CN109687451A - The allocation optimum model of automation equipment in a kind of Complicated Distribution Network - Google Patents
The allocation optimum model of automation equipment in a kind of Complicated Distribution Network Download PDFInfo
- Publication number
- CN109687451A CN109687451A CN201910056552.7A CN201910056552A CN109687451A CN 109687451 A CN109687451 A CN 109687451A CN 201910056552 A CN201910056552 A CN 201910056552A CN 109687451 A CN109687451 A CN 109687451A
- Authority
- CN
- China
- Prior art keywords
- failure
- distribution network
- load
- complicated distribution
- time
- 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.)
- Pending
Links
Classifications
-
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
-
- 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
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- General Physics & Mathematics (AREA)
- Pure & Applied Mathematics (AREA)
- Mathematical Optimization (AREA)
- Algebra (AREA)
- Computational Mathematics (AREA)
- Databases & Information Systems (AREA)
- Software Systems (AREA)
- General Engineering & Computer Science (AREA)
- Mathematical Analysis (AREA)
- Power Engineering (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention discloses a kind of allocation optimum models of automation equipment in Complicated Distribution Network, belong to dispatching automation of electric power systems technical field, including step A: building the polynary array of reflection Complicated Distribution Network topological structure relationship；Step B: it is closed based on the topological structure that polynary array is able to reflect, carries out the modeling of failure-load power off time；Step C: according to failure-load power off time build automation equipment in Complicated Distribution Network with power supply reliability for constraint, economy is the allocation optimum model of target, and passes through genetic algorithm solution；The present invention has efficient computational efficiency when allocation models solves, and has good economy after the completion of allocation models, and is adapted to complicated distribution net work structure, therefore has good future in engineering applications；Under the requirement for meeting entire Complicated Distribution Network power supply reliability, the minimum economic investment needed is extremely suitable for practical engineering application.
Description
Technical field
The invention belongs to automate to set in dispatching automation of electric power systems technical field more particularly to a kind of Complicated Distribution Network
Standby allocation optimum model
Background technique
As the perceptron and controller of distribution system, distribution network automated equipment be realize distribution system Situation Awareness and
Dynamic control key, however, due to distribution net work structure and the method for operation duplication multiplicity, higher-dimension combined characteristic of model etc. because
Element distributes the difficult point in always Distribution Automation Construction rationally
Summary of the invention
In view of the above-mentioned problems, the invention proposes a kind of allocation optimum model of automation equipment in Complicated Distribution Network, packet
It includes:
Step A: the polynary array of reflection Complicated Distribution Network topological structure relationship is built；
Step B: using the topological structure relationship of polynary array reflection, the modeling of failure-load power off time is carried out；
Step C: build automation equipment in Complicated Distribution Network according to failure-load power off time is about with power supply reliability
Beam using economy as the allocation optimum model of target, and is solved by genetic algorithm.
Further, the polynary array are as follows:
WhereinTheLayer (from top to bottom) thePolynary array information corresponding to section (from left to right), For
TheLayer theThe on the path to root node of sectionThe number of layer corresponding segments.
Further, the failure-load power off time are as follows:
When by the topological structure of mutual polynary array reflection being set membership between load and failure:
When by the topological structure of mutual polynary array reflection being set membership between failure and load:
When by the topological structure of mutual polynary array reflection being brotherhood between failure and load:
WhereinIn the case where being determined for automation equipment configuration x, failureLead to loadPower off time；For event
Hinder positioning time, fault correction time, the breaker actuation timeThe sum of；For fault location time, automatic switch
Actuation time, the breaker actuation timeThe sum of;For fault location time, it is automatically switched actuation time, automatically
Interconnection switch actuation timeThe sum of；For loadTo failureThe subscript collection of all automatic configuration variables on path
It closes； For loadCorresponding all offsprings get in touch with the subscript set of automatic configuration variable；
With When topological structure relationship for load and failure is brotherhood, they respectively arrive road between common former generation
The subscript set of all automatic configuration variables on diameter； ,,The respectively corresponding automation of subscript
Configuration variables, value represent for 1 and configure automatic switch at this, and value 0 then represents and do not configure automatic switch at this.
Further, allocation optimum model described in step C are as follows:
。
WhereinIt is automatic configurationCorresponding average power supply reliability in the case where determination,It is power supply
The threshold value of reliability；
WhereinFor the set of loads all on route；For set faulty on route；For failureIt is corresponding
Failure rate；For the user volume on route.
WhereinIt is automatic configurationCorresponding loss of outage in the case where determination
WhereinFor the set of branches all on Complicated Distribution Network； It is in Complicated Distribution NetworkIn branch
The set of all loads in face； It is in Complicated Distribution NetworkThe set of all above failure of branch；Complexity is matched
In power gridFailure above branchCorresponding failure rate；For user type set；For loadTheType load
Load；For automation equipment configurationIn the case where determination, failureLead to loadPower failure between; For automation equipment configuration In the case where determination, theThe corresponding loss of outage of class user type.
WhereinIt is automatic configurationCorresponding life cycle cost in the case where determination；
WhereinThe ratio of investment cost is accounted for for maintenance cost；For the price of automatic switch.
Beneficial effects of the present invention: the present invention has efficient computational efficiency when allocation models solves, and allocation models is complete
There is good economy at rear, and be adapted to complicated distribution net work structure, therefore there is good future in engineering applications；Full
Under the requirement of the entire Complicated Distribution Network power supply reliability of foot, the smallest economic input needed is extremely suitable for reality
Engineer application
Detailed description of the invention
Fig. 1 is the tree structure schematic diagram of Complicated Distribution Network in embodiment.
Fig. 2 is the schematic diagram that topological structure relationship in embodiment between load and failure is set membership.
Fig. 3 is the schematic diagram that topological structure relationship in embodiment between failure and load is set membership.
Fig. 4 is the schematic diagram that topological structure relationship in embodiment between failure and load is brotherhood.
Fig. 5 is genetic algorithm flow chart in embodiment.
Fig. 6 is the schematic diagram of unassembled automatic switch in embodiment.
Fig. 7 is the schematic diagram for assembling automatic switch in embodiment entirely.
Fig. 8 is the allocation optimum scheme of automation equipment in Complicated Distribution Network in embodiment.
Fig. 9 is the comparison for assembling automatic switch solution Yu allocation optimum scheme in embodiment entirely.
Figure 10 is the allocation optimum model flow figure of automation equipment in Complicated Distribution Network of the invention
Specific embodiment
With reference to the accompanying drawing, it elaborates to embodiment.
As shown in Figure 10, in Complicated Distribution Network of the present invention automation equipment allocation optimum model (Optimal
Configuration model of automation equipment in complex distribution network).
Step A: the polynary array of reflection Complicated Distribution Network topological structure is built.
The topological structure of Complicated Distribution Network can be indicated by tree structure as shown in Figure 1.Tree structure has altogether in figure
There are 7 segmentations, can from top to bottom, from left to right number consecutively, is used in combination Variable come indicate every segmentation from
Dynamicization equipment allocation optimum.For oneThe number of layer, can useThe array of member is indicated.Therefore, for such as Fig. 1 institute
The structure shown can be reflected every section of topological structure relationship by a three-number set.Every section of polynary array information with
It is indicated with following formula:
(1)
WhereinTheLayer (from top to bottom) thePolynary array information corresponding to section (from left to right), For
TheLayer theThe on the path to root node of sectionThe number of layer corresponding segments.
The array can be very good to indicate set membership.Such asSection corresponding array (1,0,0) withNumber of segment group (1,3,7)
Second is not identical, but is 0, therefore may determine that Duan Shi The former generation of section.
It can also indicate brotherhood simultaneously, such as Number of segment group (1,3,6) and Number of segment group (1,2,0) is similarly
First identical second is different, but is not 0, therefore may determine that their common former generation is , Ta Menwei
Brotherhood.
Step B: the topological structure relationship based on the mutual polynary array reflection of load and failure, foundation are set about automation
Standby failure-power off time model.
To make those skilled in the art more fully understand sheet 1, it is as follows to provide detailed derivation process.
Step B1: as shown in Fig. 2, load is in switch position candidate On, failure is in switch position candidateUnder,
The topology location relationship of load and failure be a set membership, it is contemplated that between load and failure be figure in dashed path from
Dynamicization equipment existence can arrive power off time by even multiplied are as follows:
(2)
WhereinIn the case where being determined for automation equipment configuration x, failureLead to loadPower off time；For event
Hinder positioning time, fault correction time, the breaker actuation timeThe sum of；For loadTo failureOwn on path
The subscript set of automatic configuration variable； It isA automatic configuration variable, value are represented for 1 and are configured certainly at this
Dynamic switch, value 0 then represent and do not configure automatic switch at this；For fault location time, it is automatically switched actuation time, the breaker actuation timeThe sum of.
Step B2: as shown in figure 3, failure is in switch position candidate On, load is in switch position candidate It
Under, the topology location relationship of load and failure is a set membership, it is contemplated that is dashed path in figure between load and failure
Automation equipment existence, can by even it is multiplied arrive power off time are as follows:
(3)
For loadCorresponding all offsprings get in touch with the subscript set of automatic configuration variable；When for fault location
Between, it is automatically switched actuation time, automatic interconnection switch actuation timeThe sum of.
Step B3: as shown in figure 4, because load and location of fault relationship are brotherhood, failure is considered first
To former generation with the presence or absence of automatic switch, if it does, load can then be restored electricity by breaker, power off time is
.Load is isolated with the presence or absence of FTU to former generation with failure if there is no load is then continued with, is then considered further that
All offsprings in location whether there is at least one interconnection switch, be restored electricity by interconnection switch, power off time
For , otherwise power off time be , power off time is as follows:
(4)
With When topological structure relationship for load and failure is brotherhood, they are respectively arrived jointly
Former generation between all automatic configuration variables on path subscript set.
Step C: it is with power supply reliability according to what failure-load power off time built automation equipment in Complicated Distribution Network
Constraint, economy are the allocation optimum model of target, and are solved by genetic algorithm.
Step C1: power supply reliability model is built
(5)
WhereinIt is automatic configurationCorresponding average power supply reliability in the case where determination,It is that power supply is reliable
The threshold value of property；WhereinFor the set of loads all on route；For set faulty on route；For failure
Corresponding failure rate；For the user volume on route.
Step C2: loss of outage model is built
(6)
For the set of branches all on Complicated Distribution Network； It is in Complicated Distribution NetworkInstitute above branch
There is the set of load； It is in Complicated Distribution NetworkThe set of all above failure of branch；Complicated Distribution Network
InFailure above branchCorresponding failure rate；For user type set；For loadTheThe load of type load
Amount；For automation equipment configurationIn the case where determination, failureLead to loadPower failure between; For automation equipment configuration In the case where determination, theThe corresponding loss of outage of class user type.
Step C3: life cycle cost is built
(7)
WhereinThe ratio of investment cost is accounted for for maintenance cost；For the price of automatic switch.
Step C4: the allocation optimum model of Complicated Distribution Network automation equipment is built.
(7)
As comprehensive cost；The meaning of the model is to acquire satisfaction power supply can
Under property restraint condition, the smallest automatic configuration scheme of economic input.
Step C5: the automation equipment into Complicated Distribution Network for using the genetic algorithm of process as shown in Figure 5 to solve is most
Excellent scheme.
It is the schematic diagram of unassembled automatic switch in Complicated Distribution Network, the schematic diagram of full assembly automatic switch, allocation optimum
The schematic diagram of scheme is respectively Fig. 6, Fig. 7, Fig. 8；Full assembly automatic switch is as shown in Figure 9 with the comparison diagram of allocation optimum scheme.
This embodiment is merely preferred embodiments of the present invention, but scope of protection of the present invention is not limited thereto,
In the technical scope disclosed by the present invention, any changes or substitutions that can be easily thought of by anyone skilled in the art,
It should be covered by the protection scope of the present invention；Therefore, protection scope of the present invention should be with scope of protection of the claims
Subject to.
Claims (4)
1. the allocation optimum model of automation equipment in a kind of Complicated Distribution Network characterized by comprising
Step A: the polynary array of reflection Complicated Distribution Network topological structure relationship is built；
Step B: the topological structure relationship being able to reflect based on polynary array carries out the modeling of failure-load power off time；
Step C: build automation equipment in Complicated Distribution Network according to failure-load power off time is about with power supply reliability
Beam using economy as target allocation optimum model, and is solved by genetic algorithm.
2. the allocation optimum model of automation equipment in a kind of Complicated Distribution Network according to claim 1, which is characterized in that
The polynary array are as follows:
WhereinTheLayer (from top to bottom) thePolynary array information corresponding to section (from left to right), It isLayer theThe on the path to root node of sectionThe number of layer corresponding segments.
3. the optimal configuration method of automation equipment, feature exist in a kind of Complicated Distribution Network according to claim 1 or 2
In failure described in step B-load power off time model are as follows:
When by the topological structure of mutual polynary array reflection being set membership between load and failure:
When by the topological structure of mutual polynary array reflection being set membership between failure and load:
When by the topological structure of mutual polynary array reflection being brotherhood between failure and load:
WhereinIn the case where being determined for automation equipment configuration x, failureLead to loadPower off time；For failure
Positioning time, fault correction time, the breaker actuation timeThe sum of；For fault location time, it is automatically switched dynamic
Make the time, the breaker actuation timeThe sum of;For fault location time, it is automatically switched actuation time, automatic to join
The network switch motion timeThe sum of；For loadTo failureThe subscript set of all automatic configuration variables on path； For loadCorresponding all offsprings get in touch with the subscript set of automatic configuration variable； With When topological structure relationship for load and failure is brotherhood, they respectively arrive path between common former generation
On all automatic configuration variables subscript set； ,,The respectively corresponding automation of subscript is matched
Variable is set, value represents for 1 and configures automatic switch at this, and value 0 then represents and do not configure automatic switch at this.
4. the optimal configuration method of automation equipment, feature exist in a kind of Complicated Distribution Network according to claim 1 or 2
In:
Allocation optimum model described in step C are as follows:
WhereinIt is automatic configurationCorresponding average power supply reliability in the case where determination,It is that power supply is reliable
The threshold value of property；
WhereinFor the set of loads all on route；For set faulty on route；For failureIt is corresponding
Failure rate；For the user volume on route；
WhereinIt is automatic configurationCorresponding loss of outage in the case where determination；
WhereinFor the set of branches all on Complicated Distribution Network； It is in Complicated Distribution NetworkAbove branch
The set of all loads； It is in Complicated Distribution NetworkThe set of all above failure of branch；Complicated distribution
In netFailure above branchCorresponding failure rate；For user type set；For loadTheType load is born
Lotus amount；For automation equipment configurationIn the case where determination, failureLead to loadPower failure between; For automation equipment configurationIn the case where determination, theThe corresponding loss of outage of class user type；
WhereinIt is automatic configurationCorresponding life cycle cost in the case where determination；
The ratio of investment cost is accounted for for maintenance cost,For the price of automatic switch.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910056552.7A CN109687451A (en) | 2019-01-22 | 2019-01-22 | The allocation optimum model of automation equipment in a kind of Complicated Distribution Network |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910056552.7A CN109687451A (en) | 2019-01-22 | 2019-01-22 | The allocation optimum model of automation equipment in a kind of Complicated Distribution Network |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109687451A true CN109687451A (en) | 2019-04-26 |
Family
ID=66192635
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910056552.7A Pending CN109687451A (en) | 2019-01-22 | 2019-01-22 | The allocation optimum model of automation equipment in a kind of Complicated Distribution Network |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109687451A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111555266A (en) * | 2020-04-09 | 2020-08-18 | 清华大学 | Comprehensive planning method for distribution network automation system based on reliability constraint |
| CN111555265A (en) * | 2020-04-09 | 2020-08-18 | 清华大学 | Optimal transformation method for feeder automation equipment based on reliability constraint |
-
2019
- 2019-01-22 CN CN201910056552.7A patent/CN109687451A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111555266A (en) * | 2020-04-09 | 2020-08-18 | 清华大学 | Comprehensive planning method for distribution network automation system based on reliability constraint |
| CN111555265A (en) * | 2020-04-09 | 2020-08-18 | 清华大学 | Optimal transformation method for feeder automation equipment based on reliability constraint |
| CN111555265B (en) * | 2020-04-09 | 2021-08-17 | 清华大学 | Optimal transformation method for feeder automation equipment based on reliability constraint |
| CN111555266B (en) * | 2020-04-09 | 2021-08-17 | 清华大学 | Comprehensive planning method for distribution network automation system based on reliability constraint |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Ren et al. | Agent-based restoration approach for reliability with load balancing on smart grids | |
| Kroposki et al. | Autonomous energy grids: Controlling the future grid with large amounts of distributed energy resources | |
| Zhang et al. | Sequential disaster recovery model for distribution systems with co-optimization of maintenance and restoration crew dispatch | |
| Li et al. | Coordinated preparation and recovery of a post-disaster multi-energy distribution system considering thermal inertia and diverse uncertainties | |
| Aghaei et al. | Distribution expansion planning considering reliability and security of energy using modified PSO (Particle Swarm Optimization) algorithm | |
| CN104716745B (en) | A kind of Topology g eneration method and its system towards distribution power automation terminal | |
| Li et al. | Coordinating multi-energy to improve urban integrated energy system resilience against extreme weather events | |
| CN104732295A (en) | Power load predicating model based on big data technology | |
| CN111475953B (en) | Energy supply reliability influence analysis method, device equipment and storage medium | |
| Zeng et al. | Coordinating multiple resources for enhancing distribution system resilience against extreme weather events considering multi-stage coupling | |
| CN107545516A (en) | A kind of line feed terminals Optimal Configuration Method based on genetic algorithm | |
| Igder et al. | Service restoration through microgrid formation in distribution networks: A review | |
| Oboudi et al. | A feasible method for controlled intentional islanding in microgrids based on PSO algorithm | |
| CN109687451A (en) | The allocation optimum model of automation equipment in a kind of Complicated Distribution Network | |
| Fichera et al. | A multi-layer agent-based model for the analysis of energy distribution networks in urban areas | |
| Al Karim et al. | A machine learning based optimized energy dispatching scheme for restoring a hybrid microgrid | |
| CN110350511A (en) | It is a kind of based on turn power supply affinity a distribution network failure restoration methods | |
| CN113344280A (en) | Power failure plan optimization model constraint construction method and device considering load transfer | |
| Bian et al. | Multi-microgrids for enhancing power system resilience in response to the increasingly frequent natural hazards | |
| CN115663922A (en) | Distributed power supply multi-degree-of-freedom optimal configuration method and system | |
| CN114389263A (en) | Elastic power distribution network post-disaster recovery method and system based on information physical collaborative optimization | |
| Abidi et al. | Source resizing and improved power distribution for high available island microgrid: A case study on a tunisian petroleum platform | |
| Jarndal et al. | Forecasting of peak electricity demand using ANNGA and ANN-PSO approaches | |
| CN109687432A (en) | A kind of distribution terminal addressing method for shaping and system based on multistage collaboration | |
| Talebjedi et al. | Advanced design and operation of Energy Hub for forest industry using reliability assessment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20190426 |
|
| WD01 | Invention patent application deemed withdrawn after publication |