71 results about "Network reconfiguration" patented technology

A system for modifying an electric grid having electrical components includes a processor for executing instructions. The instructions include: generating a mesh-view map of the electric grid with mesh grid lines forming cells, each electrical component being represented in a corresponding cell; plotting a disturbance event on the map to provide a disturbance modified map having one or more disturbance event parameters; generating a plurality of scenarios affecting the electric grid using the disturbance modified map based on uncertainty of various parameters of the electric grid and the disturbance event; developing a plan to modify the electric grid to optimize economics of operation and resilience of the electric grid, and carbon emission from electrical generation using the plurality of scenarios and the disturbance modified map. The system also includes a grid manipulator device configured to modify the electric grid in response to receiving a signal from the processor.

The invention discloses a multi-source cooperative power distribution network fault self-recovery and recovery optimization method, system and device and a storage medium, and relates to the technical field of power system power distribution networks, and the method comprises the steps: collecting the electrical quantity and parameters of each node in real time, and obtaining system state information through data processing; detecting faults by using a multi-criterion algorithm, and determining types and severity; determining a fault section according to a result and minimizing isolation; a collaborative recovery strategy is formulated by integrating multiple sources, and network reconstruction and switching operation optimization are carried out; and finally evaluating a recovery effect, and combining with a historical data feedback adjustment strategy to improve the recovery efficiency. The fault recovery capability of the power distribution network can be remarkably improved, the fault isolation is fast, the load recovery rate is high, the recovery time is short, the economic loss is reduced, the self-healing of different fault scenes is strong, and the unification of technology and economic benefits is realized.

This disclosure pertains to computer-assisted methods, apparatus, and systems for forecasting network performance responsive to network reconfigurations in large scale communication networks.

The invention discloses a flexible interconnection configuration method and system for a power distribution network frame, a medium and equipment, and belongs to the technical field of power distribution network planning of an electric power system, and the method comprises the steps: obtaining an equipment parameter, a source load parameter and a network topology parameter of a current power distribution network; based on the equipment parameters, the source load parameters and the network topology parameters, taking the joint planning of SOP, interconnection switches and lines as an optimization object, taking the lowest comprehensive equiannual value cost of an investment scheme as a target, constructing a target function, and combining a physical structure constraint, an equipment operation constraint, an electrical performance constraint and a network reconstruction constraint to construct a planning model; and iteratively solving the planning model, and outputting a configuration scheme for power distribution network reconstruction. Therefore, by implementing the method, the problems of high investment cost, low operation efficiency and difficulty in realizing efficient consumption of new energy and economic operation of the system under resource constraints caused by lack of cooperation of equipment and line planning in a power distribution network planning configuration method in the prior art can be solved.

The invention discloses a method for improving the toughness of a power distribution network containing an energy storage type flexible soft switch in a fault state, and belongs to the field of power systems and automation of the power systems, and the method comprises the steps: extracting time sequence data and fault information of a distributed power supply and a load; according to the method, an integrated optimization model integrating fault isolation, multi-stage dynamic maintenance, network reconstruction and energy storage type flexible soft switch cooperation is constructed, minimization of whole-process power loss and branch and device loss is taken as a target, and multiple constraints including time sequence balance, device operation, maintenance resources and decoupling power flow are taken into consideration. Wherein the energy storage type flexible soft switch realizes cross-period energy time shifting through an embedded energy storage system; and a mixed integer second-order cone programming algorithm is adopted to carry out rolling solution, and island division, a maintenance sequence and a device operation strategy are synchronously optimized in each stage. According to the method, global coordination and space-time energy management of the multi-stage recovery process can be realized, and the power supply recovery capability and toughness of the power distribution network under the extreme fault are remarkably improved.

Method and system for generating digital signature following one or more secure protocols based on a threshold additively homomorphic encryption (TAHE) over a broadcast channel, where a threshold of parties of a decentralized network produces digital signature by following a Universally Composable secure protocol configured to output Elliptic curve digital signature algorithm (ECDSA) signature or a Schnorr signature. At least one client may cooperate with the threshold of parties to generate digital signature, or threshold of parties may cooperate to generate digital signature without a client. Method may include additively homomorphic encryption (AHE) distributed key generation (DKG), ECDSA / Schnorr DKG, ECDSA / Schnorr presigning, providing ECDSA / Schnorr child keys, ECDSA / Schnorr signing, wallet transfer and / or network reconfiguration.

A network scheduling method, for allocating network resources for communications between a plurality of nodes connected in a network, is performed as follows. Multiple requests for network resources are received, each request being for connection from one node among the plurality of nodes, acting as a source node, to another node among the plurality of nodes, acting as a destination node. A forthcoming epoch of time is considered, the epoch being the network reconfiguration cycle time, the epoch being divided into T timeslots, a timeslot being the shortest period of time that a communication circuit in the network remains active for communication. A plurality of windows of requests, from said received requests, are selected for processing; each window comprising up to T requests for each source node. Multiple stages of arbitration are applied sequentially to the requests selected for processing in different re source domains to identify contentious requests in different domains. For each stage of arbitration, (i) where a request is uncontentious, that request is indicated for potential grant, and (ii) where there is a contention between requests, one request is picked for potential grant and the other contentious requests are indicated as failed. Requests are circulated within each window to retry failed requests in other timeslots. After circulation and repeated arbitration: all surviving requests indicated for potential grant are granted, which comprises outputting grant information to source nodes at each timeslot iteration, and outputting network resource configuration information at each epoch for the granted requests. Any remaining requests that are indicated as 'failed requests' are buffered in a buffer for reconsideration in another epoch.

The invention relates to a node entanglement perception and heterogeneous agent collaborative reinforcement learning defense method oriented to an electric power information physical system, and belongs to the technical field of electric power information physical systems. According to the method, firstly, a simulation model in which a power system layer and a communication system layer are tightly coupled is constructed, a node entanglement degree is introduced to serve as a core index for quantifying network toughness, and key fragile nodes are accurately identified by analyzing the sensitivity of network spectrum entropy to node disturbance. On the basis, a heterogeneous multi-agent reinforcement learning framework composed of a communication agent and an electric power agent is designed and is responsible for route optimization and network reconstruction respectively. By constructing a collaborative objective function fusing a voltage recovery reward and a node entanglement perception promotion reward, the intelligent agent is guided to actively enhance the overall robustness of the system network while recovering the power supply quality. And a hierarchical cooperative training mechanism is adopted, so that a heterogeneous agent learns a cooperative decision strategy, and an information physical cooperative defense mechanism under a cross-domain fault is realized.

The invention discloses an AC / DC hybrid power distribution network fault recovery method based on network reconstruction and opportunity constraint, and belongs to the field of AC / DC power distribution network fault recovery. The method comprises the following steps: step 1, establishing a flexible interconnected power distribution network frame reconstruction model; 2, solving the model constructed in the step 1 based on a binary particle swarm algorithm; 3, constructing an interconnected power distribution network fault recovery model considering opportunity constraints; step 4, carrying out uncertainty scene modeling of wind and light output; 5, converting and solving the opportunity constraint model; and 6, verifying the feasibility of the model through example analysis. According to the method, the flexible internet distribution network rack reconstruction model and the interconnected distribution network fault recovery model considering the chance constraint are established, so that the operation time consumption of the optimization process can be greatly shortened on the basis of effectively ensuring the load recovery effect after the fault, the fault recovery efficiency is remarkably improved, and the fault recovery efficiency is improved. And the method is of great significance to security guarantee of a large-scale power grid.

The invention discloses a power distribution system unit cluster net rack extension planning method and device based on reliability explicit constraint matrix reduction, and the method comprises the following steps: firstly, obtaining the system data of a to-be-planned region, and determining related parameters; secondly, a reliability explicit calculation method capable of reducing the matrix scale is adopted, an MILP model of multi-contact power distribution system unit cluster expansion planning is constructed, and an objective function calculation expression and various constraints are provided; comprising power flow constraints and network topology constraints considering network reconstruction under normal and fault conditions, virtual topology constraints under normal and fault conditions, and reliability index calculation equations and constraints; and finally, based on the input parameters, solving the MILP model by using a solver to obtain main line and tie line planning results of the to-be-planned region in each stage in the future. Aiming at the medium-voltage power distribution network and considering the reliability requirement of the planning area, the invention provides the multi-stage planning method for the power supply unit cluster in the power distribution network taking a multi-contact form as a target networking structure, an investment scheme can be determined in each planning stage, and the reliability and the economical efficiency of the planning are favorably improved.

The invention provides a power distribution network pre-disaster active defense method considering network reconstruction. The method comprises the following steps: 1) establishing a power distribution network operation state model and defining system elements; 2) acquiring meteorological prediction data in a future preset time window, predicting the icing thickness of the distribution line at each moment, calculating the line failure probability according to the icing thickness, and judging the line with the failure probability exceeding a threshold value as a high-risk line; 3) constructing a pre-disaster active defense optimization model of the power distribution network; 4) introducing a second-order cone relaxation method to convert the non-convex power flow constraint in the pre-disaster active defense optimization model of the power distribution network into a convex constraint form; (5) carrying out iterative solution on the converted active defense model by adopting a Benders decomposition method to generate an optimal network reconstruction scheme, a power flow operation state and a distributed power supply output scheme, and (6) monitoring a line icing state in real time to realize dynamic updating of an active defense strategy.

The present invention discloses a method, device, equipment and storage medium for network reconfiguration of transmission network buses, which relates to the technical field of power system simulation. It includes starting from the 10 kV bus of the main transformer under maintenance in the transmission network, and for the 10 kV bus incoming line breaker disconnected due to main transformer maintenance and the distribution network feeders de-energized after operation, using topological analysis method to conduct topological search on each distribution network feeder. Subsequently, the feeders with independent transfer supply schemes can be independently transferred and supplied, and the feeders without independent transfer supply schemes can be spliced to the head end of the independently transferred and supplied feeders to simulate the reverse charging of the de-energized feeders due to main transformer maintenance through the distribution network for power supply, reasonably dispersing the operation risks of each feeder after transfer supply, and adopting weighted index optimization method and optimal load recombination method to reasonably give the optimal network reconfiguration scheme of the distribution network that can improve the basic state index.

The invention provides an NTN-oriented intelligent mobility management and service continuity guarantee method, which is executed by an intelligent mobility management engine at a network side, and comprises the following steps of: based on real-time position information of user equipment and a network node, predicting a position in a future set time by utilizing a prediction algorithm; a dynamic network relation graph is constructed based on the prediction result; analyzing the dynamic network relation graph by using a graph neural network to obtain a network reconfiguration decision; and based on the network reconfiguration decision, indirectly guiding the network equipment to trigger a switching process meeting the 3GPP standard so as to execute switching and core network element migration. A network reconfiguration decision is obtained by constructing a dynamic network relation graph, and the decision guides a standard 3GPP process to be triggered and executed towards a globally optimal direction in a mode of pre-configuring network resources and optimizing a strategy. Therefore, the purposes of seamless switching, reduced signaling overhead, decision globalization and remarkably enhanced service continuity are achieved.

This invention discloses a method and system for configuring and restoring flexible resources and mobile energy storage in a power distribution network, belonging to the field of smart power distribution network technology. Based on a typhoon wind field and wind and rain load model, this invention constructs a time-varying failure rate for power lines and uses Latin hypercube sampling to generate a set of failure scenarios. Typical scenarios are obtained through scenario reduction. Based on the failure scenarios, in the pre-disaster stage, the invention identifies the deployment locations of smart soft switches (SOPs) and mobile energy storage systems (MESSs) that minimize the sum of pre-disaster investment costs and post-disaster recovery period weighted load shedding costs. In the post-disaster stage, time-varying accessibility constraints are constructed based on road travel time preprocessing results, establishing a collaborative recovery model that includes SOP operation, network reconfiguration, and MESS time-varying scheduling. This invention, based on the collaborative configuration and post-disaster control of flexible resources and mobile energy storage, effectively reduces the configuration cost of the power distribution network while improving its support and recovery capabilities in the face of extreme disasters such as typhoons.

The invention belongs to the technical field of distributed new energy dominated microgrid operation and control, and particularly relates to a mountainous area distributed new energy microgrid fault recovery method, which comprises the steps of S1, constructing a probability output model of distributed new energy, the method is used for quantifying the influence of output uncertainty of wind power and photovoltaic power under mountainous complex weather and terrain disturbance on power fluctuation of a power grid. S2, constructing a scene generation and reduction model of multi-source-load joint operation, wherein the model is used for extracting a typical operation scene set from high-dimensional uncertainty input; s3, constructing a load grading model of the weak micro-grid in the mountainous area, carrying out classification and dynamic grading on loads, and outputting a load grading result; and S4, constructing and solving a multi-objective optimization problem so as to realize source-load-storage collaborative fault recovery and island division. According to the method, island division, network reconstruction and key load priority recovery can be rapidly completed in sudden failure or extreme weather, so that the toughness, reliability and operation efficiency of the micro-grid in the mountainous area are remarkably improved.

The application relates to a kind of digital power energy storage system dynamic network reconfiguration methods in the technical field of power energy storage, S1. Build energy storage system;It is composed of intelligent layer, control layer and data layer;S2. Energy storage network modeling;Adopt graph capsule neural network to learn the optimal control strategy of energy storage network;S3. Dynamic network reconfiguration;Based on Markov decision process, generate fault emergency response model;By systematic optimization of the topological structure and optimal control strategy of energy storage network, the quick isolation of fault area is realized, and the dynamic adjustment and reconfiguration of the working mode of energy storage equipment and load equipment are realized, to ensure that the energy storage network can still operate stably under fault situation, improve the flexibility and elasticity (fault tolerance) of energy storage system in dynamic environment;By reducing the energy loss in the transmission process, balancing network load and preventing local failure, the technical problems existing in the prior art are solved, and the sustainable development of new renewable energy system is promoted.

The present application discloses a battery management system, a networking method, and a power battery. The battery management system comprises a master node and multiple slave nodes. Wireless communication is performed between the master node and each slave node; each slave node monitors a communication state of the current channel in real time, and sends a monitoring result to the master node; the master node receives and parses the monitoring result, and determines whether the communication state of the current channel satisfies a preset communication condition; when the communication state of the current channel does not satisfy the preset communication condition, the master node acquires multiple available channels satisfying the preset communication condition, determines a target channel having an optimal communication state from among the multiple available channels on the basis of a preset channel selection criterion, and broadcasts a channel switching signal and a re-networking signal to each slave node; and upon receiving the channel switching signal and the re-networking signal, each slave node performs re-networking with the master node by means of the target channel. The present application allows for timely and effective network reconfiguration, thereby avoiding failure of the battery management system, and improving the communication stability of the battery management system.

A processing system including at least one processor of a communication network may detect an electrical power event of an alternating current electrical power distribution network. The processing system may next select one or more remedial actions in the communication network in response to a severity level of the electrical power event, where the processing system is configured to apply different sets of one or more remedial actions for different severity levels of electrical power events. The processing system may then implement the one or more remedial actions to reconfigure the communication network in response to the severity level of the electrical power event.

This invention relates to the field of power system technology. To address the problem that existing technologies cannot meet the requirements of conservative dispatching and risk ranking for sensitivity to tail risks, it provides a method and system for risk ranking of distribution network branches for high-penetration renewable energy sources. The method for risk ranking of distribution network branches for high-penetration renewable energy sources includes: constructing a steady-state closed-loop relationship considering electro-thermal coupling; establishing a load factor-failure rate mapping model based on renewable energy and load uncertainty models, while simultaneously considering the steady-state closed-loop relationship of electro-thermal coupling, to obtain the branch failure rate; constructing a joint optimization model of risk-aware minimum load shedding and network reconfiguration to obtain the accident consequence assessment result; constructing accident landing point weights based on the branch failure rate, and then calculating the EVAR (Effective Value Assigned) branch risk contribution and ranking each branch based on the accident consequence assessment result to obtain a list of high-risk branches. This method can achieve the screening and ranking of high-risk branches while maintaining the feasibility of the engineering process.

The invention relates to a net rack reconstruction method for transforming a single-radiation line into a 2-1 single-ring network, and the method comprises the steps: recognizing at least two feeder lines in a single-radiation operation state in a power grid, obtaining the electrical parameters, load rates and wiring modes of the feeder lines, selecting the two single-radiation feeder lines with the load rate difference meeting a preset condition as a target transformation line, and carrying out the reconstruction of the two single-radiation feeder lines. A cable line is newly built from an intermediate node of a first target feeder line to be connected to an intermediate node of a second target feeder line, automatic section switches are additionally arranged on the two target feeder lines respectively to form a main section, and the two original single-radiation feeder lines are connected to form a 2-1 single-ring network structure through the newly built cable line and the additionally arranged automatic section switches. And an optical fiber communication network and a distribution automation terminal are configured to realize fault positioning, isolation and non-fault section power supply recovery functions.

The invention discloses a post-fault reliability improvement method for embedded multi-master multi-slave end-to-end transaction and power distribution network operator-producer interaction and cooperation. The method comprises the following steps: step 1, establishing a producer energy consumption benefit measurement model considering differentiated reliability preference; 2, in combination with the production and consumer energy consumption benefit measurement model, establishing a post-fault power distribution network operator-production and consumer double-layer interaction reliability improvement model of the embedded multi-master multi-slave end-to-end transaction; and step 3, based on the balance proof of the multi-master multi-slave game, and based on a sample boundary compression algorithm, solving the power distribution network operator-production and consumer double-layer interaction reliability improvement model after the fault, and finally outputting a network reconstruction strategy of the power distribution network operator and an operation strategy of the production and consumer after the power distribution network fault. According to the technical scheme provided by the embodiment of the invention, mutual benefit and win-win of a power distribution network operator and a producer after a power distribution network fault event occurs are realized, and the social welfare level is effectively improved.

The invention discloses a graph reinforcement learning-based distributed power supply-containing power distribution network fault recovery method, and relates to the field of power system optimization scheduling, in particular to a graph reinforcement learning-based distributed power supply-containing power distribution network fault recovery method. The method comprises the following steps: firstly, establishing a power distribution system topological graph model, constructing a multi-agent decision process, and realizing agent and environment interaction on the basis of power flow analysis and topological verification; secondly, abstracting the power distribution network into graph data, extracting topology and electrical characteristic information by utilizing a graph neural network, and realizing a dynamic recovery decision by combining a deep Q network; and meanwhile, a priority experience playback and sparse reward allocation mechanism is designed, so that the training efficiency and the strategy convergence are improved. According to the method, key load recovery and network reconstruction can be quickly realized under complex topological change and constraint conditions, and the toughness of the power distribution network is remarkably improved.

This disclosure pertains to computer-assisted methods, apparatus, and systems for forecasting network performance responsive to network reconfigurations in large scale communication networks.

To achieve appropriate power supply and demand management.SOLUTION: Each base management device includes an autonomous distributed recovery unit 800. The autonomous distributed recovery unit 800 includes: a network reconfiguration unit 820 that reconfigures a base group including a plurality of base systems capable of communicating with each other as elements when it becomes impossible for an overall management system to manage power supply and demand between multiple base systems due to an occurrence of a failure in the overall management system or a first communication network; an overall management startup destination selection unit 840 that selects one of the base management devices in the multiple base systems belonging to the base group as the startup destination for a new overall management unit; and an overall management unit startup unit 860 that starts the overall management unit in the selected base management device.SELECTED DRAWING: Figure 6

A network scheduling method for allocating network resources for communication between multiple connected nodes in a network is performed as follows: Multiple requests for network resources are received, each request pertaining to a connection from one of the multiple nodes acting as a source node to another of the multiple nodes acting as a destination node. An upcoming time round is considered, which is a network reconfiguration cycle time, divided into T time slots, where a time slot is the shortest period during which communication circuits in the network remain active for communication. Multiple request windows are selected from the received requests for processing; each window includes up to T requests per source node. For the selected requests for processing, multiple arbitration phases are sequentially applied in different resource domains to identify competing requests in different domains. For each arbitration phase, (i) if a request is not competing, it is indicated that the request awaits potential permission, and (ii) if there is competition between requests, one request is selected to await potential permission and the other competing requests are indicated as failed. Within each window, the requests are looped through to retry failed requests in other time slots. After round-robin and repeated arbitration: all remaining requests indicated as potentially pending permission are granted, including outputting permission information to the source node at each time slot iteration and outputting network resource configuration information for granted requests at each cycle. Any remaining requests indicated as "failed requests" are cached in a buffer for reconsideration in another cycle.

The invention discloses an active power distribution network staged fault recovery method and device considering energy storage and controllable load cooperation, a medium and a product, and relates to the technical field of power distribution network fault recovery, the method mainly comprises an island division stage and a network reconstruction stage, in the island division stage, an expansion method based on graph search is adopted, and the power distribution network fault recovery efficiency is improved. A multi-dimensional island establishment feasibility criterion including power balance, energy persistence and active power supply constraints is constructed, so that a self-healing island which can operate stably theoretically is scientifically identified and constructed; in a network reconstruction stage, a multi-objective optimization fault recovery model with maximization of recovery benefits and minimization of operation cost as objectives is established, residual fault areas are recovered, and finally a global optimal recovery strategy considering the recovery range, reliability and economy is formed.

The invention discloses an MPNN-based risk discrimination method and system for participation of large-scale wind power in grid reconstruction, and relates to the technical field of power system wind power access risk assessment, and the method comprises the steps: defining a risk function, and dividing the risk level of a wind power access reconstruction grid; generating a sample data set and reconstructing the sample data set into a graph data form; and training the MPNN model, and judging the risk level after wind power integration. According to the MPNN-based risk discrimination method for participation of large-scale wind power in grid reconstruction, the risk is divided into different levels through the risk function, the recovery speed and reliability of a power grid are improved, a sample set covering various topological structures and wind power access scenes is established, the generalization ability of a model in a changing environment is improved, and the risk discrimination method is suitable for large-scale wind power grid reconstruction. The intelligent level of recovery of the power system is improved, the wind power access risk level is rapidly output through feature normalization and graph data processing, the reliability and the recovery speed of the power system are improved, and better effects are achieved in the aspects of reliability, generalization ability and intelligence.

The present application relates to a kind of flexible interconnection ac-dc power distribution network multilayer collaborative voltage optimization method, comprising: the topological model of the mixed power distribution network including alternating current network, direct current network and voltage source converter interconnection device is established;Using the model conversion method based on second-order cone relaxation and linearization, the topological model is converted, and linearized topological model is obtained;Linearized topological model is used as foundation, and the system-level voltage optimization model considering dynamic network reconfiguration and the equipment-level voltage source converter droop control optimization model are constructed;In day-ahead stage, system-level voltage optimization model is solved, and in day-ahead stage, based on the real-time measurement data of power grid, the active power reference value of voltage source converter in day-ahead decision strategy is corrected on-line by equipment-level voltage source converter droop control optimization model.The present application can solve the problem of voltage fluctuation and regulation lag.

The application discloses a kind of based on hypergraph enhanced YOLOv11 frame weed detection method and device, method includes: based on YOLOv11 baseline network, reconfigures local-global collaborative main network, obtains first optimization network reconfiguration neck network is hypergraph enhanced semantic neck, to establish high-order space topological feature fusion mechanism, obtains second optimization network;Second optimization network is used as the final enhanced detection model, and based on the enhanced detection model, weeds in field are detected;Using the constructed data set and multiple public data sets, the enhanced detection model is comprehensively experimentally verified;The enhanced detection model after verification is used for weed detection.The device includes: processor and memory.The present application solves the problem that the weed detection model in the prior art has low detection accuracy due to insufficient global context perception, weak geometric deformation representation capability and missing high-order topological relationship in complex farmland scenes.

According to the power distribution network two-stage optimization method considering the electric vehicle and distributed power supply access, in the first stage, ordered scheduling of the electric vehicle is achieved by establishing a user participation scheduling probability model and a dynamic electricity price model considering the load, and the optimized electric vehicle load is superposed to a power distribution network reconstruction optimization model in the second stage; and finally, reducing network loss and node voltage deviation of the whole power distribution network through network reconstruction and distributed power supply output. According to the method provided by the invention, the load peak-valley difference can be reduced, and on the premise of considering the user participation rate, the reduction of the user charging cost is ensured, the node voltage level is also improved, and the network loss is reduced.