34 results about "Power system restoration" patented technology

The invention belongs to the technical field of power system recovery control, and discloses a power coordination control method of a hybrid energy storage auxiliary black-start system and a related device.According to the method, the total active power requirement of the black-start system is obtained and decomposed into three time scale components of fundamental waves, intermediate frequencies and high frequencies; the power is dynamically distributed to the lithium battery and the super capacitor, the distributed power is corrected based on the temperature, the operation time and the rated parameters, and finally the frequency change rate and the direct-current voltage change rate are calculated according to the actual power instruction and the system parameters so that the controller can output the control quantity. By adopting the method, the contradiction between the energy and the power density of a single power supply is overcome, the response speed and the continuous power supply capability are synergistically improved, the voltage frequency instability risk caused by load input is effectively inhibited, and the reliability and the high efficiency of black start are remarkably improved by perfecting hybrid energy storage coordination control.

The invention relates to the technical field of power system operation and control, in particular to a power system recovery capability evaluation method, device and equipment considering unconventional risks and a medium, and the method comprises the steps: determining parameters for calculating the occurrence probability of earthquake disasters of different earthquake magnitudes; calculating intensity distribution by using an earthquake intensity diffusion model; calculating transmission tower and transmission line fault probabilities to obtain a fault line set; according to the operation power flow and the maximum allowable power flow, the cascading failure situation is divided into high risk and low risk; aiming at the two conditions, respectively enumerating a first-order fault state set and a second-order fault state set to obtain a system recovery capability initial value; the value serves as input, a convergence threshold value is set, a ULBI-IISE algorithm is adopted for iterative calculation, when the difference value of the upper cut set and the lower complementary set is smaller than the threshold value, the recovery capacity and the interval are output, and the method reduces high-order fault complete enumeration and the calculation amount while guaranteeing the precision, and is suitable for rapid evaluation of emergency scenes such as earthquakes.

The invention relates to the field of power system recovery, and discloses a black-start path optimization method, which comprises the following steps of: recursively searching an initial path meeting all preset constraint conditions by taking a black-start power supply as an initial node through a backtracking algorithm to realize full-path traversal so as to avoid missing a potential optimal solution; a graph tensor is constructed based on node comprehensive feature data and edge connection feature data, a time sequence tensor is constructed in combination with dynamic time sequence data, spatial-temporal feature expression of a path is formed, a pre-trained hybrid neural network model is utilized to quickly evaluate a path comprehensive score, a candidate path with the highest score is screened out, and the path comprehensive score is evaluated. And finally, the candidate path is accurately verified through electromagnetic transient simulation, and an optimal path is determined. According to the method, path feasibility constraints are strictly considered, online path adjustment is supported to cope with dynamic changes such as energy storage attenuation, robustness is achieved, path evaluation is accelerated through the hybrid neural network, the simulation verification frequency is greatly reduced, and the search efficiency is remarkably improved.

The invention relates to the technical field of power system recovery control, in particular to a power grid black-start system and method based on cascade hydroelectric characteristics, and the method comprises the steps: constructing a software and hardware integrated system integrating physical equipment and intelligent control; situation awareness is carried out through the software and hardware integrated system, a power failure range after large-area power failure of a power grid is automatically identified, available cascade hydropower stations are positioned, and a black start plan is automatically triggered; the central decision-making unit simultaneously instructs a plurality of upstream hydropower stations to start units according to a preset rule so as to establish a plurality of independent power islands; after the frequency and voltage of each power island are stabilized, power is supplied to a next-stage transformer substation or power station in parallel, and partition collaborative recovery is carried out; dynamically distributing a load to be recovered, and performing synchronous parallel operation by using real-time phase angle difference data provided by a synchronous phasor measurement unit (PMU); and carrying out synchronous parallel operation on a plurality of subsystems which are stably operated, and gradually expanding a power grid architecture.

The present disclosure belongs to the technical field of power system restoration, and particularly relates to an orderly black start method and system of a new energy power generation unit, comprising: acquiring system parameters of the new energy power generation unit; constructing a black start system model of the new energy power generation unit based on the acquired system parameters; evaluating the black start capability of the constructed black start system model to obtain a black start utility output of the new energy power generation unit; and optimizing the start order of the new energy power generation unit according to the acquired system parameters of the new energy power generation unit and the obtained black start utility output, combining an orderly participation algorithm to complete the orderly black start of the new energy power generation unit.

The invention relates to the technical field of power system stability control, and provides a new energy black-start partition optimization method considering unconventional risks, which comprises the following steps: simulating unconventional risks possibly encountered by a power system by adopting Monte Carlo sampling; extracting the output characteristics of wind power under the unconventional risk by adopting variational mode decomposition, and performing output prediction in combination with a long-short-term memory neural network; a power system recovery partition is divided based on an LPA algorithm, and the LPA algorithm is improved by considering a partition size balance principle, so that the partition area is more balanced, and the tag oscillation effect is reduced. According to the method, the black-start partition optimization model fusing new energy output uncertainty modeling and unconventional risk scene generation is designed, and the partition scheme is cooperatively solved by adopting the improved label propagation algorithm, so that the robustness and the recovery efficiency of the black-start partition are effectively improved; and rapid and stable power supply of a power system under complex disturbance can be realized.

The invention relates to an equipment fault analysis method and device, computer equipment and a readable storage medium. The method comprises the following steps: constructing a structural modal map and a semantic modal map according to equipment identifiers, equipment icons and a physical connection relationship among equipment, obtaining equipment identifiers and fault phenomena of fault equipment, generating a fault propagation chain containing fault equipment nodes based on the equipment identifiers, the structural modal map and the semantic modal map of the fault equipment, and transmitting the fault propagation chain to the fault equipment. Determining a device priority processing sequence of each device node in the fault propagation chain, determining a fault reason from a historical case library based on the device identifier of the fault device and the fault phenomenon, and generating a fault processing suggestion of each device node in the fault propagation chain according to the device priority processing sequence and the fault reason; the fault positioning efficiency can be obviously improved, the maintenance resource scheduling is optimized, and the power system recovery time is shortened.

The invention discloses a power system recovery method and system considering social functions and load starting characteristics, and belongs to the technical field of power supply recovery of power systems. The method specifically comprises the steps of solving a power supply recovery importance degree parameter according to absolute power failure duration; solving a correction coefficient of the power supply recovery importance degree parameter considering the social function; correcting the power supply recovery importance degree parameter by using the correction coefficient of the power supply recovery importance degree parameter considering the social function to obtain the power supply recovery importance degree of the user; solving a node power supply recovery importance degree considering a topological connection correction coefficient; and according to the node power supply recovery importance considering the topological connection correction coefficient, generating a power supply recovery strategy, and realizing power system recovery considering social functions and load starting characteristics. According to the invention, the accuracy of resource allocation is improved, and the additional economic loss in the power supply recovery process is reduced.

The invention provides a power system transient voltage control method and system. The method comprises the following steps: acquiring initial power system operation state parameters in real time and establishing a transient model; obtaining an initial transient voltage severity index based on the parameters and a preset initial voltage; constructing a physical information neural network based on the transient model and exporting a loss function of the physical information neural network; based on the parameters, a preset reward parameter and a noise network, obtaining an initial Rainbow agent, executing a removal action and calculating corresponding loss; and constructing a total loss function based on the total loss function and training to convergence by taking minimization as a target, and obtaining an intelligent agent to realize the control of the transient voltage of the power system. According to the method and the system for controlling the transient voltage of the electric power system, the electric power system can be rapidly controlled to recover stability, the situation that the transient voltage control decision is not accurate due to the fact that the action value is excessively estimated is avoided, and the situation that the instability degree of the electric power system is aggravated is further prevented.

The present invention discloses an inverse-time interactive rapid sorting method for the similarity of massive power grid topologies. The edit distance between two power grid topology diagrams is used as the similarity index between the two power grid topology diagrams. Through a series of editing operations, the power grid topology diagram A is made isomorphic to the power grid topology diagram B. The sum of the edit costs of this series of editing operations is called the path cost of the edit path. The edit path with the minimum path cost is found through path search, that is, the optimal edit path. The minimum path cost corresponding to this optimal edit path is used as the edit distance between the power grid topology diagram A and the power grid topology diagram B. Using the edit distance between two power grid topology diagrams to measure the similarity of power grid topology diagrams can realize the comparison and sorting of the similarity of power grid topology diagrams, and can find the power grid topology with the highest similarity from massive power grid topologies, thereby providing a reference for fields such as the preparation of new equipment startup plans for power grids and the formulation of power system restoration plans after faults.

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.

This invention belongs to the field of power system restoration technology, and relates to a method and apparatus for dynamic partitioning of new energy power systems during black start based on Voronoi diagrams. The method includes: mapping black start power sources to Voronoi generators and mapping loads to be restored to Voronoi spatial points; acquiring generator capacity information and generating reliable capacity for new energy black start power sources; generating adaptive weights based on capacity information, reliable capacity, and load density; adjusting the diffusion speed of generators in different directions according to the adaptive weights and performing weighted Voronoi diffusion to obtain preliminary partitions; performing partition constraint verification during diffusion and controlling the corresponding generator to exit diffusion when the constraint reaches the upper limit; triggering update calculation based on new energy output information fed back by SCADA and outputting the partition results. The technical solution of this application can realize online partition updating and executability determination.

The application provides a partition method, device and equipment for power system outage recovery and a storage medium. The method comprises the following steps: determining a guarantee area based on the number and capacity of black-start power sources and the starting power of to-be-recovered conventional units and the node load power; including nodes and branches based on the rated power of the to-be-recovered conventional units in the guarantee area to obtain a feasible area; and determining the partition attribution of a new energy station based on the support power provided by the new energy station and the new energy consumption capacity of each partition in the feasible area to obtain an expanded area. The method can improve the execution efficiency of the power system recovery scheme.

The invention provides a deep reinforcement learning power grid reconstruction method and device based on high-precision wind power prediction. The method comprises the following steps: selecting an action for a grid reconstruction model by utilizing an action selection function; the action selection function is used for measuring the selected priority of an unrecovered node based on the shortest distance between the unrecovered node which is not selected in the target power system and the node of the unrecovered unit; if the action meets the action constraint condition, executing the action, rewarding the net rack reconstruction model based on the shortest distance between the recovered node and the node of the unrecovered unit, and continuing iteration; the action constraint condition comprises a wind power plant output constraint, a system frequency modulation capability constraint constructed based on a first electrical attribute parameter of a new energy unit, and a grid voltage support capability constraint constructed based on a second electrical attribute parameter of a new energy station grid-connected node. According to the invention, new energy can be introduced to participate in power system recovery and optimize the power transmission path, and the net rack reconstruction effect is improved.

The utility model discloses an automatic power system recovery device which comprises an installation frame, a fixing assembly is installed on the back face of the installation frame, a first insulation pad is laid in the installation frame, and a first connecting assembly and two second connecting assemblies are installed on the front face of the first insulation pad respectively. A mounting assembly is mounted on the front face of the mounting frame, a lifting assembly is mounted in the mounting assembly, and the first connecting assembly comprises a first conductive plate and a first wiring cylinder. The lifting assembly installed in the device can drive the two conductive clamping plates to descend respectively, so that one conductive clamping plate is connected with one first connecting clamping piece and one second connecting clamping piece, and the two second connecting assemblies can be connected with the first connecting assembly. Therefore, switching between the normal power supply and the standby power supply is facilitated, and the problem that the standby power supply is inconvenient to switch by an existing device is effectively solved through the device.

The invention provides a hybrid power ship energy recovery and optimization method and a control system. The method is used for balancing recovery schemes and carrying out optimization control according to the recovery schemes. The electric power system structure of the hybrid power ship is converted into knowledge which can be understood by an expert system through the directed graph theory, the overall reliability index of the electric power system recovery scheme is defined based on the directed graph theory, and the decision of balancing the electric power system recovery scheme is participated. Factors, such as power line transmission efficiency, switching operation times, switching operation time, distance, line reliability and overall reliability of a recovery scheme, influencing hybrid power ship power system fault recovery are calculated through a target function to participate in balancing of the recovery scheme. Furthermore, according to a capability control method with nonlinear model predictive control as a core, cost function design is carried out on a balanced recovery scheme with fuel consumption and power of a power generation device as core indexes, and energy optimization control is carried out.

The invention provides an electric power system recovery stochastic optimization method and system considering network construction type energy storage auxiliary black start, and the method comprises the steps: constructing a network construction type energy storage mathematical optimization model for a power grid recovery process based on discrete time steps; embedding the network construction type energy storage mathematical optimization model into a black-start power system recovery stochastic optimization model, wherein the optimization target of the power system recovery stochastic optimization model is that the sum of the full-time recovery load power, the recovered rated power of the thermal power generating unit and the output of the new energy unit in each time step reaches the maximum; and outputting a recovery strategy through the power system recovery stochastic optimization model, and recovering the black-start power system. The method provided by the invention can improve early-stage network formation capability and frequency and voltage stability margin, increase available load and accelerate a recovery process, and is suitable for black start recovery of a high-proportion new energy power system.

This invention provides a power system restoration method, system, medium, and electronic equipment using black-start power sources, comprising: establishing the frequency-power response characteristics of a first preset generating unit and a second preset generating unit working collaboratively; obtaining a target frequency response model under power deficit conditions due to a load surge based on the frequency-power response characteristics of the collaborative operation; determining the constraints of the power system based on the target frequency response model; obtaining the target frequency response result of each black-start power source to the power system upon startup, combined with the target frequency response model; determining multiple power aggregation methods for each black-start power source based on the target frequency response results and the constraints; and determining the optimal restoration path for each black-start power source in the shortest time based on the shortest path algorithm and each power aggregation method, so as to restore the power system according to the optimal restoration path. This invention solves the problem of low adaptability of existing black-start methods.

The present invention provides a power system restoration zoning method and device considering sub-area structure and scale. The method comprises the following steps: abstracting the topology of a power grid to be partitioned, constructing a weighted topology map of the power grid and obtaining an adjacency matrix, establishing a power system zoning model based on the principle of a label propagation algorithm, calculating a label propagation probability matrix, initializing a label classification matrix according to the position of a black start power supply node, introducing a sub-area scale matrix and a historical influence factor into the propagation strategy of the label propagation algorithm, propagating node labels according to the improved label propagation strategy to obtain a label influence matrix, updating the label classification matrix, and simultaneously restoring the label information of the black start power supply node. The node label propagation process is repeated until the label classification matrix converges, and the power system zoning result is output. The power system partitions obtained by the present invention have strong community structure characteristics and similar scales, which reduces the waiting time for interconnection of power system partitions and improves the efficiency of parallel restoration of the power system.

The invention discloses a power grid partition parallel recovery two-stage optimization method considering multi-source cooperation, and relates to the technical field of power system recovery. The method comprises the following steps: providing basic conditions for the new energy power generation system to participate in black start, and determining the number and type of black start power supplies; constructing a power grid partition optimization model based on a network flow theory in a first stage; and establishing a power grid partition parallel recovery optimization model considering multi-source cooperation in a second stage, and realizing rapid recovery of the power system taking the wind-light-water-storage multi-source cooperation as the black-start power supply. According to the invention, complete recovery of each generator set, power transmission line and power load in a power-off power grid can be realized, and the problems of long recovery process and important load recovery failure possibly caused by a serial recovery strategy are effectively solved. Meanwhile, the invention provides a power grid partition parallel recovery optimization model taking wind-light-water-storage multi-source cooperation as a black-start power supply, and the problem of insufficient black-start resources possibly existing in a local power grid is effectively solved.

The present invention discloses a multi-region and multi-stage plant-grid coordinated restoration method and system, which models the power system restoration problem by using a sub-region and sub-stage coordination method. In the power generation and transmission system, it considers maximizing the power generation of units under the reconstruction of the backbone network; in the distribution system with distributed power sources, it considers minimizing the load loss; by changing the plant-grid coordinated restoration penalty function to represent the contribution degree of distributed power sources in the distribution system to the power generation and transmission system at different time periods, it realizes the time-sharing support of the black start capability of distributed power sources for the power system restoration. The present invention can be used as an important auxiliary tool in the post-disaster restoration process of the power system, comprehensively providing sufficient decision-making guidance for power system operators and providing a reference for the identification of key nodes.

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.

A method for controlling power restoration of a power grid is disclosed. The method includes setting initial conditions on the power grid based on a combined model of the power grid, setting the initial conditions including at least one of controlling a plurality of field components of the power grid or sending information for controlling the plurality of field components, wherein controlling the plurality of field components includes opening a plurality of breakers, and performing a first iterative process including: performing a balancing operation that includes determining if a frequency of a black start generator of the power grid meets generator criteria, determining if a voltage of a generator voltage bus of the power grid meets bus criteria, or determining if an MW of an isochronous generator of the power grid meets MW criteria.

The invention discloses a power grid black-start path optimization method and system, and belongs to the technical field of power system recovery control, and the method comprises the steps: obtaining power prediction data based on the inherent uncertainty of the output power of a new energy station; constructing a black-start path optimization model according to the power prediction data; according to the power grid black-start path optimization method and system, a traditional A star algorithm is improved by introducing the weight coefficient, the path smoothing strategy and other strategies, and a black-start path optimization strategy with higher applicability is provided for a novel power system after new energy is accessed. The stability of the power grid in the black-start recovery process is ensured, and the problem that a traditional black-start path optimization algorithm cannot fully consider new energy output characteristics is solved.

The utility model provides a protection system of a standby power device and a wind generating set. The protection system of the standby power device comprises the standby power device which comprises a battery; a power conversion module connected to the standby power device via a first switch and connected to an external power supply via a second switch; the voltage sensor is used for detecting the voltage of the standby power device; and the controller is used for receiving the voltage signal output by the voltage sensor and controlling the first switch and the second switch to be switched on and switched off. When the power conversion module stops output, the standby power device is disconnected from the electric equipment to protect the standby power device, and when the main power system recovers power supply, the standby power device is automatically charged to prolong the service life of the standby power device. In addition, the charging state of the standby power device is monitored, so that reliable operation of the power system is improved, and the standby power device is protected.

The invention relates to the technical field of power system recovery and operation control, and particularly provides a thermal power generating unit black-start method based on an electric vehicle V2G technology, and the method comprises the steps: obtaining the V2G real-time resource state of each charging station in a to-be-recovered region of a power grid, and carrying out the local integration and evaluation, and obtaining the overall usable discharge resource of each charging station; collecting the total available discharge resource information of each charging station to form a regional V2G cluster, and performing safety check on the regional V2G cluster based on the black start load curve of the target thermal power generating unit; after the security check is passed, generating a black-start execution scheme, and constructing an island microgrid powered by a V2G cluster; and the V2G cluster is controlled to be divided into two stages to recover station power for the thermal power generating unit, and the V2G cluster is smoothly quitted after the unit is started. According to the scheme, a dynamic and reliable black-start power supply is formed by integrating the V2G capacity of a large-scale electric vehicle, and initial power and auxiliary power are provided for a thermal power generating unit, so that the recovery process of a power grid is accelerated, and the toughness and reliability of the power grid are improved.

The invention discloses a transient stability emergency control method and device based on Rainbow reinforcement learning, and the method comprises the steps: training an agent through setting a training strategy, and obtaining a trained agent; monitoring equipment is set to monitor the power system, and monitoring data of the power system are obtained; acquiring fault disturbance through the monitoring data; performing transient stability judgment on the fault disturbance through a transient stability index, and if the transient state is stable, recovering the stability of the power system; if the transient state is unstable, acquiring state data of the power system, and performing emergency control processing; inputting the state data of the power system into a trained intelligent agent; the intelligent agent makes a decision through a deep reinforcement learning Rainbow algorithm and outputs an emergency control strategy; and the power system carries out emergency control processing according to the emergency control strategy and restores stability. The method can quickly adapt to emergencies, optimize resource configuration, reduce power failure time and improve power supply reliability.

The present invention discloses a method and system for assessing the resilience of a power system that takes uncertainty into account. The method includes: obtaining various types of data on the power system after experiencing an extreme disaster; constructing a component failure rate model dynamically associated with the power system recovery decision based on decision-dependent uncertainty; generating a power outage scenario based on the acquired data and the component failure rate model, taking into account the uncertainty of the state of some components; establishing a correlation matrix between state uncertainty and faulty components based on grey correlation theory, calculating the damage confidence of the state-uncertain components, and screening out typical power outage scenarios using system information entropy; constructing a multidimensional power system dynamic resilience assessment index system based on renewable energy output uncertainty; and calculating assessment indicators to conduct resilience assessment. The present invention integrates decision-dependent uncertainty, component state uncertainty, and renewable energy output uncertainty, making the assessment results more closely reflect the complexity of actual post-disaster scenarios.

The present invention proposes a power supply method and computer-readable medium for optimizing the placement of black start power sources. The present invention uses minimizing the black start recovery time of non-black start power source nodes as the objective function, optimizes the selection of multiple black start power source nodes from multiple black start power source nodes as restoration power supply nodes, and uses the capacity of the restored black start power source nodes as decision variables to construct a multi-black start power source placement optimization model with minimizing the black start recovery time as the objective. The multi-black start power source placement optimization model is solved based on the Coyote optimization algorithm. The Coyote optimization algorithm is improved by improving the Coyote growth model and introducing adaptive Levy flight and chaotic perturbation mechanisms to obtain the optimal placement location capacity for power restoration in the distribution network. The present invention has stronger global optimization capabilities, high algorithm accuracy, and strong stability. It can distribute multiple black start power sources more evenly across a topological network, shortening the power system recovery time.

This invention relates to power system restoration technology, and discloses a load splitting restoration method, system, equipment, and medium. The method responds to a self-healing restoration request from a distribution network line fault, identifies restoration switches and disconnect switches, and determines the area to be restored. It assesses the load in the area to be restored and the load of the outgoing switches on the opposite line to determine if there is an overload risk. If an overload is detected, restoration is performed through load transfer switches and disconnect switches based on the electrical topology. This invention solves the problem of insufficient load transfer in the area to be restored due to excessive load on the faulty line or excessive original load on the opposite line, thus avoiding self-healing program lockout. Addressing the issue of excessive load in the area to be restored due to a faulty line or excessive original load on the opposite line, this invention effectively reduces the outage area and impact through a load splitting self-healing restoration strategy, restoring power to non-faulty areas as much as possible and significantly improving the reliability of the distribution network.