CN115146927A - Distribution network disaster early warning and risk assessment method and system considering multi-source data - Google Patents
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Abstract
The invention belongs to the field of electric power, and particularly relates to a distribution network disaster early warning and risk assessment method and system considering multi-source data, wherein the method comprises the steps of collecting multi-source information data for risk identification; preprocessing the multi-source information data to obtain processed multi-source information data; and inputting the processed multi-source information data into a power distribution network equipment disaster damage probability early warning model to obtain a power distribution network damage prediction result. The authenticity of a power distribution network disaster prediction result is increased by collecting multi-source information data for risk identification; preprocessing the multi-source information data to obtain processed multi-source information data, so that the efficiency and accuracy of data processing can be improved; and inputting the processed multi-source information data into a power distribution network equipment disaster damage probability early warning model to obtain a power distribution network damage prediction result for subsequent corresponding improvement and risk coping work.
Description
Technical Field
The invention belongs to the field of electric power, and particularly relates to a distribution network disaster early warning and risk assessment method and system considering multi-source data.
Background
An intelligent distribution network is one of key links of an intelligent power grid, generally, a power network of 10kV or below belongs to a distribution network (20 kV in partial areas), and the distribution network is a part of a whole power system directly connected with dispersed users. The intelligent distribution network system integrates the online data and the offline data of the distribution network, the data and the user data of the distribution network, the structure of the power grid and the geographic graph by utilizing the modern electronic technology, the communication technology, the computer and the network technology, and realizes the intellectualization of monitoring, protection, control, power utilization and power distribution management under the normal operation and accident conditions of the distribution system.
The multi-source data fusion of the power distribution network is part of the intellectualization of the power distribution network, and the reasonable line disaster-resistant standard can be referred and formulated in the power distribution network planning process by knowing the risk condition of the power distribution network, and particularly the power distribution network can play a reference role in the rural power network planning with weak disaster-resistant capability.
At present, severe weather represented by typhoon, thunder, high temperature, icing and strong convection weather frequently occurs, and most of power networks, especially overhead lines, are distributed in outdoor environment and are exposed to the interference of the severe weather for a long time. In view of this, a method for evaluating the risk of the power distribution network facing a disaster, making a preparation for emergency repair of power, and improving the disaster prevention capability of the power distribution network is needed.
Disclosure of Invention
In order to solve or improve the problems, the invention provides a distribution network disaster early warning and risk assessment method and system considering multi-source data, and the specific technical scheme is as follows:
the invention provides a distribution network disaster early warning and risk assessment method considering multi-source data, which comprises the following steps: collecting multi-source information data for risk identification; preprocessing the multi-source information data to obtain processed multi-source information data; and inputting the processed multi-source information data into a power distribution network equipment disaster damage probability early warning model to obtain a power distribution network damage prediction result.
Preferably, the multi-source information data comprises meteorological environment data, power distribution equipment ledgers, power distribution network operation data and GIS map data.
Preferably, the power distribution network damage prediction result comprises a power distribution network equipment damage condition; correspondingly, the method further comprises the following steps: and determining the outage probability of each power distribution network device according to the damage condition of the power distribution network device.
Preferably, the method further comprises: and setting the running state of the power distribution network equipment according to the outage probability.
Preferably, the setting the operation state of the power distribution network device according to the outage probability includes: and if the outage probability meets a preset threshold value, the corresponding power distribution network equipment is shut down, standby power supply equipment is started according to the emergency management plan, and the topological structure of the power distribution network is updated.
Preferably, the method further comprises: if the updated topological structure of the power distribution network is an island power grid, obtaining the power failure load of the updated power distribution network according to the power generation and load difference of the updated power distribution network; and if the updated topological structure of the power distribution network is a complete structure, obtaining the load meeting the load shedding measures adopted by the updated power distribution network for keeping power supply according to a minimum loss load shedding optimization method.
Preferably, the minimum loss load shedding optimization method minG (P) includes:
in the formula, P i For the load i initial active power, P i * The active power of a load i after a load shedding measure is taken; f is the network power flow equation, V and theta are all node voltages and phase angle vectors, P * And Q * Respectively all load active and reactive power vectors, V, after load shedding measures k Is the node voltage amplitude, Ω is the node set, F l Psi is the branch set, the transmission power of branch l.
Preferably, the method further comprises: traversing each load of the power distribution network after the load shedding measure is executed, and calculating the power failure probability of each load; and obtaining the power failure risk of the power distribution network according to the power failure probability of each load.
The invention provides a distribution network disaster early warning and risk assessment system considering multi-source data, which comprises: the first unit is used for acquiring multi-source information data for risk identification; the second unit is used for preprocessing the multi-source information data to obtain processed multi-source information data; and the third unit is used for inputting the processed multi-source information data into a power distribution network equipment disaster damage probability early warning model to obtain a power distribution network damage prediction result.
The invention has the beneficial effects that: the authenticity of a power distribution network disaster prediction result is increased by collecting multi-source information data for risk identification; preprocessing the multi-source information data to obtain processed multi-source information data, so that the efficiency and accuracy of data processing can be improved; and inputting the processed multi-source information data into a power distribution network equipment disaster damage probability early warning model to obtain a power distribution network damage prediction result for subsequent corresponding improvement and risk coping work.
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FIG. 1 is a schematic diagram of a distribution network disaster warning and risk assessment method in accordance with the present invention that considers multi-source data;
fig. 2 is a schematic diagram of a distribution network disaster warning and risk assessment system considering multi-source data according to the present invention.
Description of the main reference numerals:
1-first unit, 2-second unit, 3-third unit.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
In order to solve or improve the problem of early warning and evaluation of power distribution network disasters fusing multi-source data, a method for early warning and risk evaluation of a power distribution network disaster considering the multi-source data is provided as shown in fig. 1, and comprises the following steps:
s1, collecting multi-source information data for risk identification;
s2, preprocessing the multi-source information data to obtain processed multi-source information data;
and S3, inputting the processed multi-source information data into a power distribution network equipment disaster damage probability early warning model to obtain a power distribution network damage prediction result.
The structure and the operation mode of the power distribution network are different from those of other industries; however, as in other industries, special accidents and abnormal conditions which can occur in the industry are encountered, and the accidents and the abnormal conditions which do not form the accidents are risks in the operation process of the power distribution network. The risk of the power distribution network can be reflected through the form of data generation/change, namely, various data generated during the persistence, change and work of the building structure of the power distribution network, and various data generated during the power transmission process of the power distribution network can change when the risk occurs; in turn, according to the sensors arranged on the building structure and the measuring equipment specially used for measuring various data generated in the power transmission process, the acquired various data related to the power distribution network change, and whether the power distribution network has risks or not can be reversely deduced. The collected data can be used for identifying related risks of the power distribution network, and the different types of data and the data from different sources are collectively called multi-source information data.
Data preprocessing refers to some processing performed on data before main processing. The processing method has the advantages that the irregularly distributed measurement data are converted into regular measurement data through interpolation, the measurement data are favorably brought into the power distribution network equipment disaster damage probability early warning model for operation in the follow-up process, and the processing efficiency can be improved.
The power distribution network equipment disaster damage probability early warning model is a mathematical model which is set according to experience and/or related theoretical models and by combining the specific structure and the running state of the power distribution network, multi-source information data is used as input, and damage probability is used as an output power distribution network damage prediction result. The setting principle of the power distribution network equipment disaster damage probability early warning model specifically can be as follows: according to the historical records, taking the risks and the data changes when the corresponding risks occur as data to be processed, then setting a mathematical model, and optimizing the mathematical model according to the data to be processed to obtain a power distribution network equipment disaster damage probability early warning model; through the power distribution network equipment disaster damage probability early warning model, the operation risk (including the content of risk occurrence time, type, occurrence probability and the like) of the power distribution network at the future time can be predicted according to the currently collected multi-source information data output by the power distribution network.
The multi-source information data comprise meteorological environment data, power distribution equipment ledgers, power distribution network operation data and GIS map data.
The meteorological environment data comprise data of the environment where the power distribution network is located, including contents such as terrain type, elevation, forest distribution condition, soil attribute, longitude and latitude and the like; and meteorological data of the place where the power distribution network is located comprise contents such as temperature, humidity, wind power, illumination intensity and the like.
The distribution equipment ledger comprises the contents of models, numbers, identifications and the like of electronic equipment, mechanical equipment and building structures in the composition of the distribution network.
The operation data of the power distribution network is in the operation process of the power distribution network: operational data generated by the electronic equipment, measurement data acquired by the sensors and measurement instruments, and other related data.
The GIS map data is short for data of a geographic information system (geographic information system) in the map aspect, and in this embodiment, map data near the location where the power grid is located is mainly assigned.
Through the data, various risks which the power distribution network can encounter can be explained by combining historical records/historical data, so that the future operating state of the power distribution network can be predicted subsequently according to the current data/real-time data.
The power distribution network damage prediction result comprises a power distribution network equipment damage condition; correspondingly, the method also comprises the following steps: and determining the outage probability of each power distribution network device according to the damage condition of the power distribution network device.
In practice, electrical distribution networks include electronic, mechanical and other devices, referred to simply as distribution network devices, which may experience/encounter various types of damage during operation. According to historical experience summarized in operation/management of the power distribution network, the damage condition of the power distribution network equipment can be counted/analyzed, and the outage probability of each power distribution network equipment can be determined according to the damage condition of the power distribution network equipment. For example, if the transformation power of the substation equipment is reduced, it indicates that aging or other abnormalities exist, and according to the reduction degree of the transformation power, the degree of aging or other abnormalities can be judged, namely the damage condition of the distribution network equipment; obviously, the greater and faster the degree of drop of the transformation power, the higher the probability of the outage probability of the substation equipment, and the corresponding maintenance or replacement is required. By determining the outage probability of each distribution network device, which distribution network devices face larger risks can be judged, and corresponding inspection, overhaul or replacement is convenient to carry out.
The method further comprises the following steps: and setting the running state of the power distribution network equipment according to the outage probability.
The safe/stable operation of the power distribution network is particularly important, and if the power distribution network is repaired correspondingly when a problem occurs, the power consumption end and the power generation end are damaged. Therefore, the power distribution network equipment can be processed in advance according to the risks, namely the outage probability, the probability of accidents can be reduced, and the safe/stable operation capacity of the power distribution network is improved.
The operating state of the distribution network device can thus be set as a function of the outage probability. Specifically, the high outage probability indicates that the power distribution network equipment faces a large operation risk, and at the moment, the power distribution network equipment can stop operating to be maintained and replaced; if the outage probability is medium, the power distribution network equipment is indicated to face a common operation risk, and at the moment, the power distribution network equipment can be overhauled; if the outage probability is low, the power distribution network equipment faces a very low operation risk, and at this time, only the inspection can be performed.
The operation state of the power distribution network equipment is set according to the outage probability, so that the maintenance cost can be reduced, and the operation stability of the power distribution network is improved in a mode of troubleshooting in advance.
The setting of the running state of the power distribution network equipment according to the outage probability comprises the following steps: and if the outage probability meets a preset threshold value, the corresponding power distribution network equipment is shut down, standby power supply equipment is started according to the emergency management plan, and the topological structure of the power distribution network is updated.
The preset threshold is a threshold set according to actual experience in the field and special requirements, and aims to prevent accidents caused by continuous operation of high-risk equipment. The emergency management plan is an operation guide of corresponding risks set according to actual experience and special requirements, and specifically can be used for starting standby power supply equipment and updating a topological structure of the power distribution network. The special requirements are requirements set according to special application scenes of the power distribution network, such as military power supply, important department power supply and important industrial power supply, and due to the existence of specificity, the power supply requirements are different.
The method further comprises the following steps: if the updated topological structure of the power distribution network is an island power grid, obtaining the power failure load of the updated power distribution network according to the power generation and load difference of the updated power distribution network; and if the updated topological structure of the power distribution network is a complete structure, obtaining the load meeting the load shedding measures adopted by the updated power distribution network for keeping power supply according to a minimum loss load shedding optimization method.
The minimum loss load shedding optimization method minG (P) comprises the following steps:
in the formula, pi is the initial active power of the load i, and Pi is the active power of the load i after the load shedding measure is taken; f is a network power flow equation, V and theta are all node voltage and phase angle vectors, P and Q are all load active power and reactive power vectors after load shedding measures respectively, vk is a node voltage amplitude, omega is a node set, fl is transmission power of a branch l, and psi is a branch set.
The load shedding measure refers to the process of switching a specific power generation source, a specific power transmission line and a specific power utilization load in a circuit. Through this process.
The method further comprises the following steps: traversing each load of the power distribution network after the load shedding measure is executed, and calculating the power failure probability of each load; and obtaining the power failure risk of the power distribution network according to the power failure probability of each load.
The server of the power distribution network can traverse each load of the power distribution network after executing the load shedding measure, and calculate the power failure probability of each load; and obtaining the power failure risk of the power distribution network according to the power failure probability of each load.
A power distribution network disaster early warning method fusing multi-source data is characterized in that under different natural disaster conditions such as typhoon, thunder, high temperature, ice coating, strong convection weather and the like, data such as meteorological environment data, power distribution equipment account, power distribution network operation, GIS maps and the like are fused and analyzed, a power distribution network equipment disaster damage probability early warning model is established, and early warning is carried out on the damage condition of a power distribution network in a disaster environment; the power distribution network disaster risk assessment technology is researched, a power distribution equipment outage probability model is established, and corresponding power failure loads after the equipment is shut down are analyzed and calculated. And stopping the equipment, starting a standby power supply path (or equipment) which is designed in the emergency management plan and can be started after the equipment is stopped, and further updating the power grid topological structure.
Analyzing the updated power grid topological structure, and if the isolated island power grid is separated from the main grid to operate, calculating the power generation and load difference of the isolated island power grid so as to obtain the power failure load of the isolated island power grid; and if the power grid is kept complete, calculating the minimum loss load shedding optimization problem, and solving the load to be shed for keeping the power supply of the key load of the system under the condition of meeting the power grid operation requirement and equipment capacity constraint. And updating the uninterrupted power probability of the load to be cut through calculation. Until all the affected equipment sets are traversed, and then the outage probability of each load is calculated. And finally, calculating the power failure risk of the urban distribution network under the condition of an emergency.
Wherein, the probability p of occurrence of the disaster i is generally adopted i And severity of hazards C i The risk R is calculated as the product of (a) and (b), which can be expressed in terms of outage load for disaster severity. The specific calculation formula is as follows:
wherein the value coefficient c i Generally determined by the need to conserve power in emergency management. For example, in everyday situations, the loads of municipalities, hospitals, transportation systems, etc. are of great value, while during major public activities such as the olympic games, etc., a greater value factor should be set for the relevant venues and transportation facilities.
The invention provides a distribution network disaster early warning and risk assessment system considering multi-source data, which is shown in figure 2 and comprises: the first unit 1 is used for collecting multi-source information data for risk identification; the second unit 2 is used for preprocessing the multi-source information data to obtain processed multi-source information data; and a third unit 3, configured to input the processed multi-source information data into a power distribution network equipment disaster damage probability early warning model, so as to obtain a power distribution network damage prediction result.
The structure and the operation mode of the power distribution network are different from those of other industries; however, as in other industries, special accidents and abnormal conditions which can occur in the industry are encountered, and the accidents and the abnormal conditions which do not form the accidents are risks in the operation process of the power distribution network. The risk of the power distribution network can be reflected through the form of data generation/change, namely, various data generated during the persistence, change and work of the building structure of the power distribution network, and various data generated during the power transmission process of the power distribution network can change when the risk occurs; in turn, according to the sensors arranged on the building structure and the measuring equipment specially used for measuring various data generated in the power transmission process, the acquired various data related to the power distribution network change, and whether the power distribution network has risks or not can be reversely deduced. The collected data can be used for identifying related risks of the power distribution network, and the data of different types and the data of different sources are collectively called multi-source information data.
Data preprocessing refers to some processing performed on data before main processing. The processing that the irregular distribution's measured data is converted into regular measured data through the interpolation, be favorable to follow-up bringing it into distribution network equipment calamity damage probability early warning model and carry out the operation, can improve the efficiency of handling.
The power distribution network equipment disaster damage probability early warning model is a mathematical model which is set according to experience and/or related theoretical models and by combining the specific structure and the running state of the power distribution network, and takes multi-source information data as input and damage probability as an output power distribution network damage prediction result. The setting principle of the power distribution network equipment disaster damage probability early warning model specifically can be as follows: according to the historical records, taking the risks and the data changes when the corresponding risks occur as data to be processed, then setting a mathematical model, and optimizing the mathematical model according to the data to be processed to obtain a power distribution network equipment disaster damage probability early warning model; through the power distribution network equipment disaster damage probability early warning model, the operation risk (including the content of risk occurrence time, type, occurrence probability and the like) of the power distribution network at the future time can be predicted according to the currently collected multi-source information data output by the power distribution network.
Those of ordinary skill in the art will appreciate that the elements of the examples described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations thereof, and that the components of the examples have been described above generally in terms of their functionality in order to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present application, it should be understood that the division of the unit is only one division of logical functions, and other division manners may be used in actual implementation, for example, multiple units may be combined into one unit, one unit may be split into multiple units, or some features may be omitted.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit and scope of the embodiments of the present invention, and they should be construed as being covered by the appended claims and their equivalents.
Claims (9)
1. A distribution network disaster early warning and risk assessment method considering multi-source data is characterized by comprising the following steps:
collecting multi-source information data for risk identification;
preprocessing the multi-source information data to obtain processed multi-source information data;
and inputting the processed multi-source information data into a power distribution network equipment disaster damage probability early warning model to obtain a power distribution network damage prediction result.
2. The distribution network disaster early warning and risk assessment method considering multi-source data as claimed in claim 1, wherein the multi-source information data includes meteorological environment data, distribution equipment ledger, distribution network operation data and GIS map data.
3. The distribution network disaster early warning and risk assessment method considering multi-source data according to claim 1, wherein the distribution network damage prediction result comprises a distribution network equipment damage condition;
correspondingly, the method further comprises the following steps:
and determining the outage probability of each power distribution network device according to the damage condition of the power distribution network device.
4. The distribution network disaster early warning and risk assessment method considering multi-source data according to claim 3, characterized in that the method further comprises:
and setting the running state of the power distribution network equipment according to the outage probability.
5. The distribution network disaster early warning and risk assessment method considering multi-source data according to claim 4, wherein the setting of the operation state of the distribution network equipment according to outage probability comprises:
and if the outage probability meets a preset threshold value, the corresponding power distribution network equipment is shut down, standby power supply equipment is started according to the emergency management plan, and the topological structure of the power distribution network is updated.
6. The distribution network disaster early warning and risk assessment method considering multi-source data according to claim 5, characterized in that the method further comprises:
if the updated topological structure of the power distribution network is an island power grid, obtaining the power failure load of the updated power distribution network according to the power generation and load difference of the updated power distribution network;
and if the updated topological structure of the power distribution network is a complete structure, obtaining the load meeting the load shedding measures adopted by the updated power distribution network for keeping power supply according to a minimum loss load shedding optimization method.
7. The distribution network disaster early warning and risk assessment method considering multi-source data according to claim 6, wherein the minimum loss load shedding optimization method minG (P) comprises:
in the formula, P i For the load i initial active power, P i * The active power of a load i after a load shedding measure is taken; f is the network power flow equation, V and theta are all node voltages and phase angle vectors, P * And Q * All loads after load shedding measuresActive and reactive power vectors, V k Is the node voltage amplitude, Ω is the node set, F l Psi is the branch set, the transmission power of branch l.
8. The distribution network disaster early warning and risk assessment method considering multi-source data according to claim 7, characterized in that the method further comprises:
traversing each load of the power distribution network after the load shedding measure is executed, and calculating the power failure probability of each load;
and obtaining the power failure risk of the power distribution network according to the power failure probability of each load.
9. The utility model provides a consider net disaster early warning and risk assessment system of joining in marriage of multisource data which characterized in that includes:
the first unit is used for acquiring multi-source information data for risk identification;
the second unit is used for preprocessing the multi-source information data to obtain processed multi-source information data;
and the third unit is used for inputting the processed multi-source information data into a power distribution network equipment disaster damage probability early warning model to obtain a power distribution network damage prediction result.
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