CN115622033B - Intelligent self-healing method for power grid after extreme precipitation disaster - Google Patents
Intelligent self-healing method for power grid after extreme precipitation disaster Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for AC mains or AC distribution networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for AC mains or AC distribution networks
- H02J3/007—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources
- H02J3/0075—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources for providing alternative feeding paths between load and source according to economic or energy efficiency considerations, e.g. economic dispatch
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for AC mains or AC distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/388—Islanding, i.e. disconnection of local power supply from the network
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
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Abstract
本发明公开了一种极端降水灾害后的电网智能自愈方法。本发明包括以下步骤：S1：监测电网拓扑中各级设备的数据，统计受灾设备；S2：以设备的地理位置结合设备所处的电网拓扑位置，确定故障路径，划分待自愈区域；S3：将待自愈区域孤岛化运行，统计待自愈区域内的多类型能源储能分布情况，制定区域内自愈计划；S4：区域内自愈完成后，重新统计电网受极端降水灾害情况，根据电网拓扑中所有资源的分布，制定电网拓扑协同自愈计划；S5：在限定时间后，判断电网自愈情况；若未完成自愈，则更新电网受极端降水灾害情况后，重新制定自愈计划。虑到极端降水对实际地理路径的影响以及电力传输路径的影响，保证自愈计划的可靠实时。
The invention discloses an intelligent self-healing method for power grid after extreme precipitation disaster. The invention includes the following steps: S1: Monitor the data of equipment at all levels in the power grid topology, and count the disaster-stricken equipment; S2: Determine the fault path based on the geographical location of the equipment combined with the topological location of the power grid where the equipment is located, and divide the area to be self-healed; S3: Operate the area to be self-healed in an isolated manner, count the distribution of multiple types of energy storage in the area to be self-healed, and formulate a self-healing plan in the area; S4: After the self-healing in the area is completed, re-calculate the extreme precipitation disasters of the power grid. According to Based on the distribution of all resources in the power grid topology, formulate a collaborative self-healing plan for the power grid topology; S5: After a limited time, determine the self-healing situation of the power grid; if self-healing is not completed, update the power grid's extreme precipitation disaster situation and re-formulate a self-healing plan. . Taking into account the impact of extreme precipitation on actual geographical paths and power transmission paths, the self-healing plan is guaranteed to be reliable and real-time.
Description
Technical Field
The application relates to the field of self-healing after power grid disaster, in particular to an intelligent self-healing method for a power grid after extreme rainfall disaster.
Background
In recent years, extreme weather frequencies and intensities have increased significantly due to global warming. The strong precipitation occurs in many places in China, and the method has long duration, large accumulated rainfall, concentrated period and extreme performance. Due to shortage of urban space resources, power equipment such as cables, power transformation equipment, power distribution equipment and the like are gradually transferred to the ground. Urban frequent water logging events in underground distribution/transformation houses and cable wells are affected by extreme rainfall. The electric power equipment is soaked in the accumulated water, so that flashover discharge, short circuit fault and even tripping of the insulating part of the equipment are caused, large-area power failure is caused, electric leakage is easy to occur, personal injury is caused, and heavy rainfall and waterlogging are becoming important hidden hazards of electric power safety. The complete power grid security defense framework comprises links of disaster prevention, disaster reduction, disaster relief and the like, and the post-disaster intelligent self-healing of the power grid is one of important means of disaster relief.
Currently, there are some control methods for self-healing of a power grid, for example, an "urban power distribution network self-healing control method" disclosed in chinese patent literature, the publication number CN101436780B of which includes the following steps: (1) Defining a system state function related to voltage, current, active power, reactive power and frequency, and setting an emergency state function value, a recovery state function value, an abnormal state function value, an alert state function value and a safety state function value range; (2) collecting electrical quantity parameters; (3) Calculating the function value of the state function, respectively comparing the function value with the system set state function value, and transferring the related control processing step according to the comparison result; (4) emergency control processing; (5) resuming the control process; (6) correction control processing; (7) preventive control treatment.
The method is simple in model, dynamic behaviors of the power distribution network are difficult to comprehensively reflect, and influence factors caused by extreme rainfall disasters in the self-healing process of the power grid are not considered.
Disclosure of Invention
The method mainly solves the problems that the self-healing method in the prior art is simple in model, dynamic behaviors of the power distribution network are difficult to comprehensively reflect, and influence factors caused by extreme rainfall disasters in the self-healing process of the power grid are not considered; the intelligent self-healing method for the power grid after the extreme precipitation disaster is provided, a fault path is determined, a self-healing area is divided, self-healing in the area and collaborative self-healing in an interval are sequentially completed, and post-disaster self-healing of the power grid is achieved.
The technical problems of the application are mainly solved by the following technical proposal:
an intelligent self-healing method for a power grid after extreme precipitation disasters comprises the following steps:
s1: monitoring data of all levels of equipment in the power grid topology, and counting disaster-receiving equipment of the power grid subjected to extreme rainfall disasters;
s2: combining the geographic position of the equipment with the topological position of the power grid where the equipment is positioned, determining a fault path according to the extreme rainfall disaster condition of the power grid, and dividing the area to be self-healed;
s3: island operation is carried out on the area to be self-healed, multi-type energy storage distribution conditions in the area to be self-healed are counted, and a self-healing plan in the area is formulated;
s4: after the self-healing in the area is completed, the condition that the power grid receives extreme rainfall disasters is counted again, and a power grid topology cooperative self-healing plan is formulated according to the distribution of all resources in the power grid topology;
s5: after the limiting time, judging the self-healing condition of the power grid; if the self-healing is not completed, the self-healing plan is made again after the situation that the power grid receives extreme rainfall disasters is updated.
According to the scheme, the influence of extreme precipitation on an actual geographic path and the influence of an electric power transmission path are considered, the fault path is determined, the area is divided, the self-healing plan is guaranteed to be reliable and real-time, the consideration factors are more comprehensive, and the influence of extreme precipitation disasters on the self-healing of the power grid is reduced. And the intra-interval self-healing and the inter-interval collaborative self-healing are sequentially executed, so that the trans-regional resource transmission is reduced, the influence of extreme disasters on resource transportation is avoided, and the influence of the self-healing process on other normal equipment is reduced.
Preferably, the step S1 includes the steps of:
s101: monitoring power grid data after extreme precipitation disasters of all levels of equipment in a power grid topology in real time, and collecting the detected power grid data to a head-end equipment by all levels of equipment;
s102: the power grid data of each level of equipment are respectively compared with a rated operation threshold range, a lowest operation threshold range and a fault range threshold value, and the state of the corresponding equipment is determined;
s103: and taking all subordinate devices in the power grid topology of the equipment with the state judged to be the fault as disaster-stricken devices.
When the head equipment cannot receive the detection data, the equipment and the subordinate equipment in the topology are considered to be disaster-affected equipment, and the association influence among the equipment is reflected.
Preferably, the step S2 includes the following steps:
s201: marking all levels of equipment on a map based on the map, and dividing the corresponding influence range of all levels of equipment;
s202: taking the sum of the influence ranges of related disaster-stricken devices on the same power grid topological path as a disaster-stricken area;
s203: and (3) taking a transportation path and an electric power transmission path obstacle brought by an extreme precipitation disaster as a fault path, taking the fault path as a dividing limit, and finely dividing each disaster-affected area into a plurality of areas to be self-healed.
The influence of extreme precipitation on the actual geographical path and the influence of the power transmission path are considered, the fault path is determined, the area is divided, the reliability and the real time of the self-healing plan are guaranteed, the consideration factors are more comprehensive, and the influence of the extreme precipitation disaster on the self-healing of the power grid is reduced.
Preferably, the fault path confirming process is as follows:
a1: judging the number of fault devices existing in the same disaster-stricken area; if only the head equipment of the equipment topology in the disaster area is the fault equipment, performing obstacle judgment of the transportation path in the step A3; otherwise, performing obstacle judgment of the power transmission path in the step A2;
a2: the fault judgment of the power transmission path is carried out, the topological positions of all fault devices in the same disaster-affected area are obtained, and the transmission path from each level of fault device to the next level of equipment is taken as the power transmission path fault;
a3: and judging the transportation path faults, collecting road ponding information, comparing the road ponding information with a ponding passing threshold value, judging whether the trafficability of a road is judged, and taking a path with the ponding depth being more than or equal to the ponding passing threshold value as the transportation path faults.
The influence of extreme precipitation on the actual geographical path and the influence of the power transmission path are considered, the reliable real-time of the self-healing plan is guaranteed, the consideration factors are more comprehensive, and the influence of extreme precipitation disasters on the self-healing of the power grid is reduced.
Preferably, the step S3 includes the following steps:
s301: isolating topological head equipment in each area to be self-healed from superior equipment to realize island operation of the area to be self-healed;
s302: counting the storage amount of each type of energy source in the area to be self-healed;
s303; and according to the positions of topological head devices in each to-be-healed area in the whole power grid topology, starting from the to-be-healed area where the lowest-level device is positioned, and sequentially executing the in-area self-healing.
Island isolation self-healing reduces resource scheduling among areas and improves self-healing efficiency.
Preferably, the in-zone self-healing process is:
using energy reserves of various types in the area to be self-healed to keep the lowest working condition operation for the equipment in the area to be self-healed;
and updating the residual energy reserve quantity and the estimated use time of each area to be self-healed with fixed frequency until the fault equipment is recovered, and returning to the step S2 to repartition the area to be self-healed.
The self-healing of the power grid is carried out by eliminating the power grid which can be self-sufficient at all levels and carrying out island self-healing, and the self-healing of the power grid is carried out by other energy scheduling stored by the source network load, so that the disaster influence is not enlarged, the dynamic adjustment is ensured, and the energy scheduling efficiency is improved.
Preferably, the step S4 includes the following steps:
s401: acquiring an intra-area self-healing result of each area to be healed, judging whether equipment in the area at the current moment can operate under the lowest working condition, if so, ending after acquiring residual energy reserves and estimating the service time; otherwise, go to step S402;
s402: and calculating a collaborative self-healing recovery chain according to the maintenance importance, the equipment association degree and the recovery cost weight of the fault equipment in the current self-healing area.
Preferably, the collaborative self-healing recovery chain calculates collaborative recovery priority of each area to be self-healed, and the calculation process of the priority is as follows:
wherein Y (i) is the priority score of the ith interval to be self-healed;
A ij the area occupied by the j electricity type in the i-th interval to be self-healed is the area occupied by the j electricity type;
W j importance coefficients for the j-th electricity type;
j is the total number of electricity consumption types;
S in the state coefficient of the nth self-healing interval where the subordinate equipment of the equipment in the ith self-healing interval is located; if R is cn > 0, then S in Taking +1; if R is cn S is less than or equal to 0 in Taking-1;
R cn the remaining energy reserve of the nth to-be-self-healed area where the subordinate equipment is located;
k Tn a predicted use time coefficient for the residual energy reserve of the nth to-be-self-healed area where the subordinate equipment is located; when the estimated use time is greater than or equal to the set use threshold value, k Tn Taking 1, otherwise taking 0;
n is the total number of the areas to be self-healed where the subordinate equipment is located;
L i the resource transmission path length of the self-healing process of the ith area to be self-healed;
k d cost coefficients of the resource transmission path;
and sequencing from big to small according to the priority scores, and sequentially cooperating with self-healing according to the priority scores.
And planning the sequence of self-healing according to the priority, and ensuring the maximization of benefits.
Preferably, the recovery time is respectively limited for the self-healing plan in the area and the grid topology cooperative self-healing plan;
executing the power grid topology cooperative self-healing plan after the self-healing plan in the area reaches the limited recovery time;
judging whether the equipment operation condition of the whole power grid topology reaches the lowest operation condition after the power grid topology is cooperated with the self-healing plan to reach the limited recovery, if so, continuing to execute the next period; otherwise, returning to the step S3 to re-execute the self-healing planning.
And judging whether the formulated self-healing plan is reasonable or not by executing the recovery time, so that the self-healing plan is updated by feedback, and the self-healing efficiency is improved.
Preferably, the limit recovery time of the grid topology collaborative self-healing plan is obtained by weighting and calculating the disaster condition of the grid, the working condition of each energy source type and the association degree:
wherein ,TiL Defining recovery time for the grid topology collaborative self-healing plan of the ith self-healing area;
E ig the g energy working condition in the i self-healing area is the g energy working condition;
E mg the g energy working condition in the i self-healing area is the g energy working condition;
g is the total energy;
G im for the ith self-healing area and the mth self-healing areaCorrelation coefficients of the regions;
D i the disaster situation of the power grid in the ith self-healing area is determined;
t is the time base.
The beneficial effects of the application are as follows:
1. the influence of extreme precipitation on the actual geographical path and the influence of the power transmission path are considered, the fault path is determined, the area is divided, the reliability and the real time of the self-healing plan are guaranteed, the consideration factors are more comprehensive, and the influence of the extreme precipitation disaster on the self-healing of the power grid is reduced.
2. And the intra-interval self-healing and the inter-interval collaborative self-healing are sequentially executed, so that the trans-regional resource transmission is reduced, the influence of extreme disasters on resource transportation is avoided, and the influence of the self-healing process on other normal equipment is reduced.
3. And judging whether the formulated self-healing plan is reasonable or not by executing the recovery time, so that the self-healing plan is updated by feedback, and the self-healing efficiency is improved.
Drawings
Fig. 1 is a flow chart of an intelligent self-healing method of a power grid after extreme precipitation disasters.
Detailed Description
The technical scheme of the application is further specifically described below through examples and with reference to the accompanying drawings.
Examples:
the intelligent self-healing method for the power grid after the extreme precipitation disaster in the embodiment is shown in fig. 1, and comprises the following steps:
s1: and monitoring data of all levels of equipment in the power grid topology, and counting disaster-receiving equipment of the power grid subjected to extreme rainfall disasters.
S101: and monitoring the power grid data of all levels of equipment after extreme precipitation disasters in the power grid topology in real time, and collecting the detected power grid data transmission to the head-end equipment by all levels of equipment.
The grid data includes generator power angle, bus voltage phase angle, line active, reactive, voltage and frequency. If the monitoring equipment cannot monitor the corresponding power grid working condition parameters, the transmission data is 0, and then serious faults are judged.
In this embodiment, a data processing center is set at a headend device of the power grid topology, and the monitoring device uses a global satellite positioning system synchronous clock to measure working condition parameters of the power grid in real time on line, and transmits the working condition parameter data of the power grid in real time at high speed through digital microwaves and other devices.
S102: and comparing the power grid data of each level of equipment with a rated operation threshold range, a lowest operation threshold range and a fault range threshold respectively, and determining the state of the corresponding equipment.
The data processing center collects working condition parameters such as generator power angle, bus voltage phase angle and line active, reactive, voltage and frequency of each level of power grid, and draws a dynamic change waveform chart by taking time as a horizontal axis. The threshold comparison is used for respectively comparing the normal operation state data, the lowest operation state data and the fault operation state data in the historical database, and judging disaster conditions of all levels of power grids in sequence, wherein the disaster conditions comprise whether equipment fails or not, the failure type and the minimum work requirement of the load can be maintained.
And comparing the relative power angle of the generator and the relative phase of the bus with the data of the normal running state, judging the fault when the data range is different from the threshold data range, and otherwise judging the fault as normal.
And comparing the current state with the lowest running state data to judge the lowest working requirement that the current state can maintain the load, and if not, improving the maintenance importance of the current power grid.
And comparing the data with fault operation state data, and matching the data with highest similarity to determine the fault type.
S103: and taking all subordinate devices in the power grid topology of the equipment with the state judged to be the fault as disaster-stricken devices.
When the head equipment cannot receive the detection data, the equipment and the subordinate equipment in the topology are considered to be disaster-affected equipment, and the association influence among the equipment is reflected.
S2: and determining a fault path according to the extreme rainfall disaster condition of the power grid by combining the geographical position of the equipment with the topological position of the power grid where the equipment is positioned, and dividing the area to be self-healed.
S201: and marking all levels of equipment on the map based on the map, and dividing the corresponding influence range of all levels of equipment.
S202: and taking the sum of the influence ranges of related disaster-stricken devices on the same power grid topological path as a disaster-stricken area.
S203: and (3) taking a transportation path and an electric power transmission path obstacle brought by an extreme precipitation disaster as a fault path, taking the fault path as a dividing limit, and finely dividing each disaster-affected area into a plurality of areas to be self-healed.
The fault path confirming process comprises the following steps:
a1: judging the number of fault devices existing in the same disaster-stricken area; if only the head equipment of the equipment topology in the disaster area is the fault equipment, performing obstacle judgment of the transportation path in the step A3; otherwise, performing obstacle judgment of the power transmission path in the step A2;
a2: the fault judgment of the power transmission path is carried out, the topological positions of all fault devices in the same disaster-affected area are obtained, and the transmission path from each level of fault device to the next level of equipment is taken as the power transmission path fault;
a3: and judging the transportation path faults, collecting road ponding information, comparing the road ponding information with a ponding passing threshold value, judging whether the trafficability of a road is judged, and taking a path with the ponding depth being more than or equal to the ponding passing threshold value as the transportation path faults.
The influence of extreme precipitation on the actual geographical path and the influence of the power transmission path are considered, the reliable real-time of the self-healing plan is guaranteed, the consideration factors are more comprehensive, and the influence of extreme precipitation disasters on the self-healing of the power grid is reduced.
In this embodiment, the to-be-self-healed area refined by the fault path is further judged, if fault equipment exists in the to-be-self-healed area, if so, the to-be-self-healed area is reserved, otherwise, the to-be-self-healed area is removed.
S3: and carrying out island operation on the area to be self-healed, counting the energy storage distribution condition of multiple types of energy sources in the area to be self-healed, and making a self-healing plan in the area.
S301: and isolating topological head equipment in each area to be self-healed from superior equipment, and realizing island operation of the area to be self-healed.
S302: and counting the storage amount of each type of energy source in the area to be self-healed.
In this embodiment, the energy types include thermal power storage and thermal power generation capability, wind power storage, standby battery storage, hydroelectric power storage and hydroelectric power generation capability, solar power storage and solar power generation capability, and the like.
S303; and according to the positions of topological head devices in each to-be-healed area in the whole power grid topology, starting from the to-be-healed area where the lowest-level device is positioned, and sequentially executing the in-area self-healing.
The self-healing process in the area is as follows:
using energy reserves of various types in the area to be self-healed to keep the lowest working condition operation for the equipment in the area to be self-healed;
and updating the residual energy reserve quantity and the estimated use time of each area to be self-healed with fixed frequency until the fault equipment is recovered, and returning to the step S2 to repartition the area to be self-healed.
The self-healing of the power grid is carried out by eliminating the power grid which can be self-sufficient at all levels and carrying out island self-healing, and the self-healing of the power grid is carried out by other energy scheduling stored by the source network load, so that the disaster influence is not enlarged, the dynamic adjustment is ensured, and the energy scheduling efficiency is improved.
Island isolation self-healing reduces resource scheduling among areas and improves self-healing efficiency.
S4: and after the self-healing in the area is completed, the condition of the power grid under extreme rainfall disaster is reckoned, and a power grid topology cooperative self-healing plan is formulated according to the distribution of all resources in the power grid topology.
S401: acquiring an intra-area self-healing result of each area to be healed, judging whether equipment in the area at the current moment can operate under the lowest working condition, if so, ending after acquiring residual energy reserves and estimating the service time; otherwise, step S402 is entered.
S402: and calculating a collaborative self-healing recovery chain according to the maintenance importance, the equipment association degree and the recovery cost weight of the fault equipment in the current self-healing area.
The collaborative self-healing recovery chain calculates the collaborative recovery priority of each area to be self-healed, and the calculation process of the priority is as follows:
wherein Y (i) is the priority score of the ith interval to be self-healed;
A ij the area occupied by the j electricity type in the i-th interval to be self-healed is the area occupied by the j electricity type;
W j importance coefficients for the j-th electricity type;
j is the total number of electricity consumption types;
S in the state coefficient of the nth self-healing interval where the subordinate equipment of the equipment in the ith self-healing interval is located; if R is cn > 0, then S in Taking +1; if R is cn S is less than or equal to 0 in Taking-1;
R cn the remaining energy reserve of the nth to-be-self-healed area where the subordinate equipment is located;
k Tn a predicted use time coefficient for the residual energy reserve of the nth to-be-self-healed area where the subordinate equipment is located; when the estimated use time is greater than or equal to the set use threshold value, k Tn Taking 1, otherwise taking 0;
n is the total number of the areas to be self-healed where the subordinate equipment is located;
L i the resource transmission path length of the self-healing process of the ith area to be self-healed;
k d cost coefficients of the resource transmission path;
and sequencing from big to small according to the priority scores, and sequentially cooperating with self-healing according to the priority scores.
And planning the sequence of self-healing according to the priority, and ensuring the maximization of benefits.
S5: after the limiting time, judging the self-healing condition of the power grid; if the self-healing is not completed, the self-healing plan is made again after the situation that the power grid receives extreme rainfall disasters is updated.
And respectively limiting recovery time for the self-healing plan in the area and the grid topology collaborative self-healing plan.
And executing the grid topology collaborative self-healing plan after the self-healing plan in the area reaches the defined recovery time. In this embodiment, the defined recovery time of the intra-area self-healing plan is set according to a fixed frequency of updating the remaining energy reserve amount and the estimated use time.
Judging whether the equipment operation condition of the whole power grid topology reaches the lowest operation condition after the power grid topology is cooperated with the self-healing plan to reach the limited recovery, if so, continuing to execute the next period; otherwise, returning to the step S3 to re-execute the self-healing planning.
The limiting recovery time of the grid topology collaborative self-healing plan is obtained by weighted calculation of the disaster condition of the grid, the working condition of each energy source type and the association degree:
wherein ,TiL Defining recovery time for the grid topology collaborative self-healing plan of the ith self-healing area;
E ig the g energy working condition in the i self-healing area is the g energy working condition;
E mg the g energy working condition in the i self-healing area is the g energy working condition;
g is the total energy;
G im the association coefficient of the ith self-healing area and the mth self-healing area;
D i the disaster situation of the power grid in the ith self-healing area is determined;
t is the time base.
And judging whether the formulated self-healing plan is reasonable or not by executing the recovery time, so that the self-healing plan is updated by feedback, and the self-healing efficiency is improved.
According to the scheme of the embodiment, the influence of extreme precipitation on an actual geographic path and the influence of an electric power transmission path are considered, the fault path is determined, the area is divided, the self-healing plan is guaranteed to be reliable and real-time, the consideration factors are more comprehensive, and the influence of extreme precipitation disasters on the self-healing of the power grid is reduced. And the intra-interval self-healing and the inter-interval collaborative self-healing are sequentially executed, so that the trans-regional resource transmission is reduced, the influence of extreme disasters on resource transportation is avoided, and the influence of the self-healing process on other normal equipment is reduced.
It should be understood that the examples are only for illustrating the present application and are not intended to limit the scope of the present application. Furthermore, it should be understood that various changes and modifications can be made by one skilled in the art after reading the teachings of the present application, and such equivalents are intended to fall within the scope of the application as defined in the appended claims.
Claims (8)
1. The intelligent self-healing method for the power grid after extreme precipitation disaster is characterized by comprising the following steps of:
s1: monitoring data of all levels of equipment in the power grid topology, and counting disaster-receiving equipment of the power grid subjected to extreme rainfall disasters;
s2: combining the geographic position of the equipment with the topological position of the power grid where the equipment is positioned, determining a fault path according to the extreme rainfall disaster condition of the power grid, and dividing the area to be self-healed;
s3: island operation is carried out on the area to be self-healed, multi-type energy storage distribution conditions in the area to be self-healed are counted, and a self-healing plan in the area is formulated;
s4: after the self-healing in the area is completed, a grid topology cooperative self-healing plan is formulated according to the distribution of all resources in the grid topology;
s5: after the limiting time, judging the self-healing condition of the power grid; if the self-healing is not completed, after the condition that the power grid receives extreme rainfall disaster is updated, a self-healing plan is made again;
the step S4 comprises the following steps:
s401: acquiring an intra-area self-healing result of each area to be healed, judging whether equipment in the area at the current moment can operate under the lowest working condition, if so, ending after acquiring residual energy reserves and estimating the service time; otherwise, go to step S402;
s402: according to the maintenance importance, the equipment association degree and the recovery cost weight of the fault equipment in the current self-healing area, calculating a collaborative self-healing recovery chain;
the collaborative self-healing recovery chain calculates the collaborative recovery priority of each area to be self-healed, and the calculation process of the priority is as follows:
；
wherein ,the priority value of the ith interval to be self-healed is given;
the area occupied by the j electricity type in the i-th interval to be self-healed is the area occupied by the j electricity type;
importance coefficients for the j-th electricity type;
j is the total number of electricity consumption types;
the state coefficient of the nth self-healing interval where the subordinate equipment of the equipment in the ith self-healing interval is located; if it isThen->Taking +1; if->Then->Taking-1;
residual energy reserve for the nth self-healing zone in which the subordinate device is located；
A predicted use time coefficient for the residual energy reserve of the nth to-be-self-healed area where the subordinate equipment is located; when the estimated use time is greater than or equal to the set use threshold value, the user is given a +_>Taking 1, otherwise taking 0;
n is the total number of the areas to be self-healed where the subordinate equipment is located;
the resource transmission path length of the self-healing process of the ith area to be self-healed;
cost coefficients of the resource transmission path;
and sequencing from big to small according to the priority scores, and sequentially cooperating with self-healing according to the priority scores.
2. The intelligent self-healing method for the power grid after extreme rainfall disaster according to claim 1, wherein the step S1 comprises the following steps:
s101: monitoring power grid data after extreme precipitation disasters of all levels of equipment in a power grid topology in real time, and collecting the detected power grid data to a head-end equipment by all levels of equipment;
s102: the power grid data of each level of equipment are respectively compared with a rated operation threshold range, a lowest operation threshold range and a fault range threshold value, and the state of the corresponding equipment is determined;
s103: and taking all subordinate devices in the power grid topology of the equipment with the state judged to be the fault as disaster-stricken devices.
3. The intelligent self-healing method for power grid after extreme rainfall disaster according to claim 1 or 2, wherein the step S2 comprises the following steps:
s201: marking all levels of equipment on a map based on the map, and dividing the corresponding influence range of all levels of equipment;
s202: taking the sum of the influence ranges of the disaster-stricken devices which are mutually related on the same power grid topological path as a disaster-stricken area;
s203: and (3) taking a transportation path and an electric power transmission path obstacle brought by an extreme precipitation disaster as a fault path, taking the fault path as a dividing limit, and finely dividing each disaster-affected area into a plurality of areas to be self-healed.
4. The intelligent self-healing method for a power grid after extreme precipitation disaster according to claim 3, wherein the fault path confirmation process is as follows:
a1: judging the number of fault devices existing in the same disaster-stricken area; if only the head equipment of the equipment topology in the disaster area is the fault equipment, performing obstacle judgment of the transportation path in the step A3; otherwise, performing obstacle judgment of the power transmission path in the step A2;
a2: the fault judgment of the power transmission path is carried out, the topological positions of all fault devices in the same disaster-affected area are obtained, and the transmission path from each level of fault device to the next level of equipment is taken as the power transmission path fault;
a3: and judging the transportation path faults, collecting road ponding information, comparing the road ponding information with a ponding passing threshold value, judging whether the trafficability of a road is judged, and taking a path with the ponding depth being more than or equal to the ponding passing threshold value as the transportation path faults.
5. The intelligent self-healing method for power grid after extreme rainfall disaster according to claim 1 or 4, wherein the step S3 comprises the following steps:
s301: isolating topological head equipment in each area to be self-healed from superior equipment to realize island operation of the area to be self-healed;
s302: counting the storage amount of each type of energy source in the area to be self-healed;
s303; and according to the positions of topological head devices in each to-be-healed area in the whole power grid topology, starting from the to-be-healed area where the lowest-level device is positioned, and sequentially executing the in-area self-healing.
6. The intelligent self-healing method for the power grid after extreme rainfall disaster according to claim 5, wherein the self-healing process in the area is as follows:
using energy reserves of various types in the area to be self-healed to keep the lowest working condition operation for the equipment in the area to be self-healed;
and updating the residual energy reserve quantity and the estimated use time of each area to be self-healed with fixed frequency until the fault equipment is recovered, and returning to the step S2 to repartition the area to be self-healed.
7. The intelligent self-healing method for power grid after extreme rainfall disaster according to claim 1 or 6, wherein recovery time is defined for the self-healing plan in the area and the grid topology collaborative self-healing plan respectively;
executing the power grid topology cooperative self-healing plan after the self-healing plan in the area reaches the limited recovery time;
judging whether the equipment operation condition of the whole power grid topology reaches the lowest operation condition after the power grid topology is cooperated with the self-healing plan to reach the limited recovery, if so, continuing to execute the next period; otherwise, returning to the step S3 to re-execute the self-healing planning.
8. The intelligent self-healing method for the power grid after extreme rainfall disaster according to claim 7, wherein the limit recovery time of the power grid topology collaborative self-healing plan is obtained by weighting and calculating the disaster condition of the power grid, the working condition of each energy source type and the association degree:
；
wherein ,defining recovery time for the grid topology collaborative self-healing plan of the ith self-healing area;
the g energy working condition in the i self-healing area is the g energy working condition;
the g energy working condition in the m-th self-healing area;
g is the total energy;
the association coefficient of the ith self-healing area and the mth self-healing area;
the disaster situation of the power grid in the ith self-healing area is determined;
t is the time base.
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