CN109193652A - A kind of distribution network failure self-healing system containing distributed generation resource based on Situation Awareness - Google Patents
A kind of distribution network failure self-healing system containing distributed generation resource based on Situation Awareness Download PDFInfo
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Classifications
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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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- H02J13/0075—
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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
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
- Y02E40/70—Smart grids as climate change mitigation technology in the energy generation sector
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/22—Flexible AC transmission systems [FACTS] or power factor or reactive power compensating or correcting units
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S40/00—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them
- Y04S40/12—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them characterised by data transport means between the monitoring, controlling or managing units and monitored, controlled or operated electrical equipment
- Y04S40/126—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them characterised by data transport means between the monitoring, controlling or managing units and monitored, controlled or operated electrical equipment using wireless data transmission
Abstract
The invention discloses a kind of distribution network failure self-healing system containing distributed generation resource based on Situation Awareness, it includes: PMU information acquisition module, is connect with wireless communication module；Wireless communication module is connect with PMU information acquisition module and MYSQL database module；MYSQL database module is connect with multi-source data processing module, distributed generation resource power output prediction module and Analysis on Observability module；Multi-source data processing module: handling distribution multi-source data, Analysis on Observability module: analyzing the ornamental of distribution network；Distributed generation resource power output prediction module is connect with fault self-recovery module；Fault self-recovery module: data basis is provided for the Load flow calculation of active distribution network, control and operation, completes network reconfiguration；Solving the prior art has solution conventional electrical distribution net fault recovery reconstruction, cannot effectively carry out fault self-recovery and realize the technical problems such as power distribution network network reconfiguration.
Description
Technical field
The invention belongs to distribution network failure self healing field more particularly to it is a kind of based on Situation Awareness containing distributed generation resource
Distribution network failure self-healing system.
Background technique
The core concept that active control is active distribution network is carried out to the operation situation of active distribution network, this requires matching
During power grid real time execution controls, the real-time running state letter of the necessary to master the whole network of power distribution network dispatching control centers at different levels
Breath, this also proposes the requirement of real-time, rapidity to the method for estimating state for being adapted to active distribution network.Therefore to power distribution network
Stable operation and reliable control for, there is the self-healing control after realizing distribution network failure important theoretical value and engineering to anticipate
Justice.
Distribution network failure recovery and rebuilding problem is a hot topic of present distribution research.Distribution network failure recovery and rebuilding is one
A multiple target, multiple constraint, multi-period, non-linear and discontinuous optimum organization problem, problems improve not yet
Solution.Currently, domestic and foreign scholars have carried out a large amount of research to the problem, according to can will substantially match the characteristics of method
Electric network fault restructing algorithm is divided into: traditional mathematics optimization algorithm, heuritic approach, ant group algorithm, particle swarm algorithm, fuzzy evaluation
Algorithm, genetic algorithm, expert system approach, multi-agent system method and hybrid optimized algorithm.
Although solving conventional electrical distribution net fault recovery reconstruction currently, having and much having researched and proposed certain methods,
Influence of the distributed generation resource to distribution network failure recovery and rebuilding is not accounted for, and mainly distribution network failure recovery algorithms are changed
It is more into studying, without reference to the change of fail-over policy and model；So that cannot effectively carry out failure when distribution network failure
Power distribution network network reconfiguration is realized in self-healing.
Summary of the invention
The technical problem to be solved by the present invention is providing a kind of power distribution network event containing distributed generation resource based on Situation Awareness
Hinder self-healing system, has solution conventional electrical distribution net fault recovery reconstruction to solve the prior art, but do not account for distribution
Influence of the power supply to distribution network failure recovery and rebuilding, so that cannot effectively carry out fault self-recovery when distribution network failure and realize distribution
The technical problems such as net network reconfiguration.
The present invention specifically uses following technical scheme:
A kind of distribution network failure self-healing system containing distributed generation resource based on Situation Awareness, it includes:
PMU information acquisition module: PMU information acquisition module is set on distribution line, is responsible for real time monitoring distribution line
Information, fault message when distribution information and distribution line when including operating normally break down；Connect with wireless communication module
It connects；
Wireless communication module: wireless communication module is connect with PMU information acquisition module and MYSQL database module；It is responsible for
The multi-source information signal that PMU information acquisition module detects is received, and transmits the distribution received to multi-source data processing module
Information；
MYSQL database module: for storing collected Various types of data in distribution operation, including real-time major network power transformation
It stands load data, real-time generation of electricity by new energy data, band under data, the distant data of real-time distribution network terminal three, distribution transforming quasi real time
When target real time information PMU data；With multi-source data processing module, distributed generation resource power output prediction module and observability point
Analyse module connection；
Multi-source data processing module: handling distribution multi-source data, realizes to collected asynchronous information, power transformation
Real time data, PMU metric data, Distribution Network Load Data data, the generation of electricity by new energy data of standing synchronize cleaning treatment and data fusion；
Analysis on Observability module: analyzing the ornamental of distribution network, obtains the observability of power distribution network；
Distributed generation resource power output prediction module: power output prediction is carried out to the distributed generation resource accessed in power distribution network；With failure
The connection of self-healing module；
Fault self-recovery module: data basis is provided for the Load flow calculation of active distribution network, control and operation；Load flow calculation is
Network reconfiguration provides data basis；Complete network reconfiguration.
The fault self-recovery module includes state estimation submodule, Load flow calculation submodule and network reconfiguration submodule；Shape
State estimates that submodule provides data basis for the Load flow calculation of active distribution network, control and operation；Load flow calculation submodule carries out
Load flow calculation；Network reconfiguration submodule carries out network reconfiguration.
The method that the network reconfiguration submodule carries out network reconfiguration are as follows:
Step 1, using each DG as root node, DG, which predicts activity of force and is limited, carries out breadth first search formation plan isolated island；
Step 2 judges whether plan isolated island intersects, non-intersecting to enter step 4 if intersection, enters step 3；
Step 3 re-searches for carrying out isolated island merging with DG generation model, forms new isolated island；
Step 4 is up to the preferential recovery and optimization that objective function carries out important load with the load of recovery, forms each area
The initial network reconfiguration scheme in domain；
Step 5, each network reconfiguration region carry out information exchange, optimal for objective function to switch number of operations, carry out complete
Optimizing is coordinated by office.
Wireless communication module includes including short distance and remote radio communication network, and Small Area Wireless Communication Networks are used for will
The fault-signal that each group fault detection detects converges to node；Remote radio communication network is used for whole failures at node
Information is transmitted to multi-source data processing module；The short range wireless communications network is ZIGBEE communication network；The long distance wireless is logical
Communication network is GPRS network.
The multi-source data processing module includes two stages of data cleansing and data integration.
The data cleansing stage synchronizes cleaning to collected asynchronous information using gray system；The data
Integration phase carries out fuzzy revising to the data within the scope of acceptable error using boundary values optimal conditions, allows to be suitable for matching
Network control system.
Analysis on Observability module carries out Observability Analysis to network using the method based on graph theory depth-first search, obtains
To the considerable situation of nodes.
The distributed generation resource power output prediction module establishes a kind of genetic algorithm optimization BP mind based on grey correlation analysis
It contributes prediction model, prediction day DG power output is carried out as unit of different small period spans pre- in short term through network generation of electricity by new energy
It surveys.
The state estimation submodule estimates state of electric distribution network with least-squares estimation model.
The network reconfiguration submodule use layering and zoning network reconfiguration scheme, respectively with the load of recovery at most and
Switch number of operations is at least that objective function carries out region and global optimization.
The invention has the advantages that:
The invention proposes the distribution network failure self-healing systems containing DG based on Situation Awareness.The system utilizes layering and zoning
Distribution Network Failure Network Reconfiguration Algorithm carry out power distribution network network reconfiguration, realize power distribution network stable operation control, mainly include
PMU information acquisition module, wireless communication module, MYSQL database module, multi-source data processing module, Analysis on Observability mould
Block, distributed generation resource power output prediction module and fault self-recovery module, wherein fault self-recovery module mainly includes state estimation, trend
It calculates and three submodules of network reconfiguration, network reconfiguration module synthesis distribution contributes prediction module result using layering and zoning
Method carries out Distribution Network Failure recovery.
The present invention has following outstanding advantages:
<1>multi-source data processing module is used, it is clear to the data carried out according to the collected asynchronous information of different frequency
It washes and handles, the data in multiple data sources are combined and are uniformly processed, substantially increase the matter that distribution is calculated and controlled
Amount reduces the time required for self-healing control calculates.
<2>the layering and zoning distribution network failure self-healing system based on Situation Awareness is contributed using distributed generation resource and predicts mould
Block carries out power output prediction to the distributed generation resource of access distribution, the randomness of distributed generation resource has been fully considered, so that distribution net
Network reconstruct more has practicability.
<3>the layering and zoning distribution network failure self-healing system based on Situation Awareness, fault self-recovery module is based on power distribution network
Situation Awareness uses the fault self-recovery algorithm of layering and zoning, and the multi-period power output model of cooperation DG carries out network reconfiguration, distribution network
Reconfiguration scheme, which more has, to tally with the actual situation.
Solving the prior art has solution conventional electrical distribution net fault recovery reconstruction, but does not account for distributed generation resource
Influence to distribution network failure recovery and rebuilding, so that cannot effectively carry out fault self-recovery when distribution network failure and realize power distribution network net
The technical problems such as network reconstruct.
Detailed description of the invention:
Fig. 1 is present system schematic diagram；
Fig. 2 is network reconfiguration flow diagram.
Specific embodiment
The present invention is as shown in Figure 1, mainly include PMU (synchronous phasor measuring device) information acquisition module, wireless telecommunications mould
Block, MYSQL database module, multi-source data processing module, Analysis on Observability module, distributed generation resource power output prediction module and
Fault self-recovery module, wherein fault self-recovery module mainly includes three state estimation, Load flow calculation and network reconfiguration submodules, net
The comprehensive distributed power output prediction module result of network reconstructed module carries out distribution network reconfiguration using the method for layering and zoning.
PMU information acquisition module
PMU information acquisition module is set on distribution line, is responsible for real time monitoring distribution line information, including operate normally
When fault message (voltage, electric current etc.) when breaking down of distribution information and distribution line.
Wireless communication module
Wireless communication module and PMU information acquisition module and multi-source data processing module are wirelessly connected, and are responsible for receiving PMU letter
The multi-source information signal that breath acquisition module detects, and the distribution information received is transmitted to multi-source data processing module.
MYSQL database module
MYSQL database is for storing collected Various types of data in distribution operation, including real-time major network substation number
According to load data, real-time generation of electricity by new energy data, band markers under, distant data of real-time distribution network terminal three, distribution transforming quasi real time
Real time information PMU data etc., in case fault self-recovery calls at any time.
Multi-source data processing module
Multi-source data processing module handles distribution multi-source data, main to realize to collected asynchronous information,
The data such as Real Time Data of Substation, PMU metric data, Distribution Network Load Data data, generation of electricity by new energy data synchronize cleaning treatment
And data fusion, data basis is provided for distribution self-healing.
Analysis on Observability module
Analysis on Observability module analyzes the ornamental of distribution network, the observability of power distribution network is obtained, after being
Continuous state estimation, Load flow calculation and network reconfiguration subregion provides data basis.
Distributed generation resource power output prediction module
Distributed generation resource power output prediction module mainly carries out power output prediction to the distributed generation resource accessed in power distribution network, analyzes
It establishes the power output prediction model of distributed generation resource in the fluctuation and randomness characteristic of different moments, certainly for distribution network failure
More it prepares.
Fault self-recovery module
Fault self-recovery module is the nucleus module of Distribution Network Failure self-healing system, mainly includes state estimation submodule, trend
Computational submodule and network reconfiguration submodule.Wherein state estimation provides for the Load flow calculation of active distribution network, control and operation
Data basis.Load flow calculation provides data basis for network reconfiguration.Network reconfiguration submodule uses the network reconfiguration of layering and zoning
Scheme is at least at most respectively that objective function carries out region and global optimization with switch number of operations with the load of recovery.
The step of network reconfiguration module includes:
Fig. 2 is invention Network Reconfiguration Algorithm schematic diagram.Failure reconfiguration step includes:
Step 1: using each DG as root node, DG predicts activity of force and is limited that carry out breadth first search formation plan lonely
Island；；
Step 2: judging whether plan isolated island intersects, non-intersecting to enter step 4 if intersection, enters step 3；
Step 3: it re-searches for carrying out isolated island merging with DG generation model, forms new isolated island；
Step 4: being up to the preferential recovery and optimization that objective function carries out important load with the load of recovery, is formed each
The initial network reconfiguration scheme in region；
Step 5: each network reconfiguration region carries out information exchange, optimal for objective function to switch number of operations, carries out complete
Optimizing is coordinated by office.
It should be noted that it is as follows to restore the optimal formula of value:
In formula: m is distribution subregion number；N is each region internal loading number；ωiFor the weighted value of i-th of load；PiFor
The practical recovery electricity of t-th of period internal loading i；N is the total load bus number in power loss region；yikTo be born in t-th of period
The power supply state of lotus i, 1 is restores electricity, and 0 is power failure state.
Switch the optimal formula of number of operations are as follows:
In formula: T indicates switch number of operations；S1Indicate the set of block switch in non-faulting outage area before failure；S2For
The set for the normally opened interconnection switch being connected with non-faulting power loss region；ki、kjRepresent the variation shape of block switch and interconnection switch
State, 1 represents closure (becoming being closed from opening), and 0 represents opening (becoming opening from closure).
Claims (10)
1. a kind of distribution network failure self-healing system containing distributed generation resource based on Situation Awareness, it includes:
PMU information acquisition module: PMU information acquisition module is set on distribution line, is responsible for real time monitoring distribution line information,
Fault message when distribution information and distribution line when including operating normally break down；It is connect with wireless communication module；
Wireless communication module: wireless communication module is connect with PMU information acquisition module and MYSQL database module；It is responsible for reception
The multi-source information signal that PMU information acquisition module detects, and the distribution information received is transmitted to multi-source data processing module；
MYSQL database module: for storing collected Various types of data in distribution operation, including real-time major network substation number
According to load data, real-time generation of electricity by new energy data, band markers under, distant data of real-time distribution network terminal three, distribution transforming quasi real time
Real time information PMU data；With multi-source data processing module, distributed generation resource power output prediction module and Analysis on Observability mould
Block connection；
Multi-source data processing module: handling distribution multi-source data, realizes real to collected asynchronous information, substation
When data, PMU metric data, Distribution Network Load Data data, generation of electricity by new energy data synchronize cleaning treatment and data fusion；
Analysis on Observability module: analyzing the ornamental of distribution network, obtains the observability of power distribution network；
Distributed generation resource power output prediction module: power output prediction is carried out to the distributed generation resource accessed in power distribution network；With fault self-recovery
Module connection；
Fault self-recovery module: data basis is provided for the Load flow calculation of active distribution network, control and operation；Load flow calculation is network
Reconstruct provides data basis；Complete network reconfiguration.
2. a kind of distribution network failure self-healing system containing distributed generation resource based on Situation Awareness according to claim 1,
It is characterized by: the fault self-recovery module includes state estimation submodule, Load flow calculation submodule and network reconfiguration submodule；
State estimation submodule provides data basis for the Load flow calculation of active distribution network, control and operation；Load flow calculation submodule into
Row Load flow calculation；Network reconfiguration submodule carries out network reconfiguration.
3. a kind of distribution network failure self-healing system containing distributed generation resource based on Situation Awareness according to claim 2,
It is characterized by: the method that the network reconfiguration submodule carries out network reconfiguration are as follows:
Step 1, using each DG as root node, DG, which predicts activity of force and is limited, carries out breadth first search formation plan isolated island；
Step 2 judges whether plan isolated island intersects, non-intersecting to enter step 4 if intersection, enters step 3；
Step 3 re-searches for carrying out isolated island merging with DG generation model, forms new isolated island；
Step 4 is up to the preferential recovery and optimization that objective function carries out important load with the load of recovery, forms each region
Initial network reconfiguration scheme；
Step 5, each network reconfiguration region carry out information exchange, optimal for objective function to switch number of operations, carry out global association
Adjust optimizing.
4. a kind of distribution network failure self-healing system containing distributed generation resource based on Situation Awareness according to claim 1,
It is characterized by: it includes short distance and remote radio communication network that wireless communication module, which includes, Small Area Wireless Communication Networks are used
Node is converged in the fault-signal for detecting each group fault detection；Remote radio communication network is used for the whole at node
Transmitting fault information is to multi-source data processing module；The short range wireless communications network is ZIGBEE communication network；The long-range nothing
Line communication network is GPRS network.
5. a kind of distribution network failure self-healing system containing distributed generation resource based on Situation Awareness according to claim 1,
It is characterized by: the multi-source data processing module includes two stages of data cleansing and data integration.
6. a kind of distribution network failure self-healing system containing distributed generation resource based on Situation Awareness according to claim 5,
It is characterized by: the data cleansing stage synchronizes cleaning to collected asynchronous information using gray system；It is described
The data integration stage carries out fuzzy revising to the data within the scope of acceptable error using boundary values optimal conditions, allows to be applicable in
It is controlled in distribution.
7. a kind of distribution network failure self-healing system containing distributed generation resource based on Situation Awareness according to claim 1,
It is characterized by: Analysis on Observability module carries out ornamental point to network using the method based on graph theory depth-first search
Analysis, obtains the considerable situation of nodes.
8. a kind of distribution network failure self-healing system containing distributed generation resource based on Situation Awareness according to claim 1,
It is characterized by: the distributed generation resource power output prediction module establishes a kind of genetic algorithm optimization BP based on grey correlation analysis
Neural network generation of electricity by new energy is contributed prediction model in short term, is carried out as unit of different small period spans to prediction day DG power output pre-
It surveys.
9. a kind of distribution network failure self-healing system containing distributed generation resource based on Situation Awareness according to claim 2,
It is characterized by: the state estimation submodule estimates state of electric distribution network with least-squares estimation model.
10. a kind of distribution network failure self-healing system containing distributed generation resource based on Situation Awareness according to claim 2,
It is characterized by: the network reconfiguration submodule uses the network reconfiguration scheme of layering and zoning, respectively most with the load of recovery
It is at least mostly that objective function carries out region and global optimization with switch number of operations.
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Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110222966A (en) * | 2019-05-28 | 2019-09-10 | 天津大学 | Synchronized phasor measure configuration partition method towards the estimation of power distribution network distributions |
| CN110412417A (en) * | 2019-07-15 | 2019-11-05 | 中国人民解放军陆军工程大学 | Micro-capacitance sensor data fault diagnostic method based on intelligent power monitoring instrument table |
| CN110602231A (en) * | 2019-09-20 | 2019-12-20 | 国网江苏省电力有限公司苏州供电分公司 | Distribution network grid edge agent system and distribution network hierarchical management system based on same |
| CN111697569A (en) * | 2020-05-22 | 2020-09-22 | 国网山东省电力公司德州供电公司 | Comprehensive analysis system and method for fault self-healing capability of distribution line |
| CN111769987A (en) * | 2020-06-29 | 2020-10-13 | 厦门力含信息技术服务有限公司 | Network information security testing system and method based on big data management model |
| CN111861256A (en) * | 2020-07-30 | 2020-10-30 | 国网经济技术研究院有限公司 | Active power distribution network reconstruction decision method and system |
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| CN112488417A (en) * | 2020-12-14 | 2021-03-12 | 国网江苏省电力有限公司苏州供电分公司 | Power grid operation characteristic sensing method and system based on LBP and neural network |
| CN113361188A (en) * | 2021-05-10 | 2021-09-07 | 国网河北省电力有限公司营销服务中心 | Multi-target power distribution network dynamic reconstruction method, device and terminal |
| CN113589079A (en) * | 2021-07-28 | 2021-11-02 | 广东电网有限责任公司 | Testing method of self-healing system of power distribution network, electronic equipment and storage medium |
| CN116365518A (en) * | 2023-05-17 | 2023-06-30 | 北京智芯微电子科技有限公司 | Reconfigurable method and system for power distribution network based on intelligent switch |
| CN111861256B (en) * | 2020-07-30 | 2024-05-14 | 国网经济技术研究院有限公司 | Active power distribution network reconstruction decision method and system |
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