43 results about "Network reconfiguration" patented technology

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.

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.

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 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 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 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 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.

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 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.

The application discloses a kind of distributed photovoltaic access capacity evaluation methods considering extreme weather failure risk, comprising;Establish the dynamic coupling model of meteorological intensity and distribution network equipment failure rate, generate the failure probability distribution evolving with time and space;Typical failure scenario set under extreme disaster is constructed;Establish the double-layer robust optimization model with the maximum of distributed photovoltaic access capacity as upper goal, with the minimum of system active defense cost under extreme scenario as lower goal;Introduce intelligent soft switch, energy storage fast response and network reconfiguration as active defense means in the lower model of double-layer robust optimization model;The double-layer robust optimization model is iteratively solved, and the limit access capacity distribution scheme of each node distributed photovoltaic is output.The application accurately measures and calculates photovoltaic limit access capacity by coupling meteorological and equipment failure relationship, constructing double-layer robust model and introducing multiple defense means, balances photovoltaic consumption and system resilience, and guarantees the safe and stable operation of distribution network.

The present application relates to power information physical system technical field, disclose a kind of based on information gap decision theory's distribution network information physical system repair method.First with the minimum total cost of distribution network information physical system as goal, the model considering the coupling relationship of distribution network and information network is established;Again, on the basis of distribution network and information network coupling model, establish post-disaster distribution network information physical system post-disaster coordinated recovery model;Then consider adding distribution network network reconfiguration, mobile emergency power supply and emergency communication vehicle and other emergency resource model;Finally, on the basis of emergency resource model, based on information gap decision theory, considering the uncertainty of wind power output, establish distribution network information physical system post-disaster multi-source coordinated recovery strategy.The present application can improve the flexibility of distribution network information physical system after failure, reduce the impact and loss of natural disasters to distribution network and its users.

This invention relates to the field of microgrid technology, providing a method and system for load restoration in a distribution network fault area. The method includes: after acquiring disaster information of the distribution network, implementing network reconfiguration and load reduction; modeling the distribution network using a graph representation learning method, abstracting the distribution network into a graph structure; modeling the fault management problem of the distribution network as a Markov decision process model based on the graph structure; and achieving rapid load restoration of the microgrid cluster during distribution network faults through coordinated control based on the Markov decision process model. This invention deeply integrates "graph representation learning + Markov decision process" with microgrid clusters, forming a closed-loop solution of "dynamic topology reconfiguration - source-grid-load-storage coordination - zero power outage for critical loads." It requires no additional hardware and can be embedded into existing distribution automation terminals, significantly improving the resilience of the distribution network under extreme disasters, the renewable energy absorption rate, and the power supply reliability of critical loads.

The invention provides a data link network reconstruction method based on channel sensing and a network system. A slave node receives position information of a planning center node from an upgrading center node by utilizing a proxy link maintenance message, and the slave node and the planning center node finish indirect link establishment; and after the slave node receives a network merging message sent by the upgrading center node, the slave node modifies the connection relationship between the slave node and the upgrading center node into a slave-slave relationship, and modifies the connection relationship between the slave node and the planning center node into a master-slave relationship. Compared with the prior art that the network is established through a direct link establishment process in the next network establishment period after the network merging message is received, the time required for network merging is greatly shortened.

The invention discloses a three-phase power distribution network topological structure identification method, and belongs to the technical field of power grid topological structure identification. The three-phase power distribution network topological structure identification method comprises the following steps: establishing a nonlinear constraint equation which takes a branch switch state, a node voltage and a branch current as decision variables through a relation among voltage, current and power; establishing an objective function by minimizing the residual error between the measured value and the estimated value; establishing a three-phase power distribution network nonlinear topology identification model based on the nonlinear constraint equation and the objective function, and performing linearization processing on the nonlinear topology identification model; and solving the topology identification model after linearization processing to obtain a three-phase power distribution network topology identification result. By adopting the three-phase power distribution network topology structure identification method, three-phase power distribution network topology identification under normal operation and network reconstruction is realized, and the three-phase power distribution network topology structure identification method is suitable for an unbalanced power distribution network; the problem of low identification precision of the topological structure of the three-phase power distribution network is solved.

This invention discloses a distributed protection method for distribution network feeders and a system incorporating this method. The distributed protection method utilizes FTUs (Feeder Terminal Units), with ring main units and incoming switches as processing units. It establishes a numbering rule for the FTU control switches, establishes communication between associated FTUs, and performs logical judgments based on the collected voltage, current, and frequency values ​​of switches and buses within the ring main unit, according to pre-defined fault identification, fault isolation, and network reconfiguration logics. This facilitates the exchange of inter-FTU blocking information, anomaly information, and reconfiguration information, thereby achieving fault isolation and network reconfiguration.

The invention relates to a planning method for improving the bearing capacity of a power distribution network by considering dynamic network reconstruction and mobile energy storage. The planning method comprises the following steps: S1, constructing a power distribution network and traffic network coupling system model; s2, establishing a comprehensive bearing capacity evaluation model of the power distribution network to obtain a bearing capacity scoring formula; and S3, performing equivalent reconstruction on the power distribution network and traffic network coupling system model to obtain an equivalent reconstruction model. S4, constructing a multi-objective planning model based on the equivalent reconstruction model and a bearing capacity scoring formula; and S5, solving the multi-objective planning model to obtain the optimal action time sequence and the optimal mobile energy storage capacity of the interconnection switch, and performing network planning based on the optimal action time sequence and the optimal mobile energy storage capacity. Compared with the prior art, the method has the advantages that the bearing capacity and economical efficiency of the power distribution network are cooperatively improved, and the like.

The application provides an NTN-oriented intelligent mobility management and service continuity guarantee method, which is executed by an intelligent mobility management engine on the network side, and comprises the following steps: based on real-time position information of a user equipment and a network node, a prediction algorithm is used to predict the position in a future set time, and a dynamic network relationship graph is constructed based on the prediction result; a graph neural network is used to analyze the dynamic network relationship graph, so that a network reconfiguration decision is obtained; based on the network reconfiguration decision, a network device is indirectly guided to trigger a handover process conforming to the 3GPP standard, so as to execute handover and core network element migration. By constructing the dynamic network relationship graph, the network reconfiguration decision is obtained, the decision guides the standard 3GPP process to trigger and execute in the direction of global optimization through the way of preconfiguring network resources and optimizing strategies. Therefore, the purposes of seamless handover, reduced signaling overhead, globalized decision and significantly enhanced service continuity are achieved.

This invention discloses a two-stage fault recovery and maintenance method for a regional integrated power-gas energy system, comprising: based on the regional integrated power-gas energy system, constructing a rapid fault recovery model for the emergency phase of the regional integrated power-gas energy system according to network operation constraints in the power distribution system, operation constraints of various distributed power sources, network reconfiguration constraints, and operation constraints in the natural gas network, and solving the model to obtain the optimal tie switch operation; based on the topology of the system after the tie switches on the distribution network lines operate in the first emergency phase, considering the relevant constraints of maintenance personnel scheduling and the relevant constraints of the system in the first phase model, establishing a second-stage regional integrated power-gas energy system network reconfiguration and maintenance scheduling optimization model; transforming the rapid fault recovery model, network reconfiguration, and maintenance scheduling optimization model into a MISOCP problem to obtain the optimal maintenance route and the tie switch operation of adjusting the optimal topology of the system as the maintenance plan progresses.

The present application relates to a kind of power grid dynamic operation optimization method and system based on electric power technology information, it is related to power grid dynamic operation optimization technical field, wherein: method includes: obtaining multidimensional electric power technology information data;Extract key feature information;Through space-time dimension and load type cross correlation generation electricity load feature optimization data;Using power grid simulation model simulates different operating conditions;Generation and test power source scheduling, network reconfiguration and load management scheme;Select optimal scheme dynamic adjustment power grid operation;System is used to realize the above-mentioned method, including data acquisition module, feature extraction module, optimization decision module and execution control module.The present application is based on the power grid dynamic operation optimization method and system of electric power technology information, through multidimensional information cross analysis and simulation verification, the forward-looking accurate optimization of power grid operating state is realized, and the perception ability of power grid to complex load change, decision comprehensiveness and scheme feasibility are improved.

This invention proposes a two-stage optimization method for distribution networks integrating electric vehicles (EVs) and distributed generation. In the first stage, an orderly scheduling of EVs is achieved by establishing a user participation dispatch probability model and a dynamic electricity price model considering load. The optimized EV load is then superimposed onto the distribution network reconfiguration optimization model in the second stage. Finally, network reconfiguration and distributed generation output are used to reduce network losses and node voltage deviations across the entire distribution network. The proposed method reduces peak-to-valley load differences. Considering user participation rates, it not only reduces user charging costs but also improves node voltage levels and reduces network losses.

The application discloses a kind of fusion network reconstruction and real-time scheduling collaborative optimization method, device and equipment, it is related to power system dispatching control technical field, and the section flow prediction result is obtained by sensitivity matrix, and section flow prediction result is determined to exceed limit state, and can quickly determine limit section;Then in the case where section exceeds limit, with the target of eliminating overload and maximizing new energy consumption, network reconstruction optimization model is established and power supply network is reconstructed, obtains the power supply network after reconstruction, can quickly remove the hard constraint of line overload and section limit, finally constructs dispatching optimization model, and real-time AGC dispatching optimization is carried out to the power supply network after reconstruction using dispatching optimization model, can realize economic operation and consumption maximization, optimize resource allocation within the safe topological boundary, guide dispatching system to preferentially reduce traditional unit output, through the collaborative optimization of network reconstruction and real-time scheduling, effectively improve the adjustment speed.

The invention discloses a double-layer coordinated power system recovery method and system based on multiple flexible resources. The method comprises the following steps: acquiring basic parameters of a target power system and setting a line recovery rate; solving the upper-layer topology reconstruction model to obtain a generator starting sequence and a skeleton network reconstruction scheme containing a bus connection state; solving the lower-layer flexible resource scheduling model to obtain a load recovery amount and flexible resource scheduling power controlled by a corresponding bus connection state; performing joint solution on the double-layer model by combining a global active power balance equation to obtain a preliminary recovery scheme; and performing physical security verification on the preliminary scheme, and if the verification is not passed, constructing an integer cutting constraint and feeding back the integer cutting constraint to the joint solution for iteration until a final recovery scheme is output. According to the method, strong coupling cooperative scheduling of grid reconstruction and multi-type flexible resources is realized, and the feasibility of global optimization and real power grid landing under extreme disasters is ensured through physical verification and a mutual exclusion constraint iteration mechanism.

The application proposes a power distribution network dynamic network reconstruction method based on constraint reinforcement security reinforcement learning, describes the DDNR task of the power distribution network as a constraint Markov decision process (CMDP), and then respectively adopts an interior point policy optimization (IPO) algorithm and a method of adding a security layer based on branch exchange to process the soft constraint (node voltage and line current constraint) and the hard constraint (radial topology constraint) in the DDNR process, and meanwhile, the application proposes a space-time perception neural network model to increase the dynamic space-time change characteristics of the power distribution network power flow in the DDNR process. The method has an important role in reducing the energy loss of the power distribution network, optimizing the voltage distribution, and increasing the new energy carrying capacity.