CN109460844A - Guarantor's electricity method for optimizing and scheduling vehicle based on GIS - Google Patents
Guarantor's electricity method for optimizing and scheduling vehicle based on GIS Download PDFInfo
- Publication number
- CN109460844A CN109460844A CN201810315902.2A CN201810315902A CN109460844A CN 109460844 A CN109460844 A CN 109460844A CN 201810315902 A CN201810315902 A CN 201810315902A CN 109460844 A CN109460844 A CN 109460844A
- Authority
- CN
- China
- Prior art keywords
- guarantor
- node
- electric
- time
- target
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 230000005611 electricity Effects 0.000 title claims abstract description 33
- 238000000034 method Methods 0.000 title claims abstract description 28
- 238000004458 analytical method Methods 0.000 claims abstract description 29
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 8
- 230000008676 import Effects 0.000 claims abstract description 3
- 230000002123 temporal effect Effects 0.000 claims abstract description 3
- 238000012423 maintenance Methods 0.000 claims description 8
- 238000012544 monitoring process Methods 0.000 claims description 6
- 230000008439 repair process Effects 0.000 claims description 3
- 230000009286 beneficial effect Effects 0.000 abstract 1
- 238000004364 calculation method Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000002922 simulated annealing Methods 0.000 description 2
- 238000000137 annealing Methods 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000009472 formulation Methods 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000011084 recovery Methods 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 238000013179 statistical model Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06312—Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Marketing (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Tourism & Hospitality (AREA)
- Quality & Reliability (AREA)
- Development Economics (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Health & Medical Sciences (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Educational Administration (AREA)
- Electric Propulsion And Braking For Vehicles (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The present invention relates to power system automatic field, in particular to a kind of guarantor's electricity method for optimizing and scheduling vehicle based on GIS.Guarantor's electricity method for optimizing and scheduling vehicle based on GIS, which is characterized in that comprise the steps of: A) it imports topological structure of electric, network of highways information and protects electric car and attach information, it solves and protects electric target collection;B) using crossing as node, to protect electric target as destination node, section is used, as line, to establish time-consuming nodal analysis method by time-consuming, the removable node that merging represents guarantor's electric car obtains object module;C) with any minimum target of temporal summation protected electric target and obtain protecting electric car arrival, object module is solved;D) when there is the electric target of guarantor to break down, arrival time shortest guarantor's electric car is assigned, and show optimal route.The beneficial effects of the present invention are: being obtained by the algorithm of science so that protects the electric highest scheduling scheme of vehicle efficiency, the reasonability and science for protecting electricity vehicle scheduling are increased.
Description
Technical field
The present invention relates to power system automatic field, in particular to a kind of guarantor's electricity optimizing and scheduling vehicle side based on GIS
Method.
Background technique
Responsible consumer electricity consumption situation is the focus of power supply enterprise, although the amount of responsible consumer is few, its be
Local society, politics occupy an important position in economy, and interruption of power supply would be possible to cause larger political impact, larger economic damage
Mistake or even social public order heavy clutter etc..Therefore, the power supply reliability of responsible consumer is improved, feasible guarantor is improved in formulation
Electric scheme is simultaneously effectively implemented, and has important practical significance for power supply company.In current guarantor's powered operation, although scene
A large amount of duty personnel can be scheduled, but the type for protecting electric recovery vehicle is more, the quantity of each type is then few, is not enough to
Whole scenes is disposed, thus is often deployed in guarantor's electricity plan scheduler's subjectivity and thinks suitable position, lacks the planning of science, leads
Cause is attended to one thing and lose sight of another, and the on-call maintenance to catastrophic failure is unfavorable for.Thus need one kind being capable of the electric maintenance vehicle of intelligent dispatch guarantor
System.
101105891 A of Chinese patent CN, publication date on January 16th, 2008, a kind of GPS vehicle applied to electric system
Monitoring and dispatching system, including vehicle-mounted terminal equipment, cordless communication network, monitoring and scheduling center and there is intelligent dispatching algorithm
With the task dispatching system of fault handling time statistical model, by counting mould with intelligent dispatching algorithm and fault handling time
Maintenance task is supervised and assigned to the task dispatching system of type, realizes monitoring and scheduling to GPS vehicle, improves dispatching efficiency,
Whole process supervision is realized simultaneously, so that the supervision to services is more effective, examination more objective and fair, but it does not disclose that
Intelligent dispatching algorithm.
Summary of the invention
The technical problem to be solved by the present invention is to protect the scheduling of electric car at present to have subjectivity and shortage planning of science activities
Problem.Propose it is a kind of based on GIS can intelligence computation go out guarantor's electricity method for optimizing and scheduling vehicle of optimal scheduling scheme.
In order to solve the above technical problems, the technical solution used in the present invention are as follows: guarantor's electricity optimizing and scheduling vehicle based on GIS
Method comprising the steps of: A) it imports topological structure of electric and protects electric car and attach information, it solves and protects electric target collection, by GIS
System obtains network of highways information;B) using road intersection as node, to protect electric target as destination node, made using section by time-consuming
For line, line is connect based on highway network topological structure with node and destination node, establishes time-consuming nodal analysis method, electric car will be protected
Be placed in time-consuming nodal analysis method, acquisition object module at random as removable node;C) to protect any one in electric target collection
It protects after electric target breaks down and obtains protecting the minimum target of temporal summation that electric car reaches, solve object module, obtain guarantor's electricity
Vehicle optimal scheduling;D) when protecting in electric target collection has the electric target of guarantor to break down, arrival time shortest guarantor's electric car is assigned
, and show optimal route;E) electric car executive condition is protected in monitoring, updates scheduling.
Preferably, electric target collection is protected in the solution comprises the steps of: A1) electric user's set is protected in acquisition and power grid is opened up
Flutter structure;A2 power supply and power supply line) are found out using breadth first algorithm;A3) include by power supply and power supply line
Power supply unit acquire the electric target collection of guarantor as electric target is protected.
Preferably, it is characterized in that, foundation time-consuming nodal analysis method comprises the steps of: B1) made with road intersection
The passing time in section is predicted according to section historical data for node, node is connected and composed into time-consuming using passing time as line
Node topology;B2 electric target) will be protected as node and be added into highway topological structure, and re-computation time-consuming line accordingly;
B3 electric car) will be protected to be randomly placed in time-consuming node topology as removable node, constitute time-consuming nodal analysis method.
Preferably, the solution object module comprises the steps of: C1) it is calculated to represent according to time-consuming nodal analysis method and protects electricity
The removable node i of vehicle reaches the shortest time for representing the destination node g for protecting electric targetTake minimum value conduct therein
It protects electric target and obtains guarantor's electric car arrival timeAnd then write out the calculating formula of objective function F:
Wherein G is destination node set;C2 initial value T of the real positive value as control parameter T) is taken0, count N and be set to 0;C3)
Removable node in random movement time-consuming nodal analysis method is calculated and is moved between adjacent any node or adjacent any node
The difference DELTA F of the value of objective function F ' and the value of mobile preceding objective function F, removable after receiving movement if Δ F < 0 after moving
Dynamic node location is set to 0 as new explanation and by the value of N, otherwise calculates Probability p,Take section [0,1) in
Random value ε is compared with p, if p > ε, the mobile node location after receiving movement is set to 0 as new explanation and by the value of N, otherwise
It maintains the solution before moving and the value of N is added 1;C4 value T ', T '=T-lnT of new control parameter T) is calculated;C5) judge whether full
Sufficient termination condition, termination condition are T≤1 and N >=20, repeat T ' as the value of control parameter T if being unsatisfactory for termination condition
Step C3-C4 terminates to solve if meeting termination condition, using the position of current removable node as optimal solution.
Preferably, arrival time shortest guarantor's electric car is assigned to comprise the steps of: D1) according to time-consuming nodal analysis method,
The removable node i that exhaustion represents guarantor's electric car reaches the whole routes for representing the destination node g for protecting electric target and calculates time-consumingWherein X is the set of whole routes, is takenMinimum value reach destination node as corresponding removable node i
The most short time-consuming of gIt takesOptimal route Γ of the corresponding route of minimum value as g-ig-i;D2 it) takesMinimum value
Guarantor's electric car that corresponding removable node i represents, which is used as to be assigned, protects electric car, route Γg-iIt is shown as optimal route,
Middle i ∈ I, I are the set for protecting electric car.
Preferably, the object module that solves comprises the steps of: C11) it is obtained from big data platform and protects electric target g's
History failure rate ψg;C12 it) reaches to represent according to the removable node i that time-consuming nodal analysis method calculates representative guarantor's electric car and protect
The shortest time of the destination node g of electric targetWhen minimum value therein being taken to reach as the electric target acquisition guarantor's electric car of guarantor
BetweenConsider the history failure rate ψ of the electric target g of guarantorg, write out the calculating formula of objective function F:
Wherein G is destination node set;C13 initial value T of the real positive value as control parameter T) is taken0, count N and be set to 0;
C14) the removable node in random movement time-consuming nodal analysis method is counted between adjacent any node or adjacent any node
The difference DELTA F of the value of objective function F ' and the value of mobile preceding objective function F after calculation is mobile, if Δ F < 0, after receiving movement
Mobile node location is set to 0 as new explanation and by the value of N, otherwise calculates Probability p,Take section [0,1)
Interior random value ε is compared with p, if p > ε, the mobile node location after receiving movement is set to 0 as new explanation and by the value of N,
Otherwise it maintains the solution before moving and the value of N is added 1;C15 value T ', T '=T-lnT of new control parameter T) is calculated;C16) judge
Whether termination condition is met, and termination condition is T≤1 and N >=20, by T ' as control parameter T's if being unsatisfactory for termination condition
Value repeats step C14-C15, terminates to solve if meeting termination condition, using the position of current removable node as optimal solution.
Preferably, the method for updating scheduling are as follows: E1) when guarantor's electric car is assigned and repairs task, it deducts
The guarantor's electric car being assigned and the guarantor's electricity target to break down protect electric target with residue and protect electric car and establish object module again
And repeat step C;E2) when protecting electric car completion maintenance task, the guarantor's electric car repaired and the guarantor repaired electricity are completed in addition
Target establishes object module again and repeats step C.
Preferably, calculating the shortest time that removable node i reaches destination node gMethod are as follows: according to time-consuming
Nodal analysis method, the removable node i arrival representative that exhaustion represents guarantor's electric car protect whole routes of the destination node g of electric target simultaneously
It calculates time-consumingWherein X is the set of whole routes, is takenMinimum value reach target section as removable node i
The shortest time of point g
Preferably, the multiple guarantor's electricity targets for being located at highway network topological structure same position are considered as the electric target of a guarantor.
Substantial effect of the invention is: it is obtained by the algorithm of science so that protecting the highest dispatching party of electric vehicle efficiency
Case increases the reasonability and science for protecting electric vehicle scheduling.
Detailed description of the invention
Fig. 1 is guarantor's electricity vehicle dispatching method flow diagram based on GIS.
Specific embodiment
Below by specific embodiment, and in conjunction with attached drawing, a specific embodiment of the invention is further described in detail.
It is as shown in Figure 1 guarantor's electricity vehicle dispatching method flow diagram based on GIS, first according to topological structure of electric and guarantor
Electric user information finds out the power supply and transmission line for protecting electric user using breadth first algorithm, by power supply and power supply
The power supply unit that route includes acquires the electric target collection of guarantor as electric target is protected.
Network of highways information is imported by generalized information system, highway network topological structure is obtained, show that network of highways is each by GIS historical data
The average passing time in section.Using road intersection as node, section time-consuming reconstructs highway network topological structure, structure as line
Build time-consuming nodal analysis method.According to the geographical location for protecting electric target, electric target will be protected as destination node and imported into time-consuming node mould
In type, wherein the multiple guarantor's electricity targets for being located at highway network topological structure same position are considered as the electric target of a guarantor, then according to guarantor
Electric car, which will attach information, to constitute object module in the removable Node leading-in time-consuming nodal analysis method of guarantor's electric car conduct.Use simulation
Annealing method solves object module, obtains optimal solution, as the scheduling scheme for protecting electric car.Whether monitoring is protected in electric target collection has
Maintenance needs, and attach and protect in electric car whether have the vehicle for having completed maintenance task, and update optimizing and scheduling vehicle side
Case.
The method for solving object module using simulated annealing are as follows:
S101 it) is calculated according to time-consuming nodal analysis method and represents the target that electric target is protected in the removable node i arrival representative for protecting electric car
The shortest time of node gMinimum value therein is taken as electric target is protected and obtains guarantor's electric car arrival timeAnd then it writes
The calculating formula of objective function F out:
Wherein G is destination node set;
S102 initial value T of the real positive value as control parameter T) is taken0, count N and be set to 0;
S103) the removable node in random movement time-consuming nodal analysis method to adjacent any node or adjacent any node it
Between, the difference DELTA F of the value of objective function F ' and the value of mobile preceding objective function F after calculating is mobile, if Δ F < 0, receives movement
Mobile node location afterwards is set to 0 as new explanation and by the value of N, otherwise calculates Probability p,Take section
[0,1) in random value ε compared with p, if p > ε, receive it is mobile after mobile node location as new explanation and by the value of N
It is set to 0, the value of N is simultaneously added 1 by the solution before otherwise remaining mobile;
S104 value T ', T '=T-ln T of new control parameter T) is calculated;
S105) judge whether to meet termination condition, termination condition is T≤1 and N >=20, by T ' work if being unsatisfactory for termination condition
Step S103-S104 is repeated for the value of control parameter T, terminates to solve if meeting termination condition, by current removable node
Position is as optimal solution.
The embodiment of another consideration historical failure rate of object module is solved using simulated annealing are as follows:
S201 the history failure rate ψ for protecting electric target g) is obtained from big data platformg;
S202 it) is calculated according to time-consuming nodal analysis method and represents the target that electric target is protected in the removable node i arrival representative for protecting electric car
The shortest time of node gMinimum value therein is taken as electric target is protected and obtains guarantor's electric car arrival timeConsider to protect
The history failure rate ψ of electric target gg, write out the calculating formula of objective function F:
Wherein G is destination node set;
S203 initial value T of the real positive value as control parameter T) is taken0, count N and be set to 0;
S204) the removable node in random movement time-consuming nodal analysis method to adjacent any node or adjacent any node it
Between, the difference DELTA F of the value of objective function F ' and the value of mobile preceding objective function F after calculating is mobile, if Δ F < 0, receives movement
Mobile node location afterwards is set to 0 as new explanation and by the value of N, otherwise calculates Probability p,Take section
[0,1) in random value ε compared with p, if p > ε, receive it is mobile after mobile node location as new explanation and by the value of N
It is set to 0, the value of N is simultaneously added 1 by the solution before otherwise remaining mobile;
S205 value T ', T '=T-lnT of new control parameter T) is calculated;
S206) judge whether to meet termination condition, termination condition is T≤1 and N >=20, by T ' work if being unsatisfactory for termination condition
Step C14-C15 is repeated for the value of control parameter T, terminates to solve if meeting termination condition, by the position of current removable node
It sets as optimal solution.
Removable node i reaches the shortest time for representing the destination node g for protecting electric targetCalculation method are as follows: according to
Time-consuming nodal analysis method, the removable node i that exhaustion represents guarantor's electric car reach the whole roads for representing the destination node g for protecting electric target
Line simultaneously calculates time-consumingWherein X is the set of whole routes, is takenThe corresponding removable node i of minimum value reach
The most short time-consuming of destination node g
Assign the arrival time shortest method for protecting electric car are as follows:
S301) according to time-consuming nodal analysis method, the removable node i that exhaustion represents guarantor's electric car reaches the target for representing and protecting electric target
Whole routes of node g simultaneously calculate time-consumingWherein X is the set of whole routes, is takenMinimum value it is corresponding can
The most short time-consuming of mobile node i arrival destination node gIt takesOptimal route of the corresponding route of minimum value as g-i
Γg-i;S302 it) takesGuarantor's electric car for representing of the corresponding removable node i of minimum value protect electric car, line as being assigned
Road Γg-iIt is shown as optimal route, wherein i ∈ I, I is the set for protecting electric car.
Update the method for optimizing and scheduling vehicle are as follows:
S401) when guarantor's electric car, which is assigned, repairs task, the guarantor for deducting the guarantor's electric car being assigned and breaking down is electric
Target protects electric target with residue and guarantor's electric car establishes object module again and solves object module again and updates optimal solution;
S402) when protecting electric car completion maintenance task, addition completes the guarantor's electric car repaired and the guarantor's electricity target repaired again
It is secondary to establish object module and solve object module update optimal solution again.
Above-mentioned embodiment is only a preferred solution of the present invention, not the present invention is made in any form
Limitation, there are also other variations and modifications on the premise of not exceeding the technical scheme recorded in the claims.
Claims (9)
1. guarantor's electricity method for optimizing and scheduling vehicle based on GIS, which is characterized in that
It comprises the steps of:
A it) imports topological structure of electric and protects electric car and attach information, solve and protect electric target collection, network of highways is obtained by generalized information system
Information;
B) using road intersection as node, to protect electric target as destination node, section is used, as line, to be based on highway by time-consuming
Line is connect by net topology structure with node and destination node, establishes time-consuming nodal analysis method, will protect electric car as removable section
Point is random to be placed in time-consuming nodal analysis method, obtains object module;
C the temporal summation of guarantor's electric car arrival is obtained most after) breaking down with electric target of any one guarantor in guarantor's electricity target collection
Small is target, solves object module, obtains and protect electric car optimal scheduling;
D) when protecting in electric target collection has the electric target of guarantor to break down, arrival time shortest guarantor's electric car is assigned, and show
Optimal route;
E) electric car executive condition is protected in monitoring, updates scheduling.
2. guarantor's electricity method for optimizing and scheduling vehicle according to claim 1 based on GIS, which is characterized in that
The solution is protected electric target collection and is comprised the steps of:
A1 it) obtains and protects electric user's set and topological structure of electric;
A2 power supply and power supply line) are found out using breadth first algorithm;
A3) the electric target collection of guarantor is acquired using the power supply unit that power supply and power supply line include as electric target is protected.
3. guarantor's electricity method for optimizing and scheduling vehicle according to claim 1 based on GIS, which is characterized in that
The time-consuming nodal analysis method of the foundation comprises the steps of:
B1 it) using road intersection as node, according to section historical data, predicts the passing time in section, is to connect with passing time
Node is connected and composed time-consuming node topology by line;
B2 electric target) will be protected as node and be added into highway topological structure, and re-computation time-consuming line accordingly;
B3 electric car) will be protected to be randomly placed in time-consuming node topology as removable node, constitute time-consuming nodal analysis method.
4. guarantor's electricity method for optimizing and scheduling vehicle according to claim 1 based on GIS, which is characterized in that
The solution object module comprises the steps of:
C1 it) is calculated according to time-consuming nodal analysis method and represents the target section that electric target is protected in the removable node i arrival representative for protecting electric car
The shortest time of point gMinimum value therein is taken as electric target is protected and obtains guarantor's electric car arrival timeAnd then it writes out
The calculating formula of objective function F:
Wherein G is destination node set;
C2 initial value T of the real positive value as control parameter T) is taken0, count N and be set to 0;
C3) the removable node in random movement time-consuming nodal analysis method to adjacent any node or adjacent any node it
Between, the difference DELTA F of the value of objective function F ' and the value of mobile preceding objective function F after calculating is mobile, if Δ F < 0, receives movement
Mobile node location afterwards is set to 0 as new explanation and by the value of N, otherwise calculates Probability p,Take section
[0,1) in random value ε compared with p, if p > ε, receive it is mobile after mobile node location as new explanation and by the value of N
It is set to 0, the value of N is simultaneously added 1 by the solution before otherwise remaining mobile;
C4 value T ', T '=T-ln T of new control parameter T) is calculated;
C5) judge whether to meet termination condition, termination condition is T≤1 and N >=20, by T ' conduct if being unsatisfactory for termination condition
The value of control parameter T repeats step C3-C4, terminates to solve if meeting termination condition, and the position of current removable node is made
For optimal solution.
5. guarantor's electricity method for optimizing and scheduling vehicle according to claim 1 based on GIS, which is characterized in that
Arrival time shortest guarantor's electric car is assigned to comprise the steps of:
D1) according to time-consuming nodal analysis method, the removable node i that exhaustion represents guarantor's electric car reaches the target section for representing and protecting electric target
Whole routes of point g simultaneously calculate time-consumingWherein X is the set of whole routes, is takenMinimum value as corresponding
Removable node i reaches the most short time-consuming of destination node gIt takesOptimal line of the corresponding route of minimum value as g-i
Road Γg-i;D2 it) takesGuarantor's electric car for representing of the corresponding removable node i of minimum value protect electric car, line as being assigned
Road Γg-iIt is shown as optimal route, wherein i ∈ I, I is the set for protecting electric car.
6. guarantor's electricity method for optimizing and scheduling vehicle according to claim 1 based on GIS, which is characterized in that
The solution object module comprises the steps of:
C11 the history failure rate ψ for protecting electric target g) is obtained from big data platformg;
C12 it) is calculated according to time-consuming nodal analysis method and represents the target section that electric target is protected in the removable node i arrival representative for protecting electric car
The shortest time of point gMinimum value therein is taken as electric target is protected and obtains guarantor's electric car arrival timeConsider to protect electricity
The history failure rate ψ of target gg, write out the calculating formula of objective function F:
Wherein G is destination node set;
C13 initial value T of the real positive value as control parameter T) is taken0, count N and be set to 0;
C14) the removable node in random movement time-consuming nodal analysis method to adjacent any node or adjacent any node it
Between, the difference DELTA F of the value of objective function F ' and the value of mobile preceding objective function F after calculating is mobile, if Δ F < 0, receives movement
Mobile node location afterwards is set to 0 as new explanation and by the value of N, otherwise calculates Probability p,Take section
[0,1) in random value ε compared with p, if p > ε, receive it is mobile after mobile node location as new explanation and by the value of N
It is set to 0, the value of N is simultaneously added 1 by the solution before otherwise remaining mobile;
C15 value T ', T '=T-ln T of new control parameter T) is calculated;
C16) judge whether to meet termination condition, termination condition is T≤1 and N >=20, by T ' conduct if being unsatisfactory for termination condition
The value of control parameter T repeats step C14-C15, terminates to solve if meeting termination condition, by the position of current removable node
As optimal solution.
7. guarantor's electricity method for optimizing and scheduling vehicle according to claim 1 based on GIS, which is characterized in that
The method for updating scheduling are as follows:
E1) when protect electric car be assigned repair task when, deduct the guarantors electric car being assigned and guarantor's electricity mesh for breaking down
Mark protects electric target with residue and protects electric car and establishes object module again and repeat step C;
E2) when protecting electric car completion maintenance task, addition completes the guarantor's electric car repaired and the guarantor's electricity target repaired again
It establishes object module and repeats step C.
8. guarantor's electricity method for optimizing and scheduling vehicle according to claim 2 based on GIS, which is characterized in that be located at network of highways
Multiple guarantor's electricity targets of topological structure same position are considered as the electric target of a guarantor.
9. guarantor's electricity method for optimizing and scheduling vehicle according to claim 4 or 6 based on GIS, which is characterized in that
Calculate the shortest time that removable node i reaches destination node gMethod are as follows: according to time-consuming nodal analysis method, exhaustive generation
The removable node i that table protects electric car reaches the whole routes for representing the destination node g for protecting electric target and calculates time-consumingWherein X is the set of whole routes, is takenMinimum value as removable node i reach destination node g most
Short time
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201810315902.2A CN109460844B (en) | 2018-04-10 | 2018-04-10 | GIS-based power-conserving vehicle optimized scheduling method |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201810315902.2A CN109460844B (en) | 2018-04-10 | 2018-04-10 | GIS-based power-conserving vehicle optimized scheduling method |
Publications (2)
Publication Number | Publication Date |
---|---|
CN109460844A true CN109460844A (en) | 2019-03-12 |
CN109460844B CN109460844B (en) | 2022-03-15 |
Family
ID=65606237
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201810315902.2A Active CN109460844B (en) | 2018-04-10 | 2018-04-10 | GIS-based power-conserving vehicle optimized scheduling method |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN109460844B (en) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111274660A (en) * | 2019-11-30 | 2020-06-12 | 浙江华云信息科技有限公司 | Circuit layout method based on multi-disturbance alternative simulated annealing algorithm |
Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103337163A (en) * | 2013-07-16 | 2013-10-02 | 国家电网公司 | Scheduling method of vehicles in electric power overhaul |
WO2014127849A1 (en) * | 2013-02-25 | 2014-08-28 | Nec Europe Ltd. | Method and system for determining routes of vehicles |
-
2018
- 2018-04-10 CN CN201810315902.2A patent/CN109460844B/en active Active
Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2014127849A1 (en) * | 2013-02-25 | 2014-08-28 | Nec Europe Ltd. | Method and system for determining routes of vehicles |
CN103337163A (en) * | 2013-07-16 | 2013-10-02 | 国家电网公司 | Scheduling method of vehicles in electric power overhaul |
Non-Patent Citations (2)
Title |
---|
T. TLILI, S. KRICHEN,S. FAIZ: "Simulated annealing-based decision support system for routing problems", 《2014 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS》 * |
汤继生,项达冬,李奇,孙喜民: "基于GIS的电网抢修车辆综合调度技术研究", 《电力信息与通用技术》 * |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111274660A (en) * | 2019-11-30 | 2020-06-12 | 浙江华云信息科技有限公司 | Circuit layout method based on multi-disturbance alternative simulated annealing algorithm |
CN111274660B (en) * | 2019-11-30 | 2024-04-26 | 浙江华云信息科技有限公司 | Circuit layout method based on multi-disturbance alternate simulated annealing algorithm |
Also Published As
Publication number | Publication date |
---|---|
CN109460844B (en) | 2022-03-15 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN105303285B (en) | A kind of power emergency is disposed the intellectuality of goods and materials and is alloted method | |
CN105005827B (en) | A kind of emergency response method for early warning based on electric power accident | |
CN110852627A (en) | Decision method and device for post-disaster first-aid repair of power distribution network | |
CN109460833B (en) | Method and system for processing equipment data and repair work order data of distribution network fault | |
CN110111576B (en) | Method for realizing urban traffic elasticity index based on space-time congestion sub-cluster | |
Boyce et al. | Multiclass combined models for urban travel forecasting | |
CN112966882B (en) | Power distribution network scheduling method based on space-time global matching | |
CN109447284B (en) | Distribution network fault information sending method and system for power supply service command platform | |
CN111199320B (en) | Electric vehicle charging load space-time distribution prediction method based on travel probability matrix | |
CN104916124B (en) | Public bicycle system regulation and control method based on Markov model | |
Liu et al. | A memetic algorithm with a new split scheme for solving dynamic capacitated arc routing problems | |
CN114757797B (en) | Power grid resource service central platform architecture method based on data model drive | |
CN114331206B (en) | Point location addressing method and device, electronic equipment and readable storage medium | |
CN109460844A (en) | Guarantor's electricity method for optimizing and scheduling vehicle based on GIS | |
CN113935108A (en) | Multi-type emergency vehicle combined addressing and configuration method, device and storage medium | |
CN105352523B (en) | Intelligent route generation method and device | |
CN109449930A (en) | Power distribution network reliability assessment and repair time parameter modeling method, equipment and medium | |
CN109193946B (en) | Urgent repair information release system for power consumer | |
RUSS et al. | Optimising the design of multimodal freight transport network in Indonesia | |
CN116633011A (en) | Urban power distribution network-oriented power equipment fault influence analysis method | |
CN109687592A (en) | Substation information display control method, device and electronic equipment | |
Beheshtian et al. | Flood-resilient deployment of fueling stations: extension of facility location problem | |
CN114090621B (en) | Ground-air integrated ecological environment monitoring system | |
CN115330043A (en) | Site selection planning method and system for urban charging station | |
Nakamiti et al. | An agent-based simulation system for traffic control in the Brazilian intelligent cities project context |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |