CN112653138A - Distribution network self-healing recovery method based on distributed multi-agent - Google Patents

Distribution network self-healing recovery method based on distributed multi-agent Download PDF

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CN112653138A
CN112653138A CN202011473696.1A CN202011473696A CN112653138A CN 112653138 A CN112653138 A CN 112653138A CN 202011473696 A CN202011473696 A CN 202011473696A CN 112653138 A CN112653138 A CN 112653138A
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agent
team
switch
self
fault
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CN112653138B (en
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李稳国
李勇
周迭辉
谭益
曹一家
彭衍健
曾子龙
张明敏
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Zhuhai Powint Electric Co ltd
Hunan City University
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Zhuhai Powint Electric Co ltd
Hunan City University
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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
    • 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
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00001—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by the display of information or by user interaction, e.g. supervisory control and data acquisition systems [SCADA] or graphical user interfaces [GUI]
    • 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
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00006—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
    • H02J13/00022—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment using wireless data transmission
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/388—Islanding, i.e. disconnection of local power supply from the network
    • 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]
    • 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
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A30/00—Adapting or protecting infrastructure or their operation
    • Y02A30/60—Planning or developing urban green infrastructure
    • 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
    • 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
    • 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
    • Y04S10/12—Monitoring or controlling equipment for energy generation units, e.g. distributed energy generation [DER] or load-side generation
    • 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

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Human Computer Interaction (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Supply And Distribution Of Alternating Current (AREA)

Abstract

The invention provides a distribution network self-healing recovery method based on distributed multi-agent, which comprises the steps of dividing a distribution network into a plurality of communities according to the contact conditions of different feeder groups to form a multi-agent communication system; agents in each community form a virtual dynamic team based on a dynamic team forming mechanism, and self-adaptively update the community structure and the virtual dynamic team in real time when the community structure changes; before a fault occurs, periodically acquiring corresponding bus and branch line electrical parameters, and constructing and storing a network reconfiguration switch combined library; after the fault occurs and is isolated, executing a network reconstruction decision or a planned island decision and outputting a corresponding switch operation instruction; after a network reconstruction decision or a planned island decision is executed, fault-tolerant processing is executed by the interconnection switch agent, and self-healing recovery of the power distribution network is realized. The invention can realize the maximum recovery of the power-off load by using the minimum switching operation number, and has the characteristics of less information iteration times, high self-healing recovery speed and strong practicability.

Description

Distribution network self-healing recovery method based on distributed multi-agent
Technical Field
The invention relates to the technical field of self-healing of power distribution networks, in particular to a self-healing recovery method of a power distribution network based on distributed multi-agent.
Background
The increasing complexity of the topology of power Distribution networks and the daily penetration of Distributed Generation (DGs) into the power Distribution networks increase the risk of power Distribution system faults. Although modern advanced technologies can mitigate the probability of failure to some extent, power failure accidents of power distribution networks cannot be avoided.
At present, the protection devices and measures of the distribution network can isolate electrical faults to a certain extent, but will cause non-fault loads of the isolated area to lose power supply. The reasonable and effective fault recovery processing technology becomes a key link for improving the power supply reliability and the user satisfaction degree.
Self-healing recovery refers to maximum power recovery for a non-failing out-of-service load at a minimum switching operation cost through network reconfiguration or planning islands without violating any power network constraints.
However, the traditional centralized self-healing recovery technology relies on the control center, and makes decisions by using global information, so that the communication time is long, and the processing speed is slow. On the other hand, the conventional multi-agent self-healing recovery technology mostly adopts a layered multi-agent system (HMAS), and the lower-level agents collect information and feed the information layer by layer to the higher-level agents, and make decisions layer by layer; with the increase of the number of the levels, the communication time is increased, the communication performance is reduced, a global optimal solution cannot be obtained, and the method is difficult to be applied to the existing power distribution network.
Therefore, the prior art has certain defects.
Disclosure of Invention
The invention mainly aims to provide a distributed multi-agent-based power distribution network self-healing recovery method capable of achieving fault recovery of a power distribution network comprising distributed power sources.
In order to achieve the main purpose, the invention provides a distribution network self-healing recovery method based on distributed multi-agent, which comprises a step S1 of dividing a distribution network into a plurality of communities according to the contact conditions of different feeder groups, and initializing a plurality of distribution terminal agents in each community to form a multi-agent communication system; step S2, agents in each community form a virtual dynamic team based on a dynamic team forming mechanism, and self-adaptively update community structures and the virtual dynamic team in real time when the community structures change; step S3, before the fault occurs, the corresponding bus and branch line electrical parameters are periodically collected, and a network reconfiguration switch combination library is constructed and stored; step S4, after the fault occurs and is isolated, executing a network reconstruction decision or a plan island decision and outputting a corresponding switch operation instruction; and step S5, after a network reconstruction decision or a planned island decision is executed, fault-tolerant processing is executed by the interconnection switch agent, and self-healing recovery of the power distribution network is realized.
In a further scheme, in step S1, after a plurality of power distribution terminal agents are initialized in each community, the agents in each community read and store topology structure information of the agents in the community, and the agents in each community form a same communication group and perform real-time communication in a peer-to-peer communication mode, wherein the agents are intelligent electrical devices with embedded codes and include bus agents, feeder bus agents, tie switch bus agents, and DG bus agents.
In a further scheme, in the step S2, after the agents in each community form a virtual dynamic team based on a dynamic team forming mechanism, the virtual dynamic team type is divided and a team superior agent is determined.
In a further aspect, in step S3, before the network reconfiguration switch assembly library is constructed and stored, the team superior agent in the virtual dynamic team acquires the required self-healing recovery information in the team according to the type of the virtual dynamic team by using an information interaction mechanism, and constructs and stores the network reconfiguration switch assembly library.
In a further aspect, in step S4, before performing a network reconfiguration decision or a planned islanding decision and outputting a corresponding switch operation command, the fault isolation agent implements a virtual dynamic team thereof.
In a further aspect, in step S1, the dividing the power distribution network into a plurality of communities specifically includes: randomly selecting an unexploded node as a source node, using a contact switch of the source node as a closing state, using a bus of a transformer substation as a boundary, and searching a connected sub-network of the power distribution network by adopting a breadth-first search algorithm; and repeating the steps continuously until all the nodes are traversed, and then, any connected subnet is a community.
In a further aspect, in step S2, the dynamic team forming mechanism specifically includes: and the fault isolation node agent on the downstream side of the fault uses the fault isolation node agent as a source node, uses the effective interconnection switch as a boundary, and adopts a breadth-first algorithm to search a connected subnet to form a dynamic team.
In a further aspect, in step S2, the forming of the virtual dynamic team, the determining of the virtual dynamic team type and the team superior agent specifically include the following steps: step S21, each agent generates virtual fault and is a fault downstream side isolation node, and a virtual dynamic team is formed through a dynamic team forming mechanism; step S22, if a virtual dynamic team contains an effective contact switch, the virtual dynamic team is a network reconstruction dynamic team and a fault isolation node in the virtual dynamic team is a team superior agent; if the virtual dynamic team contains a DG bus agent and has the voltage-frequency control or droop control capability, the virtual dynamic team is a planned island dynamic team and the DG bus agent is a team superior agent; otherwise, the virtual dynamic team is an unplanned island dynamic team and has no upper-level agent.
In a further aspect, in the step S3, the information interaction mechanism specifically includes the following steps: step S31, the interconnection switch bus agent sends query information to the feeder line agents corresponding to the two ends of the interconnection switch bus agent, and obtains the current-carrying margin of the corresponding feeder line; s32, acquiring the current-carrying margin of the end-to-end feeder line by the team superior agent through the communication switch bus agent based on the information iteration mode; and step S33, the team superior agent acquires the active and reactive loads of all member agents in the team in a query-reply mode and calculates the apparent power of the member agents.
In a further aspect, in step S3, the building step of the network reconfiguration switch combination library is: step S331, using the effective interconnection switch as a power supply, wherein the output power of the effective interconnection switch is the product of the actual power current-carrying margin S and a retention factor lambda of the external feeder line of the non-fault power-loss area correspondingly connected with the effective interconnection switch; step S332, taking the distributed power supply in the non-fault power loss area as an active load; step S333, establishing all switch combination tables which meet radial constraints and contain effective interconnection switches and section switches for the non-fault power-losing areas; step S334, for each switch combination, periodically calculating line load flow and node voltage under each switch combination according to current-carrying margin of a feeder line correspondingly connected with an effective interconnection switch, load information of a non-fault power loss area and line impedance parameters of the non-fault power loss area, which are acquired in real time; and if the active power and the reactive power of a certain switch combination are insufficient, virtually cutting off the load according to the load priority until the line current and the node voltage under the switch combination do not cross the boundary.
In a further aspect, in step S4, the process of implementing the virtual dynamic team specifically includes: when a real fault occurs and is isolated, the virtual dynamic team becomes the real dynamic team and its upper-level agent is granted self-healing recovery control.
In a further aspect, in the step S4, the network reconfiguration decision specifically includes the following steps: s41, selecting all switch combinations without any line current and node voltage boundary crossing in the non-fault power loss area as alternative switch combinations; step S42, selecting the switch combination with the maximum load recovery; s43, selecting a switch combination with the minimum switch on-off operand; and step S44, comparing the selected switch combination with the original switch combination and outputting a corresponding switch action instruction.
In a further aspect, in the step S4, the planned islanding decision specifically includes the following steps: step S441, planning DGs black start in the island; step S442, planning the loads in the island to start according to the priority order; step S443, in the switching operation stage, the start-up load does not exceed the dynamic output capacity of the DGs.
In a further aspect, in step S5, the performing, by the tie switch agent, fault tolerance processing specifically includes: and the communication switch agent after closing judges whether the voltage or the frequency at the two ends of the communication switch agent is abnormal within the limit range of the preset time, and if the voltage or the frequency is abnormal, the communication switch which is just closed is disconnected again.
Therefore, the invention has the following beneficial effects:
(1) by adopting a reduction model consisting of a community division mechanism and a dynamic team formation mechanism, the calculation complexity of self-healing recovery is effectively reduced, and the method is more suitable for multi-agent self-healing recovery control with limited calculation capacity.
(2) The information interaction mechanism effectively reduces the information iteration times, and the global information required by self-healing recovery can be obtained only through one information iteration.
(3) Information acquisition and decision preparation required by self-healing recovery are completed before failure, and the self-healing recovery process is further accelerated.
(4) The constructed unified programming framework of the fully distributed multi-agent self-healing recovery control enables the agents to select corresponding program modules to independently execute corresponding tasks according to the identity attributes of the agents, and finally achieves the total self-healing recovery goal through division of labor and cooperation, and application and popularization of the distributed multi-agent based power distribution network self-healing recovery method are facilitated.
Drawings
Fig. 1 is a flow chart of an embodiment of a self-healing recovery method for a power distribution network based on distributed multi-agent in the present invention.
Fig. 2 is a specific execution flow block diagram of an embodiment of a distributed multi-agent-based power distribution network self-healing recovery method according to the present invention.
Fig. 3 is a schematic diagram of a reduced model including a community division mechanism and a dynamic team formation mechanism in an embodiment of a distributed multi-agent-based power distribution network self-healing recovery method.
Fig. 4 is a schematic diagram of an information interaction mechanism in an embodiment of a distributed multi-agent-based power distribution network self-healing recovery method according to the present invention.
Fig. 5 is a schematic diagram of an information interaction mechanism for a team superior agent to acquire global information required for self-healing recovery in the embodiment of the distributed multi-agent-based power distribution network self-healing recovery method.
The system comprises a power distribution network substation, a distributed power supply bus agent (DG) and a distributed island reconstruction team, wherein FB1-FB6 are feeder bus agents, BA1-BA22 are bus agents, TBA1-TBA3 are Tie switch bus agents, DBA1-DBA3 are distributed power supply bus agents (DG bus agents), Tie1-Tie4 are Tie switches, Sub1-Sub2 are distribution network substation, FP1-FP3 are fault points, NRDT is a network reconstruction dynamic team, IIDT is a planned island reconstruction team, Load1-Load6 is a Load, and K1-K9 are branch switches.
The invention is further explained with reference to the drawings and the embodiments.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention.
According to the self-healing recovery method for the power distribution network based on the distributed multi-agent, the adopted multi-agent technology adopts a completely distributed technology and a unified self-healing recovery programming framework, the complex self-healing recovery problem is decomposed into a plurality of small subtasks, the agents with equal positions autonomously execute the corresponding subtasks according to the identity attributes, the positions of fault points and information resources shared among the agents, and finally the self-healing recovery target is realized through the division of labor cooperation among the agents. The self-healing recovery process does not depend on a main station decision center, the self-healing decision is high in autonomy and intellectualization, the self-healing decision is quick and accurate, the self-healing mechanism can adapt to the change of the topological structure of the actual power distribution network, the unified programming framework is convenient for the realization and popularization of the self-healing recovery technology, and the self-healing recovery system is suitable for the self-healing recovery of the power distribution network containing the distributed power supply in the complex environment.
Referring to fig. 1, when the self-healing recovery method of the power distribution network performs self-healing recovery on the power distribution network, firstly, step S1 is executed, step S1 divides the power distribution network into a plurality of communities according to the contact conditions of different feeder groups, and each community initializes a plurality of power distribution terminal agents to form a multi-agent communication system.
In step S1, after a plurality of power distribution terminal agents are initialized in each community, the agents in each community read and store topology information of the agents in the community, and the agents in each community form a same communication group and perform real-time communication in a peer-to-peer communication mode, where the agents are intelligent electrical devices with embedded codes, and include bus agents, feeder bus agents, interconnection switch bus agents, and DG bus agents.
In step S1, the dividing the power distribution network into a plurality of communities specifically includes: and randomly selecting an unexploded node as a source node, using a contact switch of the source node as a closing state, using a substation bus as a boundary, searching a connected subnet of the power distribution network by adopting a Breadth First Search algorithm (BFS), and then continuously repeating the steps until all the nodes are traversed, wherein any connected subnet is a community.
Then, step S2 is executed, agents in each community form a virtual dynamic team based on a dynamic team forming mechanism, and the community structure and the virtual dynamic team are updated in real time adaptively as the community structure changes.
In step S2, after the agents in the communities form a virtual dynamic team based on the dynamic team formation mechanism, the virtual dynamic team types are divided and the team superior agent is determined.
In step S2, the dynamic team formation mechanism specifically includes: and the fault isolation node agent on the downstream side of the fault uses the fault isolation node agent as a source node, uses the effective interconnection switch as a boundary, and adopts a breadth-first algorithm to search a connected subnet to form a dynamic team.
The agents in each community form a communication group through a self-healing ring network or 5G, and the agents in the communication group communicate in real time in an object-oriented generic substation event (GOOSE) message by adopting a peer-to-peer communication mode (P2P) based on the IEC 61850 protocol standard.
In step S2, the formation of the virtual dynamic team, the type of the virtual dynamic team, and the confirmation of the team superior agent specifically include the following steps:
step S21, each agent generates a virtual fault and is itself a fault downstream-side isolated node, and a virtual dynamic team is formed through a dynamic team formation mechanism.
Step S22, if a virtual dynamic team contains an effective contact switch, the virtual dynamic team is a network reconstruction dynamic team and a fault isolation node in the virtual dynamic team is a team superior agent; if the virtual dynamic team contains a DG bus agent and has the voltage-frequency control or droop control capability, the virtual dynamic team is a planned island dynamic team and the DG bus agent is a team superior agent.
Otherwise, the virtual dynamic team is an unplanned island dynamic team and has no upper-level agent.
Further, in step S22, the determination conditions of the valid interconnection switch are: one side of the tie switch is connected with a certain dynamic team (namely a non-fault power-off area), and the other side of the tie switch is connected with a normal area outside the dynamic team.
And step S3 is executed, before the fault occurs, each agent periodically collects the corresponding bus and branch line electrical parameters according to the self attribute, and a network reconfiguration switch combination library is constructed and stored.
In the step S3, before the network reconfiguration switch assembly library is constructed and stored, the team superior agent in the virtual dynamic team acquires the required self-healing recovery information in the team according to the type of the virtual dynamic team by using an information interaction mechanism, and constructs and stores the network reconfiguration switch assembly library.
In step S3, the information interaction mechanism specifically includes the following steps:
and step S31, the interconnection switch bus agent sends the query message to the feeder line agents corresponding to the two ends of the interconnection switch bus agent, and obtains the current-carrying margin of the corresponding feeder line.
And step S32, the team superior agent obtains the current-carrying margin of the end feeder line through the interconnection switch bus agent based on the information iteration mode.
And step S33, the team superior agent acquires the active and reactive loads of all member agents in the team in a query-reply mode and calculates the apparent power of the member agents.
In step S3, the building step of the network reconfiguration switch combination library is:
and step S331, using the effective interconnection switch as a power supply, wherein the output power of the effective interconnection switch is the product (lambda epsilon (0.9, 1)) of the actual power current carrying margin S and the retention factor lambda of the external feeder line of the non-fault power-loss area correspondingly connected with the effective interconnection switch.
Step S332 is to use the Distributed Generators (DGs) in the non-faulty power loss area as active loads.
And S333, establishing all switch combination tables which meet radial constraints and contain effective interconnection switches and section switches for the non-fault power-losing areas.
Step S334, for each switch combination, periodically calculating line load flow and node voltage under each switch combination according to current-carrying margin of a feeder line correspondingly connected with an effective interconnection switch, load information of a non-fault power loss area and line impedance parameters of the non-fault power loss area, which are acquired in real time; and if the active power and the reactive power of a certain switch combination are insufficient, virtually cutting off the load according to the load priority until the line current and the node voltage under the switch combination do not cross the boundary.
Then, step S4 is executed, and after the fault occurs and is isolated, a network reconfiguration decision or a planned island decision is executed and a corresponding switch operation instruction is output.
In step S4, before performing a network reconfiguration decision or a planned islanding decision and outputting a corresponding switch operation command, the fault isolation agent performs a real processing on its virtual dynamic team.
In step S4, the process of reallocating the virtual dynamic team specifically includes: when a real fault occurs and is isolated, the virtual dynamic team becomes the real dynamic team and its upper-level agent is granted self-healing recovery control.
In step S4, the network reconfiguration decision specifically includes the following steps:
and step S41, selecting all switch combinations without any line current and node voltage boundary crossing in the non-fault power loss area as alternative switch combinations.
Step S42 is to preferentially select the switch combination with the largest load recovery.
Step S43, further, a switch combination with the minimum number of switch-on/off operations is selected.
And step S44, comparing the selected switch combination with the original switch combination and outputting a corresponding switch action instruction.
In step S4, the planned islanding decision specifically includes the following steps: and step S441, planning the DGs black start in the island.
Step S442 plans the loads in the island to be started in order of their priority levels.
Step S443, in the switching operation stage, the start-up load does not exceed the dynamic output capacity of the DGs.
And then, executing step S5, and after executing a network reconstruction decision or a planned island decision, executing fault tolerance processing by the interconnection switch agent to realize self-healing recovery of the power distribution network.
In step S5, the performing, by the tie switch agent, fault tolerance processing specifically includes: after closing, the interconnection switch agent judges whether the voltage or the frequency at the two ends of the interconnection switch agent is abnormal within the limit range of preset time, if so, the interconnection switch which is just closed is disconnected again to ensure the power supply safety and reliability of a healthy area.
Therefore, according to the self-healing recovery method for the power distribution network based on the distributed multi-agent, provided by the invention, a master station system is not needed, information interaction and division cooperation among the distributed intelligent multi-agents are utilized under a unified programming frame, network reconstruction and planned isolated island are fused, and the recovery of the load of the non-fault power loss area of the power distribution network is realized in a self-adaptive manner.
In practical application, the agents (agents) adopt Intelligent Electrical Devices (IEDs) and are divided into bus agents, feeder bus agents, tie switch bus agents and DG bus agents, Peer-to-Peer communication modes (P2P) based on IEC 61850 protocol standards are adopted among the agents, and real-time communication is performed by Object-Oriented Generic Substation event (GOOSE) messages, and the distribution network self-healing recovery method based on the distributed multi-Agent of the embodiment integrates two self-healing modes, namely network reconstruction and planned island, and includes the following steps: first, in step S1, the distribution network is divided into several communities according to the contact status of the feeder group, the agents in the communities read and store the topology of the communities, and the agents in each community form the same communication group and perform real-time communication in a peer-to-peer communication mode.
The community division method of the embodiment comprises the following steps: and randomly selecting one node which is not traversed as a source node, searching a connected subnet of the power distribution network by adopting a breadth-first search (BFS) algorithm by taking the interconnection switch as a closing state (connected state) and a substation bus as a boundary, and continuously repeating the operations until all the nodes are traversed, wherein any connected subnet is a community.
As shown in fig. 3, the agent in each community stores the topology of the power distribution sub-network in the community and the identity attribute of the agent corresponding to the node of the power distribution sub-network.
Then, in step S2, agents in each community build a virtual dynamic team by means of a dynamic team forming mechanism, and divide the virtual dynamic team type and determine team superior agents, and the community structure and the virtual dynamic team are updated adaptively in real time as the community structure changes.
Wherein, the dynamic team forming mechanism is as follows: and the fault isolation node agent on the downstream side of the fault uses the fault isolation node agent as a source node, uses the effective interconnection switch as a boundary, and adopts a breadth-first algorithm to search a connected subnet to form a dynamic team.
The agents in each community form a communication group through a self-healing ring network or 5G, and the agents in the communication group communicate in real time in an object-oriented generic substation event (GOOSE) message by adopting a peer-to-peer communication mode (P2P) based on the IEC 61850 protocol standard.
As shown in fig. 3 and 4, according to the self-healing recovery manner, the dynamic teams are divided into a network reconfiguration dynamic team, a planned island dynamic team and an unplanned island dynamic team (non-self-healing recovery dynamic team); the network reconfiguration dynamic team comprises an agent in the non-fault power loss area and an effective interconnection switch bus agent connected with the non-fault power loss area; the agents in the planned island dynamic team and the unplanned island dynamic team only comprise agents in a non-fault power loss area; before a fault, each agent assumes that the fault has occurred and that the fault is located at its adjacent upstream location, building a virtual dynamic team through a dynamic team formation mechanism; in the network reconfiguration dynamic team, the fault isolation agent serves as a superior agent; in a planned island dynamic team, a DG agent with voltage-frequency control or droop control capability and the maximum output power serves as an upper-level agent; in an unplanned island dynamic team, no upper-level agent exists; the upper-level agents in the virtual dynamic team before the fault have no decision-making power, and only the real upper-level agents after the fault isolation are granted the decision-making power.
Further, the effective interconnection switch is determined by the following conditions: one side of the interconnection switch is connected with a certain dynamic team, and the other side of the interconnection switch is connected with a normal area outside the dynamic team.
As shown in fig. 2, after the community structure changes, each agent adaptively updates the community structure and the virtual dynamic team and team member identity attributes in real time according to the power distribution sub-network topology structure maintained by each agent. Specifically, firstly, an agent identity is initialized, a network community topology is read, a virtual dynamic team is formed or updated, electrical information and information interaction are collected, whether the network reconfiguration dynamic team is a team superior agent or not is judged, if yes, a network reconfiguration switch combination library is constructed and stored, whether a network fails or not is judged, if yes, whether the network is isolated or not is judged, if yes, whether the network reconfiguration dynamic team is the team superior agent or not is judged, if yes, a network reconfiguration decision is executed, a corresponding switch operation instruction is output, and after an operation instruction is received, operation is executed and fault-tolerant processing is carried out.
In the above steps, if the network has no fault, it is determined whether the community topology structure changes, if so, the community topology structure, the virtual dynamic team and the team member identity attributes are updated, and the dynamic team is reformed or updated.
In the above steps, if the topology structure of the community is not changed, the electrical information is collected and the information interaction is performed.
In the steps, the network reconfiguration dynamic team is not a team superior agent, whether the team is a planned island superior team agent or not is judged, if yes, a planned island decision is made, and a switch operation instruction is output.
The above-described reduction model is built using a community partitioning mechanism and a dynamic team formation mechanism, as shown in fig. 3.
In step S3, before a fault occurs, each agent periodically collects the corresponding bus and branch electrical parameters according to its own attributes; and the virtual dynamic team superior agent acquires the required self-healing recovery information in the team by adopting an information interaction mechanism according to the team type, and constructs and stores a network reconfiguration switch combined library.
Referring to fig. 5, the information interaction mechanism for the team superior agent to obtain the global information required for self-healing recovery is as follows:
1) the interconnection switch bus agent sends query messages to corresponding feeder line agents at two ends of the interconnection switch bus agent to obtain current-carrying margins of corresponding feeder lines;
2) the team superior agent communicates with a switch bus agent in an information iteration mode to obtain the current-carrying margin of the feeder line at the opposite end of the team superior agent through one-time information iteration;
3) the team superior agent acquires the active and reactive loads of all member agents in the team in a query-reply mode and calculates the apparent power of the member agents.
In step S3, the network reconfiguration switch combination library is constructed by the steps of:
1) constructing the network reconstruction expert library under the condition that an effective interconnection switch exists;
2) regarding the effective interconnection switch as a power supply, wherein the output power of the effective interconnection switch is the product (lambda epsilon (0.9, 1)) of the actual power current-carrying margin S and the retention factor lambda of the correspondingly connected feeder line outside the non-fault power-loss area;
3) treating Distributed Generators (DGs) within a non-faulted power loss zone as active loads;
4) establishing all switch combination tables which meet radial constraint and contain effective interconnection switches and section switches for the non-fault power-losing areas;
5) for each switch combination, periodically calculating the line load flow and node voltage under each switch combination according to the current-carrying margin of the feeder line correspondingly connected with the effective interconnection switch, the load information of the non-fault power loss area and the line impedance parameters of the non-fault power loss area, which are acquired in real time; if the active power and the reactive power are insufficient, virtually cutting off the load according to the load priority until the line current and the node voltage under the switch combination do not cross the boundary;
the above steps S1 to S3 are preparatory work before the self-healing recovery, and are intended to accelerate the subsequent self-healing recovery.
In step S4, after the fault occurs and is isolated, the agent isolating the fault performs a real processing on the virtual dynamic team, the team superior agent makes a network reconfiguration decision or a planned island decision according to the team type and outputs a corresponding switch operation instruction, and other agents receiving the instruction execute corresponding operations.
Wherein, the virtual dynamic team is actually processed as follows: when a real fault occurs and is isolated, the virtual dynamic team becomes the real dynamic team and its upper-level agent is granted self-healing recovery control.
The network reconfiguration decision of the network reconfiguration superior agent is as follows:
1) selecting all switch combinations without any line current and node voltage boundary crossing in a non-fault power loss area as alternative switch combinations;
2) preferentially selecting the switch combination with the maximum load recovery;
3) further, a switch combination with the minimum number of switching-on and switching-off operations is preferentially selected;
4) and comparing the selected switch combination with the original switch combination, and sending a switch action instruction.
The planned island decision of the planned island upper-level agent is as follows:
1) planning DGs black starts within an island, wherein DGs with voltage-frequency or droop controllable capability are prioritized black starts;
2) planning the loads in the island to start in the order of priority;
3) during the switching phase, these startup loads should not exceed the dynamic output capacity of the DGs.
In step S5, the communication switch agent that has been closed performs post-reconfiguration fault tolerance processing.
Wherein, the fault-tolerant processing after the interconnection switch agent is reconstructed is as follows: after closing, the interconnection switch agent judges whether the voltage or the frequency at the two ends of the interconnection switch agent is abnormal within a certain time limit range, and if the voltage or the frequency at the two ends of the interconnection switch agent is abnormal, the interconnection switch which is just closed is disconnected again to ensure the power supply safety and reliability of a healthy area.
Therefore, the invention has the following beneficial effects:
(1) by adopting a reduction model consisting of a community division mechanism and a dynamic team formation mechanism, the calculation complexity of self-healing recovery is effectively reduced, and the method is more suitable for multi-agent self-healing recovery control with limited calculation capacity.
(2) The information interaction mechanism effectively reduces the information iteration times, and the global information required by self-healing recovery can be obtained only through one information iteration.
(3) Information acquisition and decision preparation required by self-healing recovery are completed before failure, and the self-healing recovery process is further accelerated.
(4) The constructed unified programming framework of the fully distributed multi-agent self-healing recovery control enables the agents to select corresponding program modules to independently execute corresponding tasks according to the identity attributes of the agents, and finally achieves the total self-healing recovery goal through division of labor and cooperation, and application and popularization of the distributed multi-agent based power distribution network self-healing recovery method are facilitated.
The distributed multi-agent-based power distribution network self-healing recovery device comprises a memory and a processor. The components in the distribution grid self-healing apparatus are interconnected by a bus system and/or other form of connection mechanism (not shown).
The memory is to store non-transitory computer readable instructions. In particular, the memory may include one or more computer program products that may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. The volatile memory may include, for example, Random Access Memory (RAM), cache memory (cache), and/or the like. The non-volatile memory may include, for example, Read Only Memory (ROM), hard disk, flash memory, etc.
The processor may be a Central Processing Unit (CPU) or other form of processing unit having data processing capabilities and/or instruction execution capabilities, and may control other components in the power distribution grid self-healing restoration device to perform desired functions. In an embodiment of the present disclosure, the processor is configured to execute the computer readable instructions stored in the memory, so that the power distribution network self-healing recovery device executes the power distribution network self-healing recovery method. The power distribution network self-healing recovery method is the same as the embodiment of the power distribution network self-healing recovery method, and repeated description thereof will be omitted.
A storage medium according to an embodiment of the present disclosure has computer-readable instructions stored thereon. The computer readable instructions, when executed by the processor, perform the power distribution network self-healing recovery method according to the embodiments of the present disclosure described above.
The foregoing describes the general principles of the present disclosure in conjunction with specific embodiments, however, it is noted that the advantages, effects, etc. mentioned in the present disclosure are merely examples and are not limiting, and they should not be considered essential to the various embodiments of the present disclosure. Furthermore, the foregoing disclosure of specific details is for the purpose of illustration and description and is not intended to be limiting, since the disclosure is not intended to be limited to the specific details so described.
The block diagrams of devices, apparatuses, systems referred to in this disclosure are only given as illustrative examples and are not intended to require or imply that the connections, arrangements, configurations, etc. must be made in the manner shown in the block diagrams. These devices, apparatuses, devices, systems may be connected, arranged, configured in any manner, as will be appreciated by those skilled in the art. Words such as "including," "comprising," "having," and the like are open-ended words that mean "including, but not limited to," and are used interchangeably therewith. The words "or" and "as used herein mean, and are used interchangeably with, the word" and/or, "unless the context clearly dictates otherwise. The word "such as" is used herein to mean, and is used interchangeably with, the phrase "such as but not limited to".
It should be noted that the above is only a preferred embodiment of the present invention, but the design concept of the present invention is not limited thereto, and any insubstantial modifications made by using the design concept also fall within the protection scope of the present invention.

Claims (14)

1. A self-healing recovery method for a power distribution network based on distributed multi-agent is characterized by comprising the following steps:
step S1, dividing the power distribution network into a plurality of communities according to the contact conditions of different feeder groups, and initializing a plurality of power distribution terminal agents in each community to form a multi-agent communication system;
step S2, agents in each community form a virtual dynamic team based on a dynamic team forming mechanism, and self-adaptively update community structures and the virtual dynamic team in real time when the community structures change;
step S3, before the fault occurs, the corresponding bus and branch line electrical parameters are periodically collected, and a network reconfiguration switch combination library is constructed and stored;
step S4, after the fault occurs and is isolated, executing a network reconstruction decision or a plan island decision and outputting a corresponding switch operation instruction;
and step S5, after a network reconstruction decision or a planned island decision is executed, fault-tolerant processing is executed by the interconnection switch agent, and self-healing recovery of the power distribution network is realized.
2. A power distribution network self-healing recovery method according to claim 1, wherein:
in step S1, after a plurality of power distribution terminal agents are initialized in each community, the agents in each community read and store topology information of the agents in the community, and the agents in each community form a same communication group and perform real-time communication in a peer-to-peer communication mode, where the agents are intelligent electrical devices with embedded codes, and include bus agents, feeder bus agents, interconnection switch bus agents, and DG bus agents.
3. A power distribution network self-healing recovery method according to claim 1, wherein:
in step S2, after the agents in the communities form a virtual dynamic team based on the dynamic team formation mechanism, the virtual dynamic team types are divided and the team superior agent is determined.
4. A power distribution network self-healing recovery method according to claim 3, wherein:
in the step S3, before the network reconfiguration switch assembly library is constructed and stored, the team superior agent in the virtual dynamic team acquires the required self-healing recovery information in the team according to the type of the virtual dynamic team by using an information interaction mechanism, and constructs and stores the network reconfiguration switch assembly library.
5. A power distribution network self-healing recovery method according to claim 1, wherein:
in step S4, before performing a network reconfiguration decision or a planned islanding decision and outputting a corresponding switch operation command, the fault isolation agent performs a real processing on its virtual dynamic team.
6. A power distribution network self-healing recovery method according to claim 2, wherein:
in step S1, the dividing the power distribution network into a plurality of communities specifically includes: randomly selecting an unexploded node as a source node, using a contact switch of the source node as a closing state, using a bus of a transformer substation as a boundary, and searching a connected sub-network of the power distribution network by adopting a breadth-first search algorithm;
and repeating the steps continuously until all the nodes are traversed, and then, any connected subnet is a community.
7. A power distribution network self-healing recovery method according to claim 1 or 3, characterized in that:
in step S2, the dynamic team formation mechanism specifically includes: and the fault isolation node agent on the downstream side of the fault uses the fault isolation node agent as a source node, uses the effective interconnection switch as a boundary, and adopts a breadth-first algorithm to search a connected subnet to form a dynamic team.
8. A power distribution network self-healing recovery method according to claim 7, wherein:
in step S2, the formation of the virtual dynamic team, the type of the virtual dynamic team, and the confirmation of the team superior agent specifically include the following steps:
step S21, each agent generates virtual fault and is a fault downstream side isolation node, and a virtual dynamic team is formed through a dynamic team forming mechanism;
step S22, if a virtual dynamic team contains an effective contact switch, the virtual dynamic team is a network reconstruction dynamic team and a fault isolation node in the virtual dynamic team is a team superior agent;
if the virtual dynamic team contains a DG bus agent and has the voltage-frequency control or droop control capability, the virtual dynamic team is a planned island dynamic team and the DG bus agent is a team superior agent;
otherwise, the virtual dynamic team is an unplanned island dynamic team and has no upper-level agent.
9. The power distribution network self-healing recovery method according to claim 4, wherein:
in step S3, the information interaction mechanism specifically includes the following steps:
step S31, the interconnection switch bus agent sends query information to the feeder line agents corresponding to the two ends of the interconnection switch bus agent, and obtains the current-carrying margin of the corresponding feeder line;
s32, acquiring the current-carrying margin of the end-to-end feeder line by the team superior agent through the communication switch bus agent based on the information iteration mode;
and step S33, the team superior agent acquires the active and reactive loads of all member agents in the team in a query-reply mode and calculates the apparent power of the member agents.
10. A power distribution network self-healing recovery method according to claim 9, wherein:
in step S3, the building step of the network reconfiguration switch combination library is:
step S331, using the effective interconnection switch as a power supply, wherein the output power of the effective interconnection switch is the product of the actual power current-carrying margin S and a retention factor lambda of the external feeder line of the non-fault power-loss area correspondingly connected with the effective interconnection switch;
step S332, taking the distributed power supply in the non-fault power loss area as an active load;
step S333, establishing all switch combination tables which meet radial constraints and contain effective interconnection switches and section switches for the non-fault power-losing areas;
step S334, for each switch combination, periodically calculating line load flow and node voltage under each switch combination according to current-carrying margin of a feeder line correspondingly connected with an effective interconnection switch, load information of a non-fault power loss area and line impedance parameters of the non-fault power loss area, which are acquired in real time; and if the active power and the reactive power of a certain switch combination are insufficient, virtually cutting off the load according to the load priority until the line current and the node voltage under the switch combination do not cross the boundary.
11. A power distribution network self-healing recovery method according to claim 5, wherein:
in step S4, the process of reallocating the virtual dynamic team specifically includes:
when a real fault occurs and is isolated, the virtual dynamic team becomes the real dynamic team and its upper-level agent is granted self-healing recovery control.
12. A power distribution network self-healing recovery method according to claim 10, wherein:
in step S4, the network reconfiguration decision specifically includes the following steps:
s41, selecting all switch combinations without any line current and node voltage boundary crossing in the non-fault power loss area as alternative switch combinations;
step S42, selecting the switch combination with the maximum load recovery;
s43, selecting a switch combination with the minimum switch on-off operand;
and step S44, comparing the selected switch combination with the original switch combination and outputting a corresponding switch action instruction.
13. A power distribution network self-healing recovery method according to claim 10, wherein:
in step S4, the planned islanding decision specifically includes the following steps:
step S441, planning DGs black start in the island;
step S442, planning the loads in the island to start according to the priority order;
step S443, in the switching operation stage, the start-up load does not exceed the dynamic output capacity of the DGs.
14. A power distribution network self-healing recovery method according to claim 1, wherein:
in step S5, the performing, by the tie switch agent, fault tolerance processing specifically includes:
and the communication switch agent after closing judges whether the voltage or the frequency at the two ends of the communication switch agent is abnormal within the limit range of the preset time, and if the voltage or the frequency is abnormal, the communication switch which is just closed is disconnected again.
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