution network data according to an established effective index system, so that the data in the active power distribution network can be comprehensively collected, the collected data can be compared on the same dimension, and the phenomenon of information asymmetry caused by different information planning sections is reduced; meanwhile, through a mature technical framework and an index system, the problems of power failure of the active power distribution network and weakness of power grid equipment can be effectively reduced, and the phenomena of errors, error transmission and omission in data configuration are reduced.
As shown in fig. 1, an active power distribution network planning method based on big data technology includes the following steps:
the method comprises the steps of firstly, fusing an initial database and detection data of the power distribution network, analyzing data fusion levels, carrying out classification comparison on data fusion methods, and planning data fusion modes in different scenes;
secondly, planning the positions and the scales of the nodes in the active power distribution network by using an initial database, wherein the planning of the active power distribution network is divided into a project storage module and a management module, and the project storage module and the management module are used for evaluating, planning and constructing;
thirdly, fusing various indexes and an electronic map by adopting a mature technical framework for business index data, geographic space data and network topology data of the active power distribution network, integrating the fused active power distribution network data, displaying the network topology data on an intelligent electric meter, storing voltage load data of the active power distribution network, and optimizing an active power distribution network system by combining the geographic space data with a GIS (geographic information system);
fourthly, establishing a planning model containing the fused active power distribution network data, and solving the planning model;
fifthly, searching and extracting network signal characteristics under the normal operation state of the active power distribution network, recording the network signal characteristics into a database, classifying, judging and storing the data of the active power distribution network by using a CIM (common information model) algorithm, scheduling and configuring known data, establishing a data analysis database, and converting the data into graphs or images by the data analysis database through computer graphics and image processing technologies to be displayed at a data receiving end;
and sixthly, establishing an effective index system, carrying out comprehensive detection and abnormal motion detection, searching and detecting information of a starting end and a terminal of a power transmission path along a fixed line in an active power distribution network structure by taking a system power transformation tracking node as a starting point and combining a deep neural network optimization method, transmitting the acquired information through a branch path, and searching and acquiring the information through a trunk line path until the information of the trunk path node is searched and stored.
As shown in fig. 2, the index system includes power supply quality, power grid structure, equipment level, power supply capacity, power grid efficiency, and power grid benefit, the selection of the index in the index system is considered from the perspective of implementation and operability, and the calculation method of the index strictly follows the relevant regulations and standards of power distribution network operation, so as to meet the actual demand of power distribution network monitoring. The power supply quality is calculated according to the power supply reliability evaluation regulation of users of a power supply system, and the index value is the sum of the power failure time of each household per total number of users (h); the calculation of the relevant indexes of the power grid structure refers to the standard of power supply business rules, such as power supply radius: (S is PL/C delta U%), wherein P is active power kW; l is the conveying distance, m; c is the voltage loss coefficient, the interconnection rate of the distribution line: r is the number of the public lines with connection/the total number of the public distribution lines multiplied by 100 percent; the power supply capacity determines a corresponding index calculation method according to the requirements of various places on the related indexes of the power supply capacity, and generally defines: no-load rate is the duration of no current (corresponding to the state of charge)/total duration; the light load rate is the duration/total duration of which the current is 20% -50% of the rated value; the overload rate is the time length for which the current reaches 80% of the rated value/total time length; full-load rate is the time length for which the current reaches the rated value/total time length; the overload rate is the time length/total time length when the current exceeds the rated value, and because an effective index system and a data analysis library are established, indexes such as the coverage rate of the transformer substation and the electric meter, the acquisition rate of distribution transformer information, the permeability of a distributed power supply and the like can be submitted by related departments without further calculation.
The active power distribution network planning method is based on big data, structured and unstructured data such as service index data, geographic space data, network topology data and the like of the power distribution network are built according to the data characteristics of the power distribution network by adopting a mature technical framework, a lightweight electronic map service is built, various indexes are fused with an electronic map, the fused power distribution network data are integrated, the distribution, characteristics, change trend and the like of the data are mastered and displayed, the foundation functions of adding, deleting, modifying, inquiring and the like of lines, towers, equipment and the like are realized by taking a geographic graph and a power grid current situation graph as backgrounds. Providing a basis for distribution network load prediction, substation site selection and net rack planning; by using computer graphics and image processing technology, data is converted into a graph or an image form for display on a screen, and a theory, a method and a technology of devious processing are performed, so that the data presentation effect can be enhanced, a user can conveniently observe the data in a more intuitive mode, and further, hidden information in the data can be found.
System normality in active distribution networkThe method comprises the steps of searching and extracting network node signal characteristics under the operating state, recording the network node signal characteristics into a database, classifying, judging and storing power distribution data parameters by using a CIM algorithm, setting the transmission frequency of the acquired network node signal data as P, the variance of a data transmission number as j, the peak value of a power distribution path transmission parameter as k, the optimal vector of the information characteristics as f, and the average vector as g, wherein the Q algorithm of the power distribution parameter planning quality is Q-1/2 pi ∑ P [ (f is f, n is a weight of the Q algorithmi-gi)k]2And optimizing the accuracy of power grid data planning by combining the algorithm, and connecting the terminal nodes and the information transmission path by using the topological network structure of the CIM so as to improve the data processing performance of the system and guarantee the operation effect of the system.
Learning and training historical fault data, summarizing equipment fault rules by combining models such as a support vector machine and the like, and predicting the time and the mode of future fault occurrence; for example, electricity stealing analysis is performed, a large amount of load data are subjected to cluster analysis to summarize typical load characteristics of fixed electricity consumers, electricity consumers who do not accord with the typical characteristics are screened and compared, and a conclusion of electricity stealing analysis can be scientifically given by combining customer archive data, so that data support and method support are provided for services of electricity stealing prevention and the like. Also, comprehensive testing and transaction testing requires further research using data analysis techniques.
Compared with the prior art, the active power distribution network planning method based on the big data technology moderately fuses topology information of the active power distribution network, state parameters of network frame equipment and geospatial information, realizes circuit and geographic information display at a panoramic three-dimensional multi-dimensional visual angle from the aspects of time dimension, topology dimension, geographic dimension, service dimension, particle dimension and the like, and reveals the trend, rule and value hidden behind data; the operation condition of the power distribution network can be visually checked, and the rule information of the power distribution network in dimensions such as safety quality and energy efficiency can be rapidly acquired and mastered.
As noted above, while the present invention has been shown and described with reference to certain preferred embodiments, it is not to be construed as limited thereto. Various changes in form and detail may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (9)
1. An active power distribution network planning method based on big data technology is characterized in that:
the method sequentially comprises the following steps:
step 1, fusing an initial database and detection data of a power distribution network, analyzing data fusion levels, classifying and comparing data fusion methods, and planning data fusion modes in different scenes;
step 2, planning the node positions and scales in the active power distribution network by using an initial database, wherein the planning of the active power distribution network is divided into a project storage module and a management module;
step 3, fusing various indexes and an electronic map by adopting a mature technical framework for service index data, geographic space data and network topology data of the active power distribution network, and integrating the fused active power distribution network data;
step 4, establishing a planning model containing the fused active power distribution network data, and solving the planning model;
step 5, searching and extracting network signal characteristics under the normal operation state of the active power distribution network, inputting the network signal characteristics into a database, classifying, judging and storing the data of the active power distribution network by adopting a CIM algorithm, scheduling and configuring known data, and establishing a data analysis database;
and 6, establishing an effective index system, and carrying out comprehensive detection and abnormal motion detection.
2. The active power distribution network planning method based on big data technology according to claim 1, characterized in that: and in the step 2, evaluating, planning and constructing the project reserve module and the management module.
3. The active power distribution network planning method based on big data technology according to claim 1, characterized in that: and 3, a network topology data client of the active power distribution network can utilize the intelligent electric meter to realize information query and store voltage load data in the active power distribution network.
4. The active power distribution network planning method based on big data technology according to claim 1, characterized in that: in the step 6, starting from a system power transformation heel node, searching and detecting information of a starting end and a terminal of a power transmission path along a fixed line in an active power distribution network structure by combining a deep neural network optimization method, and transmitting the acquired information through a branch path.
5. The active power distribution network planning method based on big data technology according to claim 4, characterized in that: and 6, searching and collecting the information through the trunk line path until the information of the trunk path node is searched and stored.
6. The active power distribution network planning method based on big data technology according to claim 1, characterized in that: and (3) optimizing the active power distribution network planning system by combining the geographic space data in the step 3 with a GIS system.
7. The active power distribution network planning method based on big data technology according to claim 1, characterized in that: and the data analysis library in the step 5 converts the data into graphs or images through computer graphics and image processing technology and displays the graphs or images on a data receiving end.
8. The active power distribution network planning method based on big data technology according to claim 1, characterized in that: the index system in the step 6 comprises power supply quality, power grid structure, equipment level, power supply capacity, power grid efficiency and power grid benefit.
9. The active power distribution network planning method based on big data technology according to claim 1, characterized in that: and the management module in the step 2 realizes quality management of the conceptual data model, the logic data model and the physical data model.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113313429A (en) * | 2021-07-22 | 2021-08-27 | 国网河南省电力公司周口供电公司 | Big data analysis system for power grid planning |
| CN117349493A (en) * | 2023-09-27 | 2024-01-05 | 广东电网有限责任公司 | Method and device for visual display of power system data based on cim model |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113313429A (en) * | 2021-07-22 | 2021-08-27 | 国网河南省电力公司周口供电公司 | Big data analysis system for power grid planning |
| CN117349493A (en) * | 2023-09-27 | 2024-01-05 | 广东电网有限责任公司 | Method and device for visual display of power system data based on cim model |
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