CN111123975A - A planning method for UAV wireless charging station in power inspection area - Google Patents
A planning method for UAV wireless charging station in power inspection area Download PDFInfo
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Abstract
本发明公开了一种电力巡检区域内的无人机无线充电站规划方法，包括如下步骤：S1、确定巡检区域G以及巡检区域G内的变电站个数为M，变电站对应编号{M1，M2···Mj}；S2、确定无人机巡检线路的起始点P0以及终点Pz；S3、采用Fleury算法求解巡检区域G内的最优巡检路径；S4、计算最优巡检路径内的各个变电站与其相邻变电站之间距离{S1，S2···Sj}；S5、设定无人机的返航剩余电量w，计算返航剩余电量的可飞行距离N；S6、配置无线充电站。该方案通过制定录巡检区域内的最优巡检路线，在最优巡检路线上配置无线充电站，减少了无线充电站的搭建成本，显著提高了无人机巡检效率。The invention discloses a method for planning a wireless charging station for unmanned aerial vehicles in a power inspection area, comprising the following steps: S1. Determine the inspection area G and the number of substations in the inspection area G as M, and the corresponding number of the substations {M1 , M2...Mj}; S2, determine the starting point P0 and the end point Pz of the UAV inspection line; S3, use the Fleury algorithm to solve the optimal inspection path in the inspection area G; S4, calculate the optimal inspection The distance between each substation in the path and its neighboring substations {S1, S2... stand. This solution reduces the construction cost of the wireless charging station and significantly improves the inspection efficiency of the drone by formulating the optimal inspection route in the inspection area and configuring the wireless charging station on the optimal inspection route.
Description
Technical Field
The invention relates to the technical field of power inspection, in particular to a planning method for an unmanned aerial vehicle wireless charging station in a power inspection area.
Background
At present, electric power inspection gradually changes from a manpower inspection mode to unmanned aerial vehicle inspection, manpower inspection and manned helicopter inspection in a coordinated mode. Due to a plurality of limiting factors of the manned helicopter, the unmanned aerial vehicle inspection line has the advantages of no restriction of terrain environment, high cost and efficiency and the like, and is safer, and the combination of electric power line inspection and manpower line inspection of the unmanned aerial vehicle becomes the main trend of line inspection work in the power industry.
In recent years, with the increasing maturity of wireless charging technology, the technology mainly depends on magnetic field to transmit energy, can not cause accidents such as short circuit, fire and the like, and is safer and more convenient compared with the traditional wired charging. Although the wireless charging technology is rapidly developed, aiming at the long-distance motion operation characteristic of the line patrol unmanned aerial vehicle, if the wireless charging is carried out in the flying process, the energy transmission efficiency is greatly reduced. The existing line patrol unmanned aerial vehicle on the market has low cruising ability, the electric energy loss is accelerated under the conditions of high electric power line patrol height and high outdoor temperature, and the charging time is more than one hour. Mismatching of cruising ability and charging efficiency limits the flight time and flight distance of the unmanned aerial vehicle, and long-time line patrol tasks cannot be realized. At present, the traditional wired charging mode of patrolling unmanned aerial vehicle mainly adopted has two kinds: (1) the charging plug is directly inserted into the unmanned aerial vehicle for charging; (2) and taking out the battery in the unmanned aerial vehicle and inserting the battery into a special charger for charging. The battery is frequently changed manually, so that the labor cost is increased, and the continuity of line inspection work of the unmanned aerial vehicle is also destroyed. Patrol that line unmanned aerial vehicle is wireless to charge and can realize unmanned aerial vehicle station full automation and unmanned, save the manpower resources of unmanned aerial vehicle management, conveniently solved the problem that unmanned aerial vehicle can't long-distance patrol line flight for a long time intelligently. Considering the distance difference between the building cost of designing wireless charging station and the transformer substation, setting for the optimum route of patrolling and examining in patrolling and examining the region and to unmanned aerial vehicle's the promotion of patrolling and examining efficiency have an important meaning, consider the not strong realistic problem of current unmanned aerial vehicle duration, dispose wireless charging station on the optimum route of patrolling and examining, can furthest's reduction patrol and examine the cost and improve and patrol and examine efficiency.
Disclosure of Invention
The invention aims to solve the problem of low inspection efficiency of the existing unmanned aerial vehicle, and provides a planning method for a wireless charging station of the unmanned aerial vehicle in a power inspection area.
In order to achieve the technical purpose, the invention provides a technical scheme that the unmanned aerial vehicle wireless charging station planning method in the power inspection area comprises the following steps:
s1, determining the inspection area G and the number of substations in the inspection area G as M, wherein the substations correspond to the numbers { M1, M2 · · Mj };
s2, determining a starting point P0 and a terminal point Pz of the unmanned aerial vehicle routing inspection line;
s3, solving the optimal routing inspection path in the routing inspection area G by adopting a Fleury algorithm;
s4, calculating the distance { S1, S2 · Sj } between each substation in the optimal routing path and the adjacent substation;
s5, setting the return residual electric quantity w of the unmanned aerial vehicle, and calculating the flyable distance N of the return residual electric quantity;
and S6, configuring a wireless charging station.
Preferably, the substation number corresponding to the starting point P0 of the unmanned aerial vehicle routing inspection line is Mi, and the substation number corresponding to the end point Pz is Me, where Mi and Me are e (M1, Mj).
Preferably, the step of solving the shortest path of the routing inspection area by the fleey algorithm is as follows:
s31, optionally selecting v0 epsilon (M1, M2 & cndot.. Mj), and enabling P0= v 0;
s32, setting a path Pi = v0e1v1e2.. eivi, Pi denotes a routing inspection path traversing all substations in the power routing inspection area G, where ei is a power transmission line between substations, and e (i +1) is selected from e (G) - { e1, e2, e3,... ei }; the following determinations are made;
judgment 1: e (i +1) is associated with vi;
and (3) judgment 2: unless no other edge can be taken, e(i+1)Should not be Gi= G-{e1,e2,e3,...,eiA bridge in (c);
s33, stopping the algorithm when the step 2 can not be carried out; an optimal patrol line Pm = v0e1v1e2.
Preferably, the number T1= [ Sd/N ] of wireless charging stations built in adjacent substations is calculated according to the distance { S1, S2 · · Sj } determined in the step S4 and the flying distance N of the return residual electric quantity of the unmanned aerial vehicle in the step S5, and Sd ∈ (S1, Sj);
wherein [ Sd/N ] represents an integer part taking Sd/N.
Preferably, after the number T1 of the wireless charging stations in two adjacent substations is determined, the layout positions of the substations are set, the length Sd of the power inspection line is determined by the space connection line between the adjacent substations, the number of interval points on the inspection line is determined according to the number T1 of the wireless charging stations, the power inspection line ed is divided into uniform line segments by the interval points, and the distance between the line segments is Sd/(T1 + 1); at this time, one wireless charging station is provided for each spaced point.
Preferably, all substations in the inspection area G are provided with a wireless charging station.
Preferably, the wireless charging stations are internally provided with a positioning module and a communication module, and the unmanned aerial vehicles are in communication connection with the wireless charging stations to share the mutual position information.
The invention has the beneficial effects that:
(1) by designing an optimal routing inspection path in the routing inspection area, the unmanned aerial vehicle is prevented from repeatedly routing inspection, and the routing inspection efficiency is improved;
(2) a wireless charging station is planned on the routing inspection path, so that the charging problem on the routing inspection path of the unmanned aerial vehicle is guaranteed, the unmanned aerial vehicle is prevented from returning to the home to supplement electric energy, and the cruising ability of the unmanned aerial vehicle is obviously improved;
(3) and the unmanned aerial vehicle automatically patrols and charges automatically, so that the manual maintenance cost is reduced.
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Fig. 1 is a plan view of an optimal routing inspection line in an inspection area according to the present invention.
Detailed Description
For the purpose of better understanding the objects, technical solutions and advantages of the present invention, the following detailed description of the present invention with reference to the accompanying drawings and examples should be understood that the specific embodiment described herein is only a preferred embodiment of the present invention, and is only used for explaining the present invention, and not for limiting the scope of the present invention, and all other embodiments obtained by a person of ordinary skill in the art without making creative efforts shall fall within the scope of the present invention.
Example (b): an unmanned aerial vehicle wireless charging station planning method in a power inspection area comprises the following steps:
step S1, firstly, the inspection area G and the number of substations in the inspection area G are determined to be M, and the corresponding number of the substations is { M1, M2 · · Mj }.
And S2, determining a starting point P0 and a terminal point Pz of the unmanned aerial vehicle inspection line, wherein the number of a transformer substation corresponding to the starting point P0 of the unmanned aerial vehicle inspection line is Mi, the number of a transformer substation corresponding to the terminal point Pz is Me, and i and e belong to (1, j).
Step S3, because the total length of the route is fixed and the total route that the unmanned aerial vehicle needs to cruise has the minimum value, the general principle of the unmanned aerial vehicle route patrol route planning is to walk around the loop less, and therefore the route planning becomes a mathematical problem of drawing a pattern in one stroke; solving an optimal routing inspection path in the routing inspection area G by adopting a Fleury algorithm;
the steps of solving the shortest path of the routing inspection area by the Fleury algorithm are as follows:
step S31, optionally taking v0 epsilon (M1, M2 & cndot.. Mj), and enabling P0= v 0;
step S32, setting a path Pi = v0e1v1e2.. eivi, wherein Pi represents one routing inspection path traversing all substations in the power routing inspection area G, wherein ei is a power transmission line between the substations, and e (i +1) is selected from E (G) - { e1, e2, e3,... ei }; the following determinations are made;
judgment 1: e (i +1) is associated with vi;
and (3) judgment 2: unless no other edge can be taken, e(i+1)Should not be Gi= G-{e1,e2,e3,...,eiA bridge in (c);
step S33, when the step 2 can not be carried out, stopping the algorithm; an optimal patrol line Pm = v0e1v1e2.
Step S4, calculating the distance { S1, S2 · Sj } between each substation and the adjacent substation in the optimal routing path;
according to the position information of the transformer substations, the shortest distance { S1, S2 · · Sj } between each transformer substation and the adjacent transformer substations thereof can be calculated.
Step S5, setting the return residual electric quantity w of the unmanned aerial vehicle, and calculating the flyable distance N of the return residual electric quantity; the return electric quantity of the unmanned aerial vehicle can be set conventionally (for example, the wireless charging station can be found when the residual electric quantity is 10%), and can also be set according to the change of weather conditions (for example, the reverse wind speed of an inspection line is more than 10m/s, and the wireless charging station can be found when the residual electric quantity is 15%; calculating the number T1= [ Sd/N ] of wireless charging stations built in adjacent substations according to the distance { S1, S2 · · Sj } determined in the step S4 and the flying distance N of the return residual electric quantity of the unmanned aerial vehicle in the step S5, and enabling Sd ∈ (S1, Sj);
wherein [ Sd/N ] represents an integer part taking Sd/N.
Step S6, configuring a wireless charging station; the specific configuration principle is as follows:
all substations in the inspection area G are provided with a wireless charging station, the wireless charging stations are provided with a positioning module and a communication module, and the unmanned aerial vehicle is in communication connection with the wireless charging stations to share mutual position information; after the number T1 of wireless charging stations in two adjacent substations is determined, setting the layout positions of the substations, determining the length Sd of the power inspection line by the space connection line between the adjacent substations, determining the number of interval points on the inspection line according to the number T1 of the wireless charging stations, dividing the power inspection line ed into uniform line segments by the interval points, and setting the distance between the line segments as Sd/(T1 + 1); at this time, one wireless charging station is provided for each spaced point.
As shown in fig. 1, a method for specifying a specific optimal path in an inspection area includes the following steps:
setting that a transformer substation is arranged in a 220kV line in an urban area as follows: white X, long X, flower X, pond X, ascending X, yellow X, lake X, and button X. And the 220kV line is externally connected with a Hua X voltage reduction station (outside the area), a GaNX (outside the area), a Shi X (outside the area), a MoXx (outside the area), a cyan X (outside the area), a phoenix X (outside the area) and a big X (outside the area). And eliminating the patrol lines (such as X-to-Phoenix lines) which have to fly back and forth, and because the number of odd lines connected with the transformer substations is more than 2, the bridge is X-to-X long.
Taking X as a starting point and yellow X as an end point, according to the optimal route planning method, the optimal route patrol route is as follows: flower X first shuttles (path unknown) with Phoenix (out of zone), flower X to X (3.532 km), X with large X (out of zone) (path unknown), X with cyan X (out of zone) (path unknown), X to pool X (16.474km), pool X to ascending X (19.191km), ascending X to HuaX depressurization station (out of zone) (31.581km), HuaX depressurization station (out of zone) to white X (19.451km), white X to long X (19.447km), long X to X with X (16.086km), X to Tsu X (out of zone) (17.733km), Tsu X (out of zone) to long X (29.055km), long X to Tsu X (12.117km), Tsu X to Tsu X (out of zone) to shuttle (19.123km X2), Tsu X to X lake (15.245km), Tsu X to Wsu X (15.264km), yellow X to Tsu X (11.315X 2 km).
The above-mentioned embodiments are preferred embodiments of the method for planning a wireless charging station for an unmanned aerial vehicle in a power inspection area according to the present invention, and the scope of the present invention is not limited thereto, and all equivalent changes in shape and structure according to the present invention are within the scope of the present invention.
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| CN111930138A (en) * | 2020-07-06 | 2020-11-13 | 浙江浙能技术研究院有限公司 | Unmanned aerial vehicle path and charging pile distribution point optimization planning method for photovoltaic power station inspection |
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| CN111930138A (en) * | 2020-07-06 | 2020-11-13 | 浙江浙能技术研究院有限公司 | Unmanned aerial vehicle path and charging pile distribution point optimization planning method for photovoltaic power station inspection |
| WO2022077954A1 (en) * | 2020-10-14 | 2022-04-21 | 国防科技大学 | Unmanned aerial vehicle path planning method based on two charging modes |
| CN113110601B (en) * | 2021-04-01 | 2023-06-16 | 国网江西省电力有限公司电力科学研究院 | Unmanned aerial vehicle power line inspection path optimization method and device |
| CN113110601A (en) * | 2021-04-01 | 2021-07-13 | 国网江西省电力有限公司电力科学研究院 | Method and device for optimizing power line inspection path of unmanned aerial vehicle |
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| CN113359864A (en) * | 2021-07-29 | 2021-09-07 | 鄂尔多斯职业学院 | Unmanned aerial vehicle line patrol route planning method and system |
| CN115686070B (en) * | 2022-11-18 | 2024-01-23 | 国网江苏省电力有限公司苏州供电分公司 | Autonomous line patrol path planning method for unmanned aerial vehicle of power distribution/transmission line |
| CN115686070A (en) * | 2022-11-18 | 2023-02-03 | 国网江苏省电力有限公司苏州供电分公司 | Unmanned aerial vehicle autonomous line patrol path planning method for power distribution/power transmission line |
| CN116878518A (en) * | 2023-09-06 | 2023-10-13 | 滨州市华亿电器设备有限公司 | Unmanned aerial vehicle inspection path planning method for urban power transmission line maintenance |
| CN116878518B (en) * | 2023-09-06 | 2023-11-21 | 滨州市华亿电器设备有限公司 | Unmanned aerial vehicle inspection path planning method for urban power transmission line maintenance |
| CN117973818A (en) * | 2024-04-01 | 2024-05-03 | 四川三瑞智慧建设工程有限公司 | Internet of things data processing method based on artificial intelligence |
| CN117973818B (en) * | 2024-04-01 | 2024-06-07 | 四川三瑞智慧建设工程有限公司 | Internet of things data processing method based on artificial intelligence |
| CN118015439A (en) * | 2024-04-09 | 2024-05-10 | 国网四川省电力公司信息通信公司 | A Substation Inspection System Based on Image Analysis |
| CN118015439B (en) * | 2024-04-09 | 2024-06-11 | 国网四川省电力公司信息通信公司 | A Substation Inspection System Based on Image Analysis |
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