CN116484149A - Quantitative evaluation method for distribution network power outage overhaul plan - Google Patents
Quantitative evaluation method for distribution network power outage overhaul plan Download PDFInfo
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Abstract
The application provides a quantitative evaluation method for a distribution network power outage overhaul plan, which comprises the following steps: performing automatic checking and balancing on the power failure maintenance plan based on the equipment topological graph, the defect equipment information and the constraint condition to obtain a risk checking result; and adjusting the distribution network power outage overhaul plan based on the risk check result. According to the method, the compliance of the maintenance plan is intelligently checked through weighting and integrating the related professional constraint conditions, the omission caused by the manual statistics is reduced, and the time consumption of the plan balancing work can be shortened.
Description
The application is a divisional application, the application number of the main application is 202210669093.1, the application date is 2022.06.14, and the invention name is a method, a system and a terminal for automatically checking balance of a distribution network power failure maintenance plan.
Technical Field
The application relates to the technical field of intelligent power grids, in particular to a quantitative evaluation method for power outage overhaul plans of a distribution network.
Background
The statements in this section merely provide background information related to the present application and may not necessarily constitute prior art.
Along with the acceleration of the modern progress of society, the dependence of production and life on electric energy is also larger and larger, and the loss caused by power failure to national economy far exceeds the loss of an electric power system. As for the power outage cause of the power system, power outage maintenance of power transmission and distribution equipment every year is an unavoidable factor, and occupies a large proportion in the event of power outage.
The current distribution network power failure maintenance plan balance adopts the maintenance of professional conferences, related constraint conditions need manual statistics and verification, omission is easy to generate manually, and a final plan can be determined by the maintenance of a plurality of professional balance conferees, so that the time consumption is long, and the early preparation work of the specific implementation of the plan is prolonged.
Disclosure of Invention
In order to solve the problems, the application provides a quantitative evaluation method for a distribution network power outage overhaul plan.
The application provides a quantitative evaluation method for a distribution network power outage overhaul plan, which comprises the following steps:
performing automatic checking and balancing on the power failure maintenance plan based on the equipment topological graph, the defect equipment information and the constraint condition to obtain a risk checking result;
adjusting the distribution network power outage overhaul plan based on the risk check result;
the risk checking result comprises a power failure risk value f, and the power failure risk value f is quantified in the following manner:
f＝λ 1 f s +λ 2 f m
wherein lambda is 1 、λ 2 Is an adjustable weight parameter; lambda (lambda) 1 +λ 1 ＝1，λ 1 、λ 2 ∈(0，1)；
d i The initial value is 1; d, repeating the power failure of the equipment once i Self-increasing 1; each self-increment generates a d i ；
M i The initial value is the standard number of the users in single power failure, and M is the number of the users exceeding the standard once in single power failure i Self-increasing 1; each self-increment generates one M i ；
T is the upper limit value of the dispatching bearing capacity;
C i to preserve the power task conflict value, the initial value is 1, and when a conflict is detected, the conflict is self-increased by 0.5, because the conflict involves two parties, each self-increase generates C i ；
f s Embodying the dimension of customer premium services, f m The dimension of safety and reliability of the power grid is embodied. .
Preferably, the constraint conditions include a time constraint, a device constraint, a frequency constraint, a dual power user constraint, a non-co-stop constraint, and a scheduling workload constraint.
Preferably, the method for automatically checking balance further comprises: and generating a power outage risk analysis report and giving an adjustment suggestion based on the AI check engine.
Preferably, the algorithm for the AI check engine to perform the check is as follows:
holiday time constraint: when the maintenance plan is intelligently arranged, the system automatically executes a holiday constraint checking function, automatically adjusts the maintenance plan time with conflict, and displays adjustment detail data and use constraint rules;
available time period constraint checking: when the overhaul plan is intelligently arranged, the system automatically executes an available time period constraint checking function, automatically adjusts the conflict overhaul plan time, and displays adjustment detail data and use constraint rules;
important equipment and electricity-keeping user constraint checking: when the overhaul plan is intelligently arranged, the system automatically executes an important equipment constraint checking function, automatically adjusts the conflict overhaul plan time, and displays adjustment detail data and use constraint rules;
checking power failure frequency constraint: automatically collecting data of historical power outage records of power outage users in two months in a power outage scheme, and automatically reminding the situation that the power outage frequency is too high so as to provide reference for customer complaint management and control and power supply reliability;
dual power user constraints: when the maintenance plan is intelligently arranged, the system automatically retrieves the line information in the dual-power user table, checks the line information with power failure equipment in all power failure plans, and gives and prompts, and displays alarm information and use constraint rules if conflict exists;
non-co-stop constraint: when the maintenance plan is intelligently arranged, the system automatically searches the line information in the equipment table which can not be stopped together, checks the line information with the power failure equipment in all the power failure plans, and gives a prompt and displays alarm information and a use constraint rule if conflict exists;
scheduling workload constraints: when the overhaul plan is intelligently arranged, the system automatically executes a scheduling workload constraint checking function, and if conflict exists, alarm information and using constraint rules are displayed for prompt.
Preferably, the risk checking result classifies the power failure risk as an early warning level according to different influence degrees of the risk.
Preferably, if the checking result of the power outage plan is free of risk, the plan is automatically validated; if the plan is at risk, the on-line approval of the relevant responsibility units is required to be effective.
Compared with the prior art, the beneficial effects of this application are:
according to the method, the compliance of the maintenance plan is intelligently checked through weighting and integrating the related professional constraint conditions, the omission caused by the manual statistics is reduced, and the time consumption of the plan balancing work can be shortened.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute an undue limitation to the application.
FIG. 1 is a flow chart of a method for automatically checking balance of a distribution network outage overhaul plan according to one embodiment of the present invention;
FIG. 2 is a flow chart of a method for automatically checking balance of a distribution network outage service plan according to yet another preferred embodiment of the present invention;
FIG. 3 is a schematic overall flow chart of a method for automatically checking balance of a distribution network outage overhaul plan according to the present invention;
FIG. 4 is a schematic diagram of various modules for performing the methods described in FIGS. 1-3;
FIG. 5 is a system architecture diagram for automatically checking balance of a distribution network outage overhaul plan that performs the method described in FIGS. 1-3;
FIG. 6 is a schematic diagram of a visual architecture layout of the present invention;
fig. 7 is a schematic structural diagram of a terminal device implementing the method described in fig. 1-3.
The specific embodiment is as follows:
the present application is further described below with reference to the drawings and examples.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments in accordance with the present disclosure. As used herein, the singular is also intended to include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that the terms "comprises" and/or "comprising" when used in this specification are taken to specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.
In the present disclosure, terms such as "upper", "lower", "left", "right", "front", "rear", "vertical", "horizontal", "side", "bottom", and the like indicate an azimuth or a positional relationship based on the azimuth or the positional relationship shown in the drawings, are merely relational terms determined for convenience in describing structural relationships of the various components or elements of the present disclosure, and do not denote any one of the components or elements of the present disclosure, and are not to be construed as limiting the present disclosure.
Referring to fig. 1, fig. 1 is a flow chart of a method for automatically checking balance of a distribution network outage overhaul plan according to an embodiment of the present invention.
In fig. 1, the method comprises the steps S1-S6 shown, each of which is implemented in particular as follows:
s1: acquiring a power outage overhaul plan of the distribution network, wherein the overhaul plan comprises a power outage overhaul plan range, power outage equipment, a power outage period of each equipment and equipment association attributes;
s2: acquiring an equipment topological graph of all equipment within the power outage overhaul plan range of the distribution network;
s3: obtaining defect equipment information;
s4: obtaining constraint conditions;
s5: performing automatic checking balance on the power failure maintenance plan based on the equipment topological graph, the defect equipment information and the constraint condition to obtain a risk checking result;
s6: and adjusting the distribution network power outage overhaul plan based on the risk check result.
In step S1, the device association attribute is a live coloring state of the display device based on the primary wiring diagram and the current operation state of the system such as the automatic interfacing EMS, and the adjacent devices with the same live coloring state are used as the associated devices.
In step S2, based on the topological relation and the running state of the device, analyzing the power supply path of the device, and performing overall analysis on the device in the power outage plan list;
in step S3, automatic association of defective devices is achieved. The method comprises the steps of obtaining log flow information of all equipment in a power failure overhaul plan range of a distribution network; and determining defect equipment information based on the log flow information.
Further, step S3 is to compare the defect flow (or log) information with the equipment in the current existing power outage plan, find the equipment not listed in the power outage plan, and automatically recommend to add the power outage plan;
the constraint conditions obtained in the step S4 include:
time constraints, device constraints, frequency constraints, dual power user constraints, non-scrutiny constraints, and scheduling workload constraints.
The following will briefly introduce the above constraints one by one:
1) Holiday time constraint
For major activities, important meetings, main holidays, special dates of power conservation and the like, the system supports the configuration function of a special time period, and the power failure plan is not allowed to be executed in the configuration time period.
2) Available time period constraint check
For the power outage plans of different overhaul categories and work categories, the system supports the function of configuring the available time period of the power outage plans, and for the configured overhaul categories or work categories, overhaul can only be carried out in the configured time period.
3) Important equipment and electricity-keeping user constraint check
And supporting distinguishing important equipment, setting constraint rules of the uninterruptible time period for specific important equipment, and establishing an important equipment constraint table.
4) Power failure frequency constraint checking
And automatically collecting data of historical power outage records of power outage users in two months in a power outage scheme.
5) Dual power user constraints
And establishing a dual-power user table, wherein the dual-power supply circuits of the same user cannot be powered off at the same time.
6) Non-stop-and-go constraint
An equipment table which can not be stopped simultaneously is established, and equipment such as double-circuit lines of the same tower, lines erected with the same pole and the like can not be stopped simultaneously. .
7) Scheduling workload constraints
For the same dispatching mechanism, setting the upper limit of the dispatching workload (dispatching operation command work) every day or every hour, and assuming that the initialization value of the dispatching workload (dispatching operation command work) corresponding to one distribution network maintenance plan is 2, setting the upper limit of the workload per hour of the dispatching mechanism to be 10, and dispatching up to 5 distribution network maintenance works per hour.
The step S5 includes:
and analyzing the power supply path of the equipment based on the equipment topological graph, integrally analyzing the power failure equipment in the power failure maintenance plan, identifying whether the power supply relation exists between the equipment to be powered off, and merging the equipment to be powered off with the power supply relation.
More specifically, in the step S5, the automatic checking balance performs weighted risk assessment by using repeated power outage of the device, out-of-limit of the dispatching bearing capacity, conflict of power-saving tasks, standard exceeding of the number of users in single power outage and repeated power outage of the user as indexes, so as to obtain a risk checking result.
Specifically, the step S5 further includes: generating a power failure risk analysis report and giving an adjustment suggestion based on an AI check engine;
the step S6 further includes: and simulating the operation recovery result of the distribution network equipment after the regulated distribution network power failure maintenance plan is executed through the AI check engine.
Taking the constraint condition as an example, the algorithm for executing the check by the AI check engine is as follows:
1) Holiday time constraint
When the maintenance plan is intelligently arranged, the system automatically executes a holiday constraint checking function, automatically adjusts the maintenance plan time with conflict, and displays adjustment detail data and usage constraint rules.
2) Available time period constraint check
When the overhaul plan is intelligently arranged, the system automatically executes an available time period constraint checking function, automatically adjusts the conflict overhaul plan time, and displays adjustment detail data and use constraint rules.
3) Important equipment and electricity-keeping user constraint check
When the overhaul plan is intelligently arranged, the system automatically executes an important equipment constraint checking function, automatically adjusts the conflict overhaul plan time, and displays adjustment detail data and use constraint rules.
4) Power failure frequency constraint checking
The method comprises the steps of automatically collecting data of historical power outage records of power outage users in two months in a power outage scheme, automatically reminding the situation that the power outage frequency is too high, and providing customer complaint management and control and power supply reliability reference.
5) Dual power user constraints
When the maintenance plan is intelligently arranged, the system automatically retrieves the line information in the dual-power user table, checks the line information with power failure equipment in all power failure plans, and gives and prompts, and displays alarm information and use constraint rules if conflict exists.
6) Non-stop-and-go constraint
When the maintenance plan is intelligently arranged, the system automatically searches the line information in the equipment table which can not be stopped together, checks the line information with the power failure equipment in all the power failure plans, and gives a prompt and displays alarm information and a use constraint rule if conflict exists.
7) Scheduling workload constraints
When the overhaul plan is intelligently arranged, the system automatically executes a scheduling workload constraint checking function, and if conflict exists, alarm information and using constraint rules are displayed for prompt.
In general, the above-described method may be framed on an annual service schedule, generating a monthly service schedule. The monthly maintenance schedule is required to be intelligently checked according to constraint conditions such as holiday time, available time period, important equipment non-blackable time period, repeated blackout equipment, dual-power users, non-stop equipment, combinable blackout equipment, inspection center workload, scheduling operation command workload and the like by the system, and the compliance of the maintenance schedule is intelligently checked according to constraint rules and the distribution network monthly maintenance schedule is intelligently arranged.
See fig. 2, based on fig. 1.
The method of fig. 2 after said step S6, the method further comprises:
s7: docking with an OMS system of the distribution network, and publishing the adjusted power failure maintenance plan of the distribution network; the publishing includes:
and displaying the risk points in the execution process of the distribution network power failure maintenance plan after adjustment in a visualized manner.
Specifically, based on the risk that the power failure plan found in the power failure risk checking and constraint condition checking process can cause to the power grid, the risk points which do not pass through checking are reminded, and an auxiliary operator can conduct targeted adjustment on the power failure plan. Many situations such as delay, cancellation of planning before the distribution network day come from the influence of extremely bad weather.
1) When the temperature of the region is lower than-10 degrees or higher than 32 degrees, the service logic and the weak point reasoning of the power grid are needed, the intelligent deferred maintenance of the main transformer side is realized, and the influence of the ultra-high load on the safety of the power grid is avoided.
2) When a certain area is in extreme severe weather such as thunderstorm or heavy rain to heavy rain, the outdoor overhaul plan does not accord with the safety overhaul condition of the power grid, and related daily overhaul should be intelligently reminded and delayed.
3) When the precipitation amount of a certain area exceeds a certain amount, the area where the equipment belongs is likely to be immersed through the equipment history data, and intelligent reminding is carried out for early protection.
4) The power outage schedule may be temporarily added.
And interfacing with an OMS system of the distribution network, and issuing a power failure plan after confirmation of a manager. The risk points in the execution process of the power outage plan are issued and circulated together with the power outage plan.
Based on the embodiment of fig. 1-2, in the step S5, the automatic checking balance performs weighted risk assessment by using repeated power outage of the device, out-of-limit of the dispatching bearing capacity, conflict of power-saving tasks, standard exceeding of the number of users in single power outage and repeated power outage of the user as indexes, so as to obtain a risk checking result.
The step S5 further includes: generating a power failure risk analysis report and giving an adjustment suggestion based on an AI check engine;
the step S6 further includes: and simulating the operation recovery result of the distribution network equipment after the regulated distribution network power failure maintenance plan is executed through the AI check engine.
More specific details of the flow may be found in the embodiment of fig. 3.
Based on fig. 3, the embodiment utilizes an artificial intelligence technology to realize intelligent analysis of power supply capacity of the distribution network, balance on-line power outage plans, intelligent arrangement of distribution network modes, intelligent generation and execution of one-key distribution network to power supply plan, optimal power supply path decision making, conversion of traditional operation mode management to an artificial intelligence direction and improvement of distribution network regulation and control operation management efficiency.
When the power failure plan is submitted, the full-element risk check of the plan can be automatically completed, and the existing risk is displayed in real time. The risk check is mainly carried out from two dimensions of safe and reliable power grid and high-quality service of clients, and the full factors of the power outage plan risk are deeply summarized, so that 8 core factors such as repeated power outage of equipment, out-of-limit dispatching bearing capacity, power protection task conflict, out-of-limit number of units in single power outage, repeated power outage of users and the like are used, and the power outage risk is accurately identified. And the power failure risk is classified as an early warning grade according to different risk influence degrees.
The checking result of the power failure plan is free of risk, and the plan is automatically effective; if the plan is at risk, the on-line approval of the relevant responsibility units is required to be effective. The risk types are equipment safety and the number of users, the power failure risk is caused for the users, the out-of-limit dispatch bearing capacity is signed by the related departments, and approval is determined by the dispatch departments according to the risk level and the like.
Specifically, the outage risk value f is quantified by:
f＝λ 1 f s +λ 2 f m
wherein lambda is 1 、λ 2 Is an adjustable weight parameter; lambda (lambda) 1 +λ 1 ＝1，λ 1 、λ 2 ∈(0，1)；
d i The initial value is 1; d, repeating the power failure of the equipment once i Self-increasing 1; each self-increment generates a d i ；
M i The initial value is the standard number of the users in single power failure, and M is the number of the users exceeding the standard once in single power failure i Self-increasing 1; each self-increment generates one M i ；
T is the upper limit value of the dispatching bearing capacity;
C i to preserve the power task conflict value, the initial value is 1, and when a conflict is detected, the conflict is increased by 0.5 (because the conflict involves two parties), and each time, the self-increase generates C i ；
f s Embodying the dimension of customer premium services, f m The dimension of safety and reliability of the power grid is embodied.
Based on the steps S5 and S6, the application also provides a quantitative evaluation method for the distribution network power outage overhaul plan.
Power outage plan declaration initiation
And providing a plurality of power failure equipment selection modes such as automatic association of defective equipment, equipment list selection, primary wiring diagram selection and the like. The generation of the annual schedule, and the generation of the monthly schedule may be selected.
1) Defect equipment is automatically associated with: the information of the butt joint defect flow (or log) is compared with the equipment in the current existing power outage plan, the equipment which is not listed in the power outage plan is found, and the joining of the power outage plan is automatically recommended;
2) List of devices selection: obtaining a device list by interfacing with an EMS system, selecting power failure devices through the device list, supporting screening and fuzzy query of a transformer substation (circuit) to which the devices belong, and supporting initial searching during screening and query;
3) Primary wiring diagram selection: automatically butting wiring diagrams and current running states of systems such as EMS and the like, and displaying the electrified coloring state of equipment; the power failure equipment is selected by the dot pattern on the basis.
4) Aiming at the declared equipment, tripping, grounding and non-stop recording of the corresponding line within one year are automatically pushed for maintenance planning content arrangement and fault cause analysis reference.
Repeated power outage equipment inspection
Based on the topological relation and the running state of the equipment, the power supply path of the equipment is analyzed, the equipment in the power outage plan list is subjected to overall analysis, whether the power supply relation exists between the equipment to be powered off or not is identified, and maintenance work with the power supply relation is combined, so that repeated power outage is avoided.
Power outage risk analysis report
1) Meanwhile, the power failure equipment is grouped: adding equipment with crossed time ranges into a group according to equipment contained in a power outage plan and the time for planning maintenance;
2) The DAS system is in butt joint, and exploration analysis is carried out based on a load transfer strategy of the power failure equipment group: analyzing initial power failure equipment and power flow distribution by taking equipment set in a power failure equipment group and power failure as an initial operation mode of load transfer strategy analysis; on the basis, based on topology analysis, possible load transfer strategies of power failure equipment and overload equipment are analyzed, and strategies corresponding to all points to be processed are combined to form a series of strategy combinations;
3) The DAS analyzes information of influences (power outage scope and power flow distribution) caused by different transfer strategies and returns the information: and aiming at different strategy combinations, integrally analyzing the recovery result of the power failure equipment and the power flow adjustment result of the heavy overload equipment, summarizing information such as load which cannot be recovered to transmit power finally, heavy overload condition and the like, and directly filtering the condition that the load rate exceeds a certain limit value according to a power flow control target.
4) And generating a power outage analysis report according to the power outage plan content through power outage plan checking.
Scheduling constraint checking
Based on the planning constraint logic library, the planning result is checked, and the above-mentioned checking of 7 constraint conditions is specifically referred to, and will not be repeated here.
Power outage plan distribution
And (5) interfacing with the distribution network OMS system, and issuing a power failure plan after confirming the mode personnel. The risk points in the execution process of the power outage plan are issued and circulated together with the power outage plan.
Fig. 4 illustrates the above flow further separated by a modular form, wherein the AI check engine is the execution core.
Fig. 5 is a block diagram of a system for automatically checking balance of a distribution network outage service plan that performs the method of fig. 1 or 2.
In fig. 5, the system includes a device topology map generation module, a repeat blackout device inspection module, a defective device auto-association module, a constraint condition input module, and a blackout plan auxiliary adjustment module,
the system also includes an AI check engine;
the equipment topological graph generation module is used for generating an equipment topological graph after acquiring all equipment in the power outage overhaul plan range of the distribution network;
the repeated power failure equipment checking module analyzes the power supply path of the equipment based on the equipment topological graph, integrally analyzes the power failure equipment in the power failure maintenance plan, identifies whether a power supply relation exists between the equipment to be powered off, and merges the equipment to be powered off with the power supply relation;
the automatic association module of the defect equipment acquires log flow information of all equipment within the current distribution network power outage overhaul plan, compares the log flow information with power outage equipment in the current distribution network power outage overhaul plan after determining the defect equipment information based on the log flow information, and automatically recommends to join in the power outage overhaul plan if the equipment which is not listed in the power outage overhaul plan is found;
the constraint condition input module is used for setting time constraint, equipment constraint, frequency constraint, dual-power user constraint, non-stop constraint and scheduling workload constraint;
the AI check engine executes automatic check balance on the power failure maintenance plan based on the equipment topological graph, the defect equipment information and the constraint condition to obtain a risk check result;
the power failure plan auxiliary adjustment module reminds risk points which are not passed by checking based on risk checking results and risks caused by the power failure plan found in the constraint condition checking process, and assists operators to carry out targeted adjustment on the power failure plan.
More specifically, the constraint condition input module includes:
holiday time constraint input sub-module: in the configured holiday time period input by the holiday time constraint input submodule, not allowing the power failure plan to be executed;
double power supply user constraint submodule: the system is used for establishing a double-power-supply user table, the double-power-supply power supply circuits of the same user cannot be powered off at the same time, when an overhaul plan is intelligently arranged, the system automatically searches the circuit information in the double-power-supply user table, checks the circuit information with power-off equipment in all power-off plans, and if conflict exists, gives a prompt, and displays alarm information and use constraint rules;
the non-stop constraint sub-module: establishing an equipment table which can not be stopped simultaneously aiming at the line equipment which is arranged on the same tower and is double-circuit line and the same pole;
scheduling workload constraint sub-module: for the same scheduling institution, an upper scheduling workload limit per day or per hour is set.
The system shown in fig. 5 further comprises a power outage overhaul plan importing module and a visual reporting module;
the power outage overhaul plan importing module is used for importing an initial version of power outage overhaul plan;
the visual report module is used for visually showing the risk points in the execution process of the distribution network power outage overhaul plan after adjustment.
In particular, the visualization architecture is shown in FIG. 6.
In fig. 6, by using an artificial intelligence technology, intelligent analysis of power supply capacity of the distribution network is realized, on-line power outage planning is balanced, a distribution network mode is intelligently arranged, intelligent generation and execution of a one-key distribution network to power supply scheme are provided, an optimal power supply path decision is provided, traditional operation mode management is converted into an artificial intelligence direction, and distribution network regulation and control operation management efficiency is improved.
In conclusion, the compliance of the overhaul plan is checked intelligently through the AI, so that omission caused by manual statistics is reduced, and the time consumption of the plan balancing work is greatly shortened. The plan reports the rapid circulation on the balance line, reserves sufficient time for the plan to be implemented specifically for working early preparation, and effectively improves the working efficiency.
The various steps of the above-described method of the present invention may be automated in the form of computer program instructions.
Accordingly, further embodiments provide an apparatus for automatically checking balance of a distribution network outage overhaul plan, the apparatus comprising a processor and a memory, the memory having stored thereon computer executable program instructions, the executable program instructions being executable by the processor for carrying out the foregoing method steps.
Referring to fig. 7, further embodiments may also be represented as a portable automatic balance checking terminal, where the terminal includes a processor, a memory, and an AI check engine, where the memory stores data execution flow instructions, and the AI check engine cooperates with the processor to execute the data execution flow instructions, so as to implement all steps of the method for automatically checking balance of a distribution network outage overhaul plan.
Further embodiments are realized as a computer medium having stored thereon computer program instructions for implementing all the steps of the method for automatically checking balance of a distribution network outage overhaul plan by executing the program instructions.
Further embodiments are implemented as a computer program product, the program product being loaded onto a computer readable storage medium, the program being executed by a processor, thereby implementing all the steps of the method for automatically checking balance of a distribution network outage overhaul plan.
Aiming at the problems that related constraint conditions in the prior art need manual statistics and verification, omission is easy to occur manually, and a final plan can be determined by calling a plurality of professional balance parties, the time consumption is long, and the early preparation work of the plan implementation is delayed. After the risk check is successful, the power failure plans are summarized, released and synchronously pushed to the distribution network OMS system, and on-line rapid flow is converted into plan concrete implementation to reserve sufficient time for working early-stage preparation, so that the working efficiency can be effectively improved.
The foregoing is merely a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and variations may be made to the present application by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.
While the foregoing description of the embodiments of the present application has been presented in conjunction with the drawings, it should be understood that it is not intended to limit the scope of the application, but rather, it is intended to cover all modifications or variations which may be resorted to without undue burden to those skilled in the art, having the benefit of the present application.
Claims (6)
1. The quantitative evaluation method for the distribution network power failure overhaul plan is characterized by comprising the following steps of:
performing automatic checking and balancing on the power failure maintenance plan based on the equipment topological graph, the defect equipment information and the constraint condition to obtain a risk checking result;
adjusting the distribution network power outage overhaul plan based on the risk check result;
the risk checking result comprises a power failure risk value f, and the power failure risk value f is quantified in the following manner:
f＝λ 1 f s +λ 2 f m
wherein lambda is 1 、λ 2 Is an adjustable weight parameter; lambda (lambda) 1 +λ 1 ＝1，λ 1 、λ 2 ∈(0，1)；
d i The initial value is 1; d, repeating the power failure of the equipment once i Self-increasing 1; each self-increment generates a d i ；
M i The initial value is the standard number of the users in single power failure, and M is the number of the users exceeding the standard once in single power failure i Self-increasing 1; each self-increment generates one M i ；
T is the upper limit value of the dispatching bearing capacity;
C i to preserve the power task conflict value, the initial value is 1, and when a conflict is detected, the conflict is self-increased by 0.5, because the conflict involves two parties, each self-increase generates C i ；
f s Embodying the dimension of customer premium services, f m The dimension of safety and reliability of the power grid is embodied. .
2. The distribution network outage overhaul plan quantitative evaluation method according to claim 1, wherein the method comprises the following steps of:
the constraint conditions include time constraint, equipment constraint, frequency constraint, dual power user constraint, non-co-stop constraint and scheduling workload constraint.
3. The distribution network outage overhaul plan quantitative evaluation method according to claim 2, wherein the method comprises the following steps of:
the method for automatically checking balance further comprises the following steps: and generating a power outage risk analysis report and giving an adjustment suggestion based on the AI check engine.
4. The distribution network outage overhaul plan quantitative evaluation method according to claim 3, wherein the method comprises the following steps of:
the AI check engine performs the check algorithm as follows:
holiday time constraint: when the maintenance plan is intelligently arranged, the system automatically executes a holiday constraint checking function, automatically adjusts the maintenance plan time with conflict, and displays adjustment detail data and use constraint rules;
available time period constraint checking: when the overhaul plan is intelligently arranged, the system automatically executes an available time period constraint checking function, automatically adjusts the conflict overhaul plan time, and displays adjustment detail data and use constraint rules;
important equipment and electricity-keeping user constraint checking: when the overhaul plan is intelligently arranged, the system automatically executes an important equipment constraint checking function, automatically adjusts the conflict overhaul plan time, and displays adjustment detail data and use constraint rules;
checking power failure frequency constraint: automatically collecting data of historical power outage records of power outage users in two months in a power outage scheme, and automatically reminding the situation that the power outage frequency is too high so as to provide reference for customer complaint management and control and power supply reliability;
dual power user constraints: when the maintenance plan is intelligently arranged, the system automatically retrieves the line information in the dual-power user table, checks the line information with power failure equipment in all power failure plans, and gives and prompts, and displays alarm information and use constraint rules if conflict exists;
non-co-stop constraint: when the maintenance plan is intelligently arranged, the system automatically searches the line information in the equipment table which can not be stopped together, checks the line information with the power failure equipment in all the power failure plans, and gives a prompt and displays alarm information and a use constraint rule if conflict exists;
scheduling workload constraints: when the overhaul plan is intelligently arranged, the system automatically executes a scheduling workload constraint checking function, and if conflict exists, alarm information and using constraint rules are displayed for prompt.
5. The distribution network outage overhaul plan quantitative evaluation method according to any one of claims 1 to 4, wherein the method comprises the following steps of:
and the risk checking result divides the power failure risk into early warning grades according to different risk influence degrees.
6. The quantitative evaluation method for the distribution network outage overhaul plan according to claim 5, wherein the quantitative evaluation method is characterized by comprising the following steps of:
the checking result of the power failure plan is free of risk, and the plan is automatically effective; if the plan is at risk, the on-line approval of the relevant responsibility units is required to be effective.
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| CN104992307B (en) * | 2015-08-10 | 2018-08-24 | 国网上海市电力公司 | A kind of power distribution network risk collaboration managing and control system |
| CN110020752B (en) * | 2019-04-03 | 2021-06-25 | 国网江苏省电力有限公司电力科学研究院 | Data acquisition optimization method, device, equipment and storage medium of multi-parameter monitoring device |
| US11277431B2 (en) * | 2019-06-27 | 2022-03-15 | Forescout Technologies, Inc. | Comprehensive risk assessment |
| CN112561248A (en) * | 2020-11-27 | 2021-03-26 | 国电南瑞南京控制系统有限公司 | Intelligent analysis and control method and system for power failure plan of main and distribution network dispatching |
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| CN113850693A (en) * | 2021-09-28 | 2021-12-28 | 国网重庆市电力公司铜梁供电分公司 | Distribution network power failure risk comprehensive assessment and early warning method based on multi-source information fusion |
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