63 results about "Power vector" patented technology

The invention provides a power grid system control method and device, computer equipment and a storage medium in the field of power grid system control, and the method comprises the steps: firstly, determining a dynamic inertia coefficient through integrating node frequency deviation, an energy storage charge state and voltage deviation, calculating inertia compensation power through employing the frequency deviation, precisely capturing the dynamic characteristics of a system, and carrying out the calculation of inertia compensation power; and constructing a target function based on the equivalent impedance matrix and the power deviation, solving a target control sequence under constraint conditions, realizing system power optimization distribution, and further adjusting node power output from multiple aspects by determining composite inertia, synthesizing inertia power, regulating and controlling a power vector and an inertia matrix. And finally, based on energy function construction and partial derivative calculation, generating a control instruction of each node. The steps can effectively deal with system power disturbance, rapidly compensate insufficient inertia, optimize power distribution, maintain system frequency stability, improve safety, reliability and stability of operation of a power system, and enhance adaptability of the system to complex working conditions.

The invention discloses a power distribution area energy storage control and capacity configuration method, system, equipment and medium, and the method comprises the steps: firstly, setting a plurality of different energy storage control strategies according to a preset discharge lower limit and a preset charge upper limit of an energy storage device of a power distribution area in combination with the residual capacity condition of the energy storage device; then, on the basis of time-of-use electricity price data and load data of the power distribution area, according to an energy storage control strategy, an objective function composed of the minimum operation cost of the power distribution area, the maximum photovoltaic consumption rate of the power distribution area and the minimum net load variance of the power distribution area is constructed; solving the objective function through an optimization algorithm to obtain a charging and discharging power vector of the energy storage device; and finally, calculating the optimal configuration capacity of the energy storage device according to the charging and discharging power vector of the energy storage device. According to the invention, the problems of too low photovoltaic consumption rate and too high total cost are solved, and the stability of the power grid is improved.

The invention discloses a fault identification and prediction method based on low-voltage distribution network topology modeling and an intelligent algorithm. Aiming at the problems of low fault positioning efficiency, insufficient intelligence and the like of the low-voltage power distribution network, the method realizes fault full-process processing through multi-module cooperation: firstly, collecting data such as voltage and current in real time through an Internet of Things terminal, and constructing a high-quality data set in combination with edge calculation and a four-step preprocessing technology; secondly, constructing a separated complex-valued neural network, and inputting a plurality of voltage and power vectors to realize accurate prediction of loop closing current and voltage deviation; reasoning fuzziness of equipment states and environmental factors through a fuzzy network, outputting TOP3 fault reasons, and tracking a fault propagation path for accurate positioning in combination with a shortest path algorithm and a D-S evidence theory; and finally, generating a switching operation sequence and a digital twinborn verification recovery scheme through an improved matrix algorithm. According to the method, the problems of dynamic modeling, uncertainty reasoning and the like are solved, and technical support is provided for intelligent operation and maintenance of the power distribution network.

The invention relates to the technical field of mathematical modeling, and discloses a modeling method for a power business decision model, and the method comprises the steps: constructing a power corpus block library and a power vector knowledge library, and determining a power business problem text; performing mixed retrieval on the power business problem text by means of a power corpus block library and a power vector knowledge library to obtain a first similarity score corresponding to a candidate corpus block and a second similarity score corresponding to a candidate document representation vector; screening the candidate corpus blocks and the candidate document representation vectors based on the first similarity score and the second similarity score, and determining a target reference text; inputting the power business problem text and the target reference text into a target large language model to obtain a target decision model; the target decision model comprises a description text of the power business problem, a target function and constraint conditions thereof. The method has the beneficial effects that the reliability and the accuracy of the target decision model are remarkably improved based on standard output of the hybrid retrieval and the large language model.

The invention relates to a high-order analysis power flow and carbon flow tracking method based on full-pure embedding, and the method comprises the specific steps: introducing a complex embedding parameter s, constructing a node voltage vector, an injection power vector and a tracking matrix in a power grid power flow equation into an analysis power series and an analysis power series of the complex embedding parameter s based on the analysis continuation characteristic of full-pure embedding, solving a node voltage initial value when the power grid is in a basic operation state by adopting a Newton-Raphson method; calculating a zero-order line active power vector based on the node voltage initial value, and constructing a zero-order distribution matrix representing a power distribution relation in a basic operation state of the power grid; solving a zero-order power flow tracking matrix based on the zero-order line active power vector and the zero-order power distribution matrix; calculating node indirect total carbon emission based on the zero-order power flow tracking matrix; and replacing the power distribution matrix, the node outflow power and the power flow direction matrix in the zero-order power distribution matrix with power series expansion of corresponding variables.

The invention relates to the technical field of digital ring main unit power distribution operation regulation and control, and discloses an intelligent power distribution operation regulation and control system of a digital ring main unit, which comprises a state sensing module, a logic judgment unit and an execution regulation and control module, the logic discrimination unit identifies a feeder power distribution state according to the power flow distribution data and generates a topology reconstruction scheme; the execution regulation and control module drives a switch to act, migrates the feeder loop to a target bus section, forms transition impedance by using closing pre-breakdown current during migration, inhibits transient inrush current, drives an impedance compensation branch to access according to a zero-sequence current vector of the feeder loop, and counteracts neutral point potential drift by using potential bias generated by reactive power injection; according to the method, the power distribution topology is converted from static hard connection to logic remapping, circuit transient state physical process reconstruction and stock hardware redundancy mining are utilized, node power vector balanced distribution is achieved under the condition that the feeder line continuous power receiving state is maintained, and power flow randomness conflicts are eliminated.

The invention discloses a power demand response collaborative optimization method and device based on flexibility sharing, equipment and a medium, and relates to the technical field of power system demand response, and the method comprises the steps: obtaining load flexibility demands and load flexibility supply cost information reported by all target users participating in power demand response collaborative operation; the load flexibility demand is a power vector difference between an actual load curve and a standard load curve after each target user independently adjusts the load, and the load flexibility demand and the load flexibility supply cost information are input into a preset power demand response collaborative optimization model; determining a corresponding power demand response collaborative scheme through a preset power demand response collaborative optimization model; and executing the power demand response coordination scheme to perform flexible settlement and flexible transaction surplus distribution according to the execution condition of the target user. The execution of a demand response cooperation scheme based on flexibility sharing is realized, and the economical efficiency and reliability of load regulation are improved.

The invention discloses a multi-target operation optimization method and system for an optical storage micro-grid, and relates to the technical field of new energy power system optimization, and the method comprises the steps: carrying out the collection and digital twinning mapping to form a health semantic graph as a state base; calculating an equilibrium priority index on the health semantic graph in a self-adaptive clustering manner to generate a health weight; dynamic weights are fused, charge and discharge power proportions are distributed according to clusters, and health constraint, aging suppression and load response collaboration are achieved; inputting the updated electric quantity vector and the predicted aging trajectory into a multi-target scheduling solver, and synchronously optimizing energy consumption cost, carbon emission estimation and frequency deviation penalty to form a planned power sequence; when the sudden change of the electricity price or the load is detected, the solver agent model is called to quickly recalculate the plan and write the plan back to the health semantic graph to ensure that the control strategy evolves along with the scene. Through mutual feedback and control interlocking of each layer of information, the overall gain of power grid frequency difference convergence and comprehensive operation cost reduction is realized.

A power-imbalanced multi-level decoding method for sparse code multiple access includes: encoded bits of all users are mapped to multi-dimensional sparse codewords through predetermined codebooks; a factor graph matrix is constructed using the predetermined codebooks, all users are classified according to the factor graph matrix under predetermined constraints to determine Z levels; based on a predetermined total transmission power, a progressive multi-level power optimization algorithm is employed to perform power-imbalanced allocation for all users according to the Z levels, thereby determining a locally optimal power vector; transmission signals corresponding to the multi-dimensional sparse codewords are transmitted according to the locally optimal power vector; SCMA detection and power-oriented decoding are sequentially performed for users each level, and outputs decoded bit sequences for the L levels.

The invention relates to the technical field of unmanned aerial vehicle communication, in particular to an unmanned aerial vehicle group collaborative awareness method and system, and the method comprises the steps: obtaining the distance between APs and a routing table updating period in the unmanned aerial vehicle group collaborative awareness process; the method comprises the following steps: acquiring a metric value weight of connection establishment between each AP and a next hop AP in a communication connection path, selecting an optimal routing path between unmanned aerial vehicles, calculating a power adjustment characteristic value between each AP and other APs which establish communication connection with each AP, acquiring a subcarrier interference characteristic value of each power vector, acquiring an optimal power vector of each AP by using a particle swarm optimization algorithm, and determining the optimal power vector of each AP according to the optimal power vector. And the sub-carrier transmission power is used as the sub-carrier transmission power of each AP in communication connection with the AP, and communication scheduling of the APs in the unmanned aerial vehicle group collaborative awareness process is completed. The communication performance in the cooperative sensing operation of the unmanned aerial vehicle group can be improved.

The invention discloses an identity authentication method and system for a power wireless local area network based on a block chain. The identity authentication method is characterized in that a terminal sends an authentication request containing a unique identifier to an access point; the AP responds to generate a challenge random number and a hash target value calculated based on the terminal historical time delay and the current load, and issues the challenge random number and the hash target value; the terminal collects real-time electric parameters of an electric power line within a limited time to generate a quantized electric power state vector, combines a challenge number and an identifier of the terminal, performs cascade Hash operation by traversing Nonce until a result is not greater than a target value, forms an activity proof containing the Nonce and the electric power vector, and submits the activity proof to the AP; after the AP verifies and proves the validity, randomly selecting a verification committee from a preset node pool by taking the hash value as a VRF seed; each node of the committee calculates a signature weight according to own equity pledge and a network topology distance between the node and the terminal, signs an authentication decision, attaches the weight and returns; and the AP aggregates all signatures with weights, and determines that the terminal authentication is passed when the total weight exceeds a preset threshold value.

This application relates to the field of mathematical modeling technology and discloses a modeling method for a power business decision-making model. The method includes: constructing a power corpus segmentation library and a power vector knowledge base to determine the power business problem text; performing a hybrid retrieval of the power business problem text using the power corpus segmentation library and the power vector knowledge base to obtain a first similarity score corresponding to candidate corpus segments and a second similarity score corresponding to candidate document representation vectors; filtering the candidate corpus segments and candidate document representation vectors based on the first and second similarity scores to determine the target reference text; and inputting the power business problem text and the target reference text into a target large language model to obtain the target decision model. The target decision model includes a description of the power business problem, an objective function, and its constraints. Its beneficial effect is that, based on hybrid retrieval and the standardized output of the large language model, the reliability and accuracy of the target decision model are significantly improved.

The application discloses a power demand response collaborative optimization method and device based on flexibility sharing, equipment and medium, relates to the technical field of power system demand response, and comprises the following steps: acquiring the load flexibility demand and load flexibility supply cost information reported by each target user participating in power demand response collaborative operation; the load flexibility demand is the power vector difference between the actual load curve of each target user after independently adjusting the load and the standard load curve; the load flexibility demand and load flexibility supply cost information are input into a preset power demand response collaborative optimization model, so that the corresponding power demand response collaborative scheme is determined through the preset power demand response collaborative optimization model; and the power demand response collaborative scheme is executed to perform flexibility settlement and flexibility transaction surplus distribution according to the target user execution situation. The execution of the demand response collaborative scheme based on flexibility sharing is realized, and the economy and reliability of load adjustment are improved.

The invention discloses an integrated sensing and backscatter communication method and device based on phase-free extension Rytov approximation, and relates to the technical field of communication, and the method comprises the steps: generating a modulation signal through a transmitting antenna based on the load impedance of a dynamic modulation tag, and backscattering the modulation signal to a receiving antenna to measure an RSSI vector, determining an environment object tag structure power vector and a tag antenna power vector, and after sensing and identifying a tag according to the determined combined xRA relative dielectric constant comparison vector and the tag antenna xRA relative dielectric constant comparison vector, activating the tag through a transmitting antenna and transmitting communication data to a receiving antenna by adopting ASK (Amplitude Shift Keying) modulation; and demodulating by combining the environment object tag structure power vector, the tag antenna power vector and the RSSI vector corresponding to the communication data, and determining information bits. Sensing and backscatter communication are realized by adopting non-phase backscatter based on extended Rytov approximation, and backscatter communication which keeps stable is assisted on the whole.

The present application relates to the field of drone communication technology, and specifically to a drone swarm collaborative perception method and system. The method includes: obtaining the distance between each AP and the routing table update period during the drone swarm collaborative perception process; obtaining the metric weight of each AP in the communication connection path to establish a connection with the next-hop AP, selecting the optimal routing path between drones, calculating the power adjustment characteristic value between each AP and each other AP with which it establishes a communication connection, obtaining the subcarrier interference characteristic value of each power vector, and using a particle swarm algorithm to obtain the optimal power vector of each AP as the subcarrier transmission power of each AP with which each AP establishes a communication connection, thereby completing the communication scheduling of the AP during the drone swarm collaborative perception process. The present application can improve the communication performance in drone swarm collaborative perception operations.

The invention discloses a complex valued neural network dynamic modeling method for power grid fault identification and prediction, and relates to the field of smart power grids. According to the method, a separated complex valued neural network is constructed, voltage phasors and power vectors in a complex number form are input, and power grid characteristics are extracted through not less than 3 complex number convolution layers and not less than 2 full connection layers. And training the model by using historical loop closing operation data not less than 100,000 times, wherein the training period does not exceed 4 hours. The model can accurately predict loop closing current amplitude and output voltage deviation, and a continuous prediction value is converted into a switch state decision signal through an embedded binarization module. According to the invention, the precision and efficiency of power grid loop closing operation and fault prediction are improved, and core model support is provided for intelligent operation and maintenance of the power grid.

An example system includes processing circuitry including n transmission paths; and a memory to store data specifying m of the n transmission paths that are operable for a first operation, m≤n. In operation, the processing circuitry starts performing the first operation on the m transmission paths; receives a signal for a second operation to be performed on p transmission paths, p≠m, and in response, preserves the data stored in the memory and stops performance of the first operation. Thereafter, the second operation is performed on the p transmission paths to completion, after which the data is restored to the memory, and performance of the first operation on the m of transmission paths is resumed.

The invention belongs to the technical field of radar signal processing, and discloses a multi-input-output radar target direction estimation method and system based on tail optimization. The method comprises the following steps: performing matched filtering and vectorization processing on a received signal to realize the expansion and structured expression of an MIMO signal aperture; re-parameterization of a guiding matrix is achieved by conducting structure rearrangement on a vectorization result of a received signal covariance matrix, and unknown amplitude-phase error factors in the guiding matrix are extracted from a guiding structure and fused into an equivalent signal power vector. According to the method, high-resolution and low-complexity target direction estimation is realized through a structure reconstruction and tail optimization mechanism under the condition that complex amplitude-phase error correction or priori error information acquisition is not needed, and the method is suitable for an MIMO radar system in various actual complex scenes.

A power monitoring system includes one or more power vector analyzers, and a power controller having one or more ports to receive transient event data comprising one or more power images and associated metadata for a transient event from the one or more power vector analyzers, and one or more processors configured to execute code to cause the one or more processors to convert the one or more power images from the one or more power vector analyzers and the associated metadata to one or more transient event vectors, and store the one or more transient event vectors in a vector database.

A power distribution method for a redundant electric drive system. The method comprises: on the basis of drive objectives on shafts and states and parameters of batteries and electric motors, determining constraint levels of the batteries, so as to set the maximum power of each battery pack; calculating an optimal power configuration of each battery pack, and on the basis of the optimal power configuration, setting a power matrix, a disturbance term and a target power vector; determining the constraint level of each electric motor, and on the basis of the constraint level, adjusting the power matrix and the disturbance term; on the basis of a full-rank condition for the power matrix and a rationality condition for a power distribution ratio, determining whether a rational power ratio can be obtained; if the conditions are not met, removing constraints layer by layer in ascending order until the conditions are met, otherwise, notifying an upper-layer controller or an upper-layer control module for processing; and on the basis of the obtained power ratio, calculating an output power of each electric motor. The method provides a general method for optimizing the power distribution of a redundant electric drive system under constraint conditions of different levels, thereby simplifying design and development, shortening development cycles and reducing costs; and calculation costs are low, and the method can be implemented in a real-time control system.

The invention relates to a wavelength and power optimization method based on pellet clustering in a wide-spectrum-domain optical communication system, and belongs to the technical field of optical fiber communication system optimization. According to the method, the problem of low spectrum efficiency caused by limited capacity of a traditional single-band system, channel parameter frequency dependence in multi-band transmission and nonlinear interference accumulation is solved. According to the technical scheme, the method comprises the following steps: constructing a particle swarm model to jointly optimize wavelength selection and power distribution, and defining a particle structure comprising a binary decision variable and a continuous power vector; screening low-contribution particles in combination with natural particle ball clustering in iteration, and dynamically updating the speed and the position of the particles; and calculating a channel signal-to-noise ratio based on a wavelength correlation model of optical fiber loss, dispersion spectrum and nonlinear interference, wherein the optimization target is to maximize the throughput of the system. The method has the technical effects of remarkably improving the multi-band transmission capacity, inhibiting nonlinear interference accumulation, reducing channel performance difference, avoiding the repeated laying cost of optical fibers, and enhancing the global search efficiency and dynamic environment adaptability of the algorithm.

This invention provides a multi-power vector thruster and aircraft based on a staggered layout, comprising two or more basic thruster units stacked longitudinally. Adjacent thruster units are connected by connectors, with a first interface and a second interface on opposite sides of the connectors. Each adjacent thruster unit is connected to both the first and second interfaces via a stator. The axes of the thruster units connected to the first interface and those connected to the second interface are parallel and spaced apart. This longitudinal stacking of multiple thruster units reduces the complexity of the control system design. Direct vector thrust control can be achieved through differences in thruster rotation speeds, avoiding the complex design and vulnerability of swashplate mechanisms. This design has fewer moving parts, making production and assembly more convenient. Furthermore, the multi-layered stacking design further utilizes longitudinal space, resulting in a smaller overall size after storage.

A method of locating an object transmitting a wireless signal in an environment having at least two receivers adapted to RSS values of the wireless signal of the object is presented. The at least two receivers have known locations and are communicatively connected to a common computing unit. The method includes determining, at a common computing unit, an optimized RSS value-based coordinate mapping function taking into account a line-of-sight path and a non-line-of-sight path using known positions of the receiver, the reflector, and the training object. The RSS values for the object and from each of the two or more receivers are aggregated and collated into a received signal power vector that contains a sum of the RSS values determined at all receivers for each individual object. For each object, a vector containing the RSS values received by the two or more receivers is mapped onto x-coordinates and y-coordinates of the environment using an optimized mapping function.

The invention belongs to the technical field of unmanned aerial vehicles, and particularly relates to an omnidirectional flight unmanned aerial vehicle based on a passive hinge type vector power system. Comprising a machine body, vector power systems and machine arms, the three machine arms are arranged on the machine body in the circumferential direction at equal intervals, and the tail ends of the three machine arms are connected with the three vector power systems correspondingly; the vector power system comprises a power system fixing frame, a two-shaft connecting piece and a plurality of power rotors, one end of the two-shaft connecting piece is rotationally connected with the vehicle arm, the other end of the two-shaft connecting piece is rotationally connected with the power system fixing frame, and the power rotors are arranged on the power system fixing frame. The power system fixing frame is of an H-shaped structure, and four power rotors are arranged at the four ends of the power system fixing frame correspondingly. The whole power vector is changed under the condition that no extra actuator is added, hovering in the air can be achieved in any posture, and omni-directional movement is achieved under the condition that any posture is kept.

This invention relates to the field of digital ring main unit (RN) power distribution operation and control technology, and discloses an intelligent power distribution operation and control system for digital RN, including a state perception module, a logic discrimination unit, and an execution control module. The logic discrimination unit identifies the power distribution status of the feeder based on power flow distribution data and generates a topology reconfiguration scheme. The execution control module drives the switch action to migrate the feeder circuit to the target bus section. During the migration, the pre-breakdown current of the closing circuit is used to form a transition impedance to suppress transient inrush current. The zero-sequence current vector of the feeder circuit drives the impedance compensation branch connection, and the potential bias generated by reactive power injection is used to offset the neutral point potential drift. This invention realizes the transformation of the power distribution topology from static hard connection to logical remapping. By utilizing the reconstruction of circuit transient physical processes and the mining of existing hardware redundancy, the power vector distribution of nodes is balanced while maintaining continuous power supply to the feeder, thus resolving random power flow conflicts.

The embodiment of the invention discloses a wind power climbing event probability prediction method based on time-frequency double domains, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining NWP data and wind power data of a historical time period, obtaining NWP data of a future time period, and carrying out the construction to obtain multi-channel time sequence data; inputting the multi-channel time sequence data into the trained wind power prediction model, and predicting to obtain a wind power distribution vector of a future time period; sampling based on the wind power distribution vector to obtain a plurality of time sequence wind power vectors, performing climbing event detection based on a revolving door algorithm, and extracting to obtain each climbing event; and carrying out statistics on various event characteristics of each climbing event, and outputting probability distribution. According to the method, the probabilistic information of the climbing event characteristics can be obtained on the day-ahead scale, so that a power grid dispatcher can have more perspectiveness, and the problem of unbalanced electric power and electric quantity caused by the wind power climbing event can be solved by adopting different types of system adjustable capacities more effectively.

The invention provides a power flow section stability boundary online calculation system and method based on multiple agents. The method comprises the steps that power grid operation state data, a power grid power flow section, the increasing direction of a power vector of the power grid power flow section and a voltage phase angle initial value of a boundary bus are obtained; power grid regions are divided based on the power grid operation state data, and each region is correspondingly provided with a region intelligent agent; determining a to-be-analyzed power grid power flow section in the power grid power flow sections by using the central coordination agent, packaging the increasing direction of the power vector of the to-be-analyzed power grid power flow section and the initial value of the voltage phase angle of the boundary bus into a calculation instruction, and issuing the calculation instruction to the regional agent; adopting an MAPPO algorithm to calculate the stability boundary of the to-be-analyzed power grid power flow section of the region; and removing abnormal data, and generating an analyzed power grid power flow section stability boundary. According to the invention, the stability and reliability of multi-agent cooperation can be guaranteed, and the intellectualization and high efficiency of power grid power flow section stability boundary calculation are improved.

The invention relates to the technical field of smart power grids, and particularly discloses a load resource checking method based on load identification, which comprises the following steps of: firstly, performing equipment-level load decomposition on an original electrical data stream to obtain a theoretical power vector representing the physical operation state of equipment; meanwhile, state vectorization processing is carried out on context data flow from a user service system so as to construct a global context state vector reflecting real-time service constraints. Then, utilizing the global context state vector to execute potential constraint gating and dynamic potential calculation on a theoretical power vector, and generating a dynamic potential vector fused with business constraints; and finally, the total adjustable potential of the user side is determined based on the dynamic potential vector, so that the checking result can accurately reflect the real schedulable capability of the equipment in a specific service scene, and the difference between the theoretical potential and the actual potential is effectively bridged.

The invention relates to a power grid load flow calculation method and device based on a unified framework and a medium, and belongs to the technical field of power systems, and the method comprises the following steps: constructing an admittance matrix of power grid nodes, and obtaining a voltage real part and a voltage imaginary part of the admittance matrix; acquiring an initial power vector of a power grid node; setting an embedding factor, and constructing a power flow recursion formula of PV nodes and PQ nodes in the power grid nodes based on the embedding factor, the voltage real part, the voltage imaginary part and the initial power vector; constructing the power flow recursion of the power grid based on the power flow recursion of the PV nodes and the PQ nodes; and solving the power flow recursion formula of the power grid to obtain the power flow of the power grid. According to the method, a complex all-pure embedded recursive relation is converted into a matrix equation form with a fixed structure, the excellent constant numerical characteristic of a coefficient matrix is fully reserved, and the load flow calculation implementation difficulty is fundamentally simplified.

The invention discloses a joint estimation method, system and equipment for broadband signal direction and signal source number, and belongs to the field of power systems, the method comprises the following steps: converting frequency domain data received by an underwater acoustic array into a sparse representation model based on a multi-frequency over-complete array manifold matrix; and performing iteration based on a probability model, so that the probability model iteratively updates each sparse signal and a current airspace power vector and a current gamma distribution rate vector of each sparse signal in the probability model according to the frequency domain data, the multi-frequency over-complete array manifold matrix and a gamma distribution shape parameter, when an iteration termination condition is satisfied, outputting a spatial domain power estimation vector and a signal source number estimation value; and performing linear approximation post-processing based on the spatial direction point corresponding to the spatial domain power estimation vector to obtain a direction estimation result of the broadband signal, so that the accuracy of the direction and source number estimation result of the broadband signal can be improved by implementing the method and the device.