44 results about "Power matrix" patented technology

The invention discloses an electric vehicle charging load prediction method in a low data quality scene, and relates to the technical field of electric vehicles, and the method comprises the steps: obtaining a first feature; setting a dynamic space-time weight factor according to the first feature; according to the dynamic space-time weight factors, vacancy values in the space-time associated charging power matrix are complemented, and complete target charging power matrix data are obtained; constructing a three-dimensional input tensor according to the complete target charging power matrix data; inputting the three-dimensional input tensor into a first model to obtain a charging load predicted value; performing trend verification on the charging load prediction value and historical charging load data to obtain a prediction trend; and if the difference value between the prediction trend and the historical trend exceeds a preset threshold value, correcting the charging load prediction value based on the change rate of the historical trend to obtain a target electric vehicle charging load prediction result. According to the method, high-precision load prediction can be realized, and powerful support is provided for power grid demand response.

The invention belongs to the related technical field of electric power measurement and calculation, and provides a photovoltaic green electricity source tracing method and system based on power distribution and dynamic boundary definition, which introduces enterprise consumption density parameters to judge whether green electricity in a region is completely consumed or not, prevents enterprises in a non-target region from participating in distribution, and cuts off the correlation of the distance to determine the consumption amount from the spatial dimension; green electricity is distributed based on the real-time load proportion of an enterprise, the absorption deviation caused by line impedance difference is thoroughly eliminated, and the equal distribution quantity fairness is achieved when the loads are equal; a generator power matrix, a node flow power matrix and a power flow tracking matrix are constructed according to a power grid real-time power flow calculation result, a core matrix and green power distribution quantity are dynamically updated along with power fluctuation, power change under the influence of distributed photovoltaic illumination / temperature can be matched in real time, and deviation caused by traditional static measurement is avoided.

The application provides a charging pile state prediction method, a computer readable medium and equipment, the method is a health index and double attention optimization GCN charging pile state prediction method, including load data acquisition, dynamic wavelet denoising, health index construction, health state prediction. The principle of the application is: firstly, the charging pile load data is collected and processed, and the server platform data and the voltage, current and power data in the charging station are integrated and processed; secondly, the original data is denoised by using dynamic threshold wavelet transform to obtain a charging pile state data matrix; thirdly, based on the voltage, current and power matrix of the charging pile load data, the health factors of the single state indicators of the charging pile are constructed by using the distance sparsity algorithm, and the health factors are fused into a health index according to the improved objective weighting method; finally, the health state of the charging pile is predicted by using a double attention optimization graph convolutional neural network.

This invention provides a modular offshore mobile platform, comprising at least two hull platforms and a flexible connecting device for flexibly connecting adjacent hull platforms. Each hull platform includes at least one modular platform unit, which includes an installation platform and multiple small boats. The installation platform is a truss frame, and the small boats are connected to at least a portion of the frame nodes of the truss frame. This invention selects a certain number of platform units according to the required size, shape, and function of the hull platform, assembles them into a hull platform, and then uses the flexible connecting device to flexibly connect the hull platforms and install the load. This invention employs a grid-distributed array of power sources to form a power matrix chassis, breaking through the limitations of traditional single propulsion modes and achieving high-speed navigation on the water surface. Relying on the independent control of each small boat, it can achieve highly maneuverable maneuvers such as turning in place, sharp-angle turning, and lateral crabbing, greatly enhancing flexibility and sea trial response capabilities.

The application discloses a power control method and device based on multi-source cooperation and a reconfigurable power matrix. The method comprises the following steps: in response to a charging power scheduling instruction, current power supply parameter sets corresponding to multi-source power supply modules are acquired; at least three-phase alternating current power grids, photovoltaic modules and energy storage modules are included in the current power supply parameter sets; according to a preset power supply mode decision strategy and the current power supply parameter sets, current on-off states of switch groups in the multi-source power supply modules and current charging power distribution strategies in the multi-source power supply modules are determined; and the current charging power distribution strategies are executed, so that the power control module charges the to-be-charged equipment connected to the charging terminal group. According to the conditions corresponding to the working parameters of the three-phase alternating current power grids, the photovoltaic modules and the energy storage modules in the multi-source power supply modules of the charging station, the power supply mode and the charging power distribution mode in the charging station can be flexibly adjusted.

The invention discloses a rural micro-grid maximum access capacity optimization method fusing demand response, and belongs to the technical field of micro-grids, and the method comprises the following steps: obtaining a typical load normalized power curve, demand response unit price and a power distribution network flow topological graph of a rural micro-grid; determining active power and reactive power of each node load, extracting standard power flow calculation nodes by combining the power flow topological graph of the power distribution network, establishing an active power balance equation and a reactive power balance equation of the power distribution network, and determining system constraint conditions of the power distribution network; and obtaining a node new energy injection power matrix, taking a system constraint condition of the power distribution network as a boundary, taking maximization of the new energy capacity of each node of the power distribution network as a target, and carrying out iterative updating on the new energy capacity of each node by adopting a particle swarm optimization algorithm to obtain the maximum new energy access capacity of each node of the rural microgrid. According to the invention, the problem of insufficient maximum access capacity under the condition that high-proportion new energy accesses the rural microgrid can be solved.

The application relates to the technical field of modulation identification, in particular to a self-adaptive integrated feature selection mixed signal modulation identification method, which comprises the following steps: dividing a received signal into a plurality of small signals by using a sliding window; determining the position where the mixed signal occurs and the position where the mixed signal ends based on the power matrix of each small signal, and extracting the mixed signal; performing feature extraction on the mixed signal, and constructing a feature set of the mixed signal; selecting each feature in the feature set by using five feature selection methods, namely, a minimum redundancy maximum correlation criterion selection method, a multi-cluster feature selection method, a correlation feature selection method, a recursive feature elimination selection method and a random forest feature importance selection method, and preliminarily screening five stable feature subsets; performing self-adaptive optimization on the five stable feature subsets by using an HGSO algorithm to obtain an optimal feature subset; and performing modulation identification based on the optimal feature subset to obtain a modulation identification result. The method effectively improves the efficiency and accuracy of mixed signal modulation identification.

This invention discloses a dynamic gain-controlled optoelectronic hybrid neural network computing system for low-altitude UAV rubble search and rescue, comprising a UAV camera, a convolutional neural network preprocessing module, a dynamic range adaptive matching module, a matrix calculation mapping control module, a weighted DAC module, an optical matrix calculation chip, a scaling restoration module, and a convolutional neural network post-processing module. The system identifies weak feature regions and performs adaptive gain amplification through the dynamic range adaptive matching module. The matrix calculation mapping control module adapts the optical calculation format, the optical matrix calculation chip performs high-speed, low-power matrix operations, and the scaling restoration module restores the true signal amplitude, ultimately outputting the target recognition result. This invention improves the accuracy of weak vital sign detection, reduces end-to-end latency and power consumption, adapts to UAV SWaP constraints, and is suitable for low-altitude UAV rubble search and rescue scenarios.

The embodiment of the invention discloses an energy storage equipment installation method and device, electronic equipment and a computer readable medium. A specific embodiment of the method comprises the steps of obtaining node topological data, parameter data of each line, a new energy output matrix, an active load matrix and a reactive load matrix; generating an active net injection power matrix and a reactive net injection power matrix; generating voltage deviation average data, an out-of-limit node number set, a node out-of-limit voltage sensitivity matrix and a power sensitivity matrix; generating a time sequence out-of-limit voltage sensitivity matrix; generating a time sequence power sensitivity matrix; determining an energy storage access point data sequence of the energy storage equipment; and controlling the mechanical arm to mount the at least one energy storage device to the corresponding at least one mounting point. According to the embodiment, waste of installation resources during installation of the energy storage equipment can be reduced.

This invention provides a modular, highly maneuverable, lightweight mobile platform with a power matrix structure, comprising at least two hull platforms and flexible connecting devices for connecting adjacent hull platforms. Each hull platform includes at least one modular platform unit, which includes an installation platform and multiple small boats. The installation platform is a truss frame, and the small boats are connected to at least a portion of the frame nodes of the truss frame. This invention selects a certain number of platform units based on the required size, shape, and function of the hull platform and assembles them. Then, the flexible connecting devices are used to flexibly connect the hull platforms and install the load. This invention uses a grid-distributed array of power sources to form a power matrix chassis, breaking through the limitations of traditional single propulsion modes and achieving high-speed navigation on the water surface. Relying on the independent control of each small boat, it can achieve highly maneuverable maneuvers such as turning in place, sharp-angle turning, and lateral crabbing, greatly enhancing flexibility and sea trial response capabilities.

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 discloses a power distribution network rapid automatic reclosing method based on a load balance coefficient, and the method comprises the following steps: S1, calling the power flow data of a line protection device after a fault occurs, and collecting the line power flow data once in real time at time intervals by a collection device, totally d power data; s2, calling the electrical load power of all loads of the line at d moments corresponding to the active power matrix at the line outlet; S3, solving the power generation power of the distributed power supply; s4, solving a weighted load balance coefficient; and S5, selecting different reclosing schemes according to the obtained weighted load balance coefficient. According to the invention, rapid reclosing can be ensured when the proportion of the distributed power supply and the load is in a feasible interval, and splitting reclosing can be ensured to be selected when the power generation power of the distributed power supply is too large, so that safe and reliable operation of the power distribution network is ensured to the greatest extent.

The invention discloses a circuit reclosing scheme selection method suitable for a small hydropower station. The circuit reclosing scheme selection method comprises the following steps: S1, after a fault occurs, performing circuit reclosing; calling a plurality of groups of active power data of all hydroelectric generating sets and active power data of all loads of the line from the sampling moment closest to the fault moment, and respectively forming a hydroelectric generating set power matrix and a power matrix of all loads of the line; s2, predicting the power at the fault moment, wherein the step a comprises the following sub-steps: a, selecting a set frequency function and fitting parameters to fit a power curve; b, calculating a power value at a fault moment; s3, selecting a reclosing scheme, wherein the reclosing scheme comprises the following sub-steps: c, calculating a power-to-use ratio; and d, selecting a reclosing scheme according to different power-to-use ratios. According to the method, different reclosing strategies are selected by considering the ratio relation between the hydroelectric generating set and the load, and synchronous grid-connected reclosing and small water electrolysis reclosing in the absence of line voltage judgment are realized by optimizing the reclosing action time.

1. Name of the product in this design: Modular Energy Storage Cabinet (Power Matrix). 2. Purpose of this design: for the storage and release of electrical energy. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

The application belongs to the technical field of target detection, and specifically discloses a two-dimensional adaptive constant false alarm rate detection method of a grid complementary reference sliding window, which comprises the following steps: constructing a grid complementary reference sliding window under a detection matrix and distributing reference units; initializing key parameters of the detection matrix, and converting an original image signal matrix into a signal power matrix; judging and assigning the coordinate features of the reference units based on a window type topological structure, and calculating the mean value after traversal to extract background clutter; calculating a second order statistic VI and a mean ratio MR, and calculating a detection threshold by means of three threshold factor calculation formulas and in combination with a judgment rule to select a constant false alarm rate algorithm. The two-dimensional adaptive constant false alarm rate detection method of the grid complementary reference sliding window has the advantages that the detection accuracy is improved by 49.4% under a multi-target and clutter interference environment, the threshold stability and boundary processing capacity are better under different backgrounds, the false alarm and missed alarm rates are effectively reduced, and the target detection performance is improved.

This invention discloses a resource scheduling method, apparatus, device, storage medium, and product. The method includes: acquiring resource information of CPU and GPU in a computing power scheduling system, and constructing corresponding computing power containers for CPU and GPU respectively; dividing CPU computing power units into different regions of the CPU computing power container based on their computing power characteristics to obtain target CPU computing power containers; similarly processing GPU computing power units to obtain target GPU computing power containers; further, converting the target containers into corresponding computing power matrices, determining idle and busy computing power sides based on the computing power matrices, and identifying the transferable computing power units of the idle computing power sides; and using a preset instruction conversion mechanism to convert the transferable computing power units into the computing power type of the busy side, thereby achieving resource scheduling. This invention can efficiently schedule CPU and GPU resources, reduce the amount of data synchronization between different computing power nodes, and improve the overall performance of the computing power system.

The invention relates to a static voltage stability evaluation method, device and equipment for new energy through a flexible direct current delivery system. The method comprises the steps of obtaining a full-order power grid susceptance matrix, a plurality of pieces of measurement data and a network topology and operation mode of the new energy through the flexible direct current delivery system; calculating to obtain a complex power matrix according to all measurement data; performing deletion and elementary row / column transformation processing on the full-order power grid susceptance matrix according to the network topology and the operation mode to obtain an updated power grid susceptance matrix; calculating static voltage stability margin index data according to the complex power matrix and the updated power grid admittance matrix; calculating the static voltage stability margin according to the static voltage stability margin index data; and according to the static voltage stability margin, judging whether the static voltage of the new energy in the operation period of the flexible direct current delivery system is stable or not. According to the method, the static voltage stability evaluation of the new energy in the operation period of the flexible direct current delivery system is realized through the static voltage stability margin, and the evaluation accuracy is improved.

This invention relates to the field of shortwave antenna communication channel testing and modeling technology, specifically to a method for measuring the angular power spectrum of an antenna in a shortwave skywave scenario. The method includes: the receiver performing a two-dimensional equally spaced angular scan within a preset azimuth and elevation range; establishing an angular power spectrum measurement equation based on the received signal power, antenna pattern, and noise power channel, using the scattering function; convolving this equation with the pattern to obtain the angular power spectrum within a single path; discretizing the single-path received power matrix and antenna pattern matrix in two dimensions, and then performing zero-plugging expansion on each; converting the discretized single-path received power matrix and antenna pattern matrix into two-dimensional frequency domain matrices, and determining the frequency domain ratio between the received power matrix and the antenna pattern matrix mapped to the angular domain using time-delay Doppler domain parameters. This invention improves the accuracy of angular power spectrum measurement in shortwave skywave channels while reducing the dependence of traditional empirical modeling methods on a single propagation assumption.

The invention discloses an active power distribution network operation risk assessment method and system considering element uncertainty, and the method comprises the steps: inputting basic data, and inputting the basic data into a pre-constructed power distribution network wind-solar output and load demand uncertainty model; constructing a multi-level active power distribution network risk assessment index system; the method comprises the following steps: taking wind power, photovoltaic and load output data as input, generating an operation condition scene by adopting LHS sampling of global sensitivity analysis, carrying out scene reduction by utilizing a K-medoids clustering algorithm to obtain an appropriate scene number and a probability of each scene, calculating a power flow in an s-th operation scene, and obtaining an output node voltage matrix and a line active and reactive power matrix; and after all scenes are traversed, the operation risk is calculated according to a pre-constructed risk index system. The method has the advantages that accurate evaluation and weak link positioning of the operation risk of the power distribution network are achieved, and the problem that a traditional risk evaluation method is insufficient in precision in the complex active power distribution network is effectively solved.

The invention belongs to the field of electromagnetic spectrum monitoring and anti-interference evaluation, particularly relates to an electromagnetic environment complexity evaluation method and device for a communication system under interference threat and a storage medium, and is suitable for scenes of ground / no-load / ship-borne spectrum sensing, interference detection and alarm, spectrum control, anti-interference communication system design and test and the like. The complexity calculated by the method is highly consistent with engineering hazard semantics, and interference with high power, large occupation and strong structure and random fluctuation of weak energy can be distinguished. The energy filling degree, the occupancy degree and the structural item are extracted in parallel through three elements, gating is conducted firstly, then energy is fused in advance, and monotonicity and interpretability are guaranteed. Cross-scene comparable, white / colored noise and parameter perturbation are robust, and irrelevant frequency bands can be further suppressed by selecting in-band calculation. The method is easy to deploy, adjustable and trainable, and keeps stable monotonic correlation with BER / delta BER. The input only needs a time-frequency power matrix, the algorithm is light, and real-time integration of CPU / GPU / FPGA is facilitated.

The application discloses a high-power charging cabinet. Parallel assembly is fixed at the middle position in the width direction of the cabinet body inside the cabinet body, and the parallel assembly comprises at least one pair of parallel copper bar assemblies extending in the width direction of the cabinet body, at least one pair of parallel device assemblies corresponding to the at least one pair of parallel copper bar assemblies and a parallel sheet metal assembly. Therefore, the first power matrix module and the second power matrix module can be respectively fixed to each of the at least one pair of parallel copper bar assemblies from the two sides of the parallel assembly, and the first power matrix module and the second power matrix module are further connected to the parallel sheet metal assembly. Thus, the convenient installation and disassembly of the first power matrix module and the second power matrix module into the charging cabinet are realized through the parallel assembly. In addition, different specifications of power matrix modules can be selected as the first power matrix module and the second power matrix module according to actual needs, so that the free combination and collocation of the power matrix modules are realized.

The embodiment of the invention discloses a power grid operation control system. A specific embodiment of the system comprises a power dispatching server configured to execute the following steps: generating a standardized power matrix and a future weather data matrix; generating a short-term power data sequence, a medium-term power data sequence and a long-term power data sequence; generating a short-term load data sequence, a medium-term load data sequence and a long-term load data sequence; generating a long-term power generation data sequence; generating a medium-term power generation data sequence; generating a short-term power generation data sequence; the energy storage controller is configured to control the energy storage equipment to store energy; and the power generation controller is configured to control the corresponding power generation equipment to generate power. According to the embodiment, system resource waste can be reduced.

The invention discloses an edge intelligent application cooperative processing system and method based on a video enhancement technology. The cooperative processing system comprises a video enhancement module, a task fragmentation module and a dynamic scheduling module. The video enhancement module is used for enhancing the initial video; the task fragmentation module is used for calculating the content complexity of the enhanced video, dividing calculation tasks and constructing a calculation task calculation power matrix; and the dynamic scheduling module is used for generating a task allocation strategy and carrying out computing power resource allocation on each enhanced video according to the task allocation strategy. According to the cooperative processing system and method, computing power resources can be reasonably distributed according to the complexity of the video content, so that the video processing efficiency is effectively improved.

The invention discloses a distributed source-load collaborative strategy optimization method oriented to supply and demand mutual assistance of production and consumer of a micro-grid. The method comprises the following steps: constructing a production and consumer source-load physical state and energy storage time sequence constraint model; constructing a mutual aid power physical boundary; defining a virtual potential energy state quantity; constructing a delivery and disappearing person supply and demand mutual aid collaborative decision-making model; performing linearization processing on the alternating current power flow equation; solving a node voltage amplitude and a line power flow disturbance vector; converting the node voltage amplitude disturbance vector into a mutual aid power matrix; establishing a network physical constraint feasible region; establishing a global mutual aid matching model; constructing an asynchronous driving and joint optimization loop; virtual congestion potential energy is calculated; performing robust sensing extreme scene verification and cross-scene residual quantization on the mutual aid power matrix, and tightening the upper bound of a network physical constraint feasible region; and when the indexes converge, outputting a mutual aid power matrix and a scheduling instruction. According to the method, the problems that existing network constraint embedding lags behind, asynchronous negotiation convergence is insufficient, and cross-scene feasibility of extreme scenes is lacked can be solved.

The invention discloses a power control method and device based on multi-source cooperation and a reconfigurable power matrix, and the method comprises the steps: obtaining a current power supply parameter set corresponding to a multi-source energy supply module in response to a charging power scheduling instruction; wherein the current power supply parameter set at least comprises working parameters of a three-phase alternating current power grid, a photovoltaic module and an energy storage module; according to a preset power supply mode decision strategy and the current power supply parameter set, determining a current on-off state of a switch group in the multi-source energy supply module and a current charging power distribution strategy in the multi-source energy supply module; and executing the current charging power distribution strategy to enable the power control module to charge to-be-charged equipment connected with the charging terminal group. According to the embodiment of the invention, the energy supply mode and the charging power distribution mode in the charging station can be flexibly adjusted according to the conditions corresponding to the working parameters of the three-phase AC power grid, the photovoltaic module and the energy storage module in the multi-source energy supply module of the charging station.

This invention provides a multi-dimensional resource optimization method for networked unmanned aerial vehicle (UAV) communication based on IRS quantity awareness, specifically including the following steps: initializing base station information, CUAV information, and IRS information; establishing a system channel model, energy consumption model, and IRS quantity-aware CUAV downlink communication model based on the base station information, CUAV information, and IRS information; establishing a joint optimization problem model for maximizing system EE and minimizing the number of associated IRSs based on the system channel model, energy consumption model, and IRS quantity-aware CUAV downlink communication model; jointly optimizing the IRS association scheduling matrix, base station transmit power matrix, and IRS phase shift matrix to achieve the optimization objective corresponding to solving the joint optimization problem model for maximizing system EE and minimizing the number of associated IRSs; this invention can maximize system EE and minimize the number of associated IRSs while satisfying constraints such as communication connectivity, mobility, and unit modulus.

This invention discloses an active support wind power cluster and its control method. The wind power cluster includes a set A of N wind turbines with reserved capacity for active support and a set B of M wind turbines without active support capabilities. All wind turbines are connected to the same grid connection point via tie lines. For this wind power cluster, active support power control is performed based on the operating status of the wind turbines and the regulation capabilities of the wind turbines in sets A and B. Specifically, the grid connection point frequency is collected to obtain the support capacity required by the wind power cluster. The uncontrollable regulation power is calculated by combining the characteristic matrix of set B and the characteristic matrix of set A. The active support regulation correction power is then obtained by combining the characteristic matrix of set A. Based on the active support regulation correction power, the active support scheduling power matrix of set A and the scheduling power matrix of set B are adjusted to more accurately respond to the active support capacity required by the entire cluster.

The invention discloses a quantitative analysis method based on a VSG control system dynamic interaction model. The method comprises the following steps: establishing a multi-VSG grid-connected system dynamic interaction analysis model, and obtaining apparent power matrix expressions of all grid-connected VSGs; on the basis of a relative gain analysis theory, according to the apparent power matrix expression of each VSG, constructing a corresponding relative gain array matrix, obtaining a power coupling degree coefficient in a single machine, and performing power coupling analysis; and according to the apparent power matrix of each VSG, focusing on an active power or reactive power analysis model, obtaining an interaction influence coefficient between the VSG and other VSGs in the system, and carrying out interaction influence analysis. According to the method, a relative gain array matrix and a multi-VSG grid-connected model are utilized to reveal the influence of key control parameters and power grid impedance in the system on the power coupling characteristic of the converter and the interaction mechanism among a plurality of converter units.

An information handling system may include a memory and a processor communicatively coupled to the memory, and configured to collect telemetry relating to execution of an artificial intelligence model on at least one configuration of a compute node and a quantization level, based on the telemetry collected, compute a power matrix setting forth average power consumption for execution of the artificial intelligence model on a plurality of configurations of compute nodes and quantization levels, and prioritize the plurality of configurations for execution of the artificial intelligence model based on the average power consumption for each configuration.

The application discloses a power grid single fault positioning method and device, terminal equipment and storage medium, the method comprises: obtaining the node three-phase current matrix, node three-phase voltage matrix, branch power matrix, branch adjacency matrix and node adjacency matrix of the power grid to be detected; wherein, the power grid to be detected only has one fault; the node three-phase current matrix, node three-phase voltage matrix, branch power matrix, branch adjacency matrix and node adjacency matrix of the power grid to be detected are input into a single fault positioning model, so that the single fault positioning model outputs a fault component of the power grid to be detected; wherein, the component comprises a node and a branch. Through implementation of the application, the topological structure relationship between the nodes and branches of the power grid can be fully considered, and the accuracy of the output result of the single fault positioning model is improved.