133 results about "Grid optimization" patented technology

A profile map of parameter values in a region is determined based on average values along linear paths through the region. In one example, a temperature map of a region of a gas turbine engine is created based on time-of-flight measurements from acoustic transceiver pairs arranged circumferentially around the region. A speed of sound for each transceiver pair is determined based on the time-of-flight measurements. An average temperature along each path is estimated from the time of flight, and the profile map is computed from the average temperatures. The profile map may be computed using a polynomial approximation technique, a grid optimization technique or a basis function technique.

The use of battery cells to store energy for EV charging and grid optimization and regulation service. The major components of the system and the benefits of such concept are also described.

The invention discloses a comprehensive energy micro-grid optimization planning method. The method comprises the following steps of: firstly establishing a structure of a comprehensive energy micro-grid; modeling devices such as a CCHP system, a gas boiler, an electric refrigerating unit and an energy storage device in the structure; obtaining a typical daily load curve and a renewable energy output curve from history data; and establishing an energy storage capacity optimization configuration model which takes a minimum total cost of an energy storage construction, operation and maintenance cost and a system operation cost as a target function by combining balance constraint of load, characteristic constraint of equipment and output constraint of new energy. Through solving the model, optimal energy storage capacities can be obtained so as to provide reference and support for the energy storage construction of practical comprehensive energy micro-grids.

The invention provides an equivalent coordinative optimization method for a large-scale power grid dispatching plan. The optimization method comprises the steps as follows: (1) a large power grid is divided into a plurality of regional power grids, and the regional power grids are taken as equivalent nodes; (2) the regional power grids submit information of the equivalent nodes to the whole grid; (3) the whole grid determines a generation dispatching plan under the equivalent regional power grids, and issues a connecting line plan between the regions, planned total output of the regional power grids and a plan of a direct dispatching set; (4) the regional power grids calculate and determine output plans of regional sets according to the planned total output of the regional power grids, and calculate locational marginal cost; and (5) whether full-grid optimization is converged or not is judged through the marginal cost of two ends of a connection line, if so, calculation is ended, if not, the set which affects the grid security constraint corrects output bounds according to the optimization result and turns to the step (2). The iteration times can be controlled; the convergence is rapid; and rapid determination of the large power grid dispatching plan can be achieved.

The invention discloses a leaf disease identification method based on a machine learning algorithm, belonging to the technical field of image processing. The invention firstly performs preprocessing operations such as grayscale transformation, image enhancement and denoising on the collected leaf sample image; Then the preprocessed image is segmented by adaptive threshold algorithm to represent the texture information of the sample image effectively. The RGB color space is selected to extract the color features of the sample image, and the texture features of the segmented image are extractedaccording to the gray level co-occurrence matrix. Finally, support vector machine model is selected to classify and recognize the sample images by cross-validation algorithm. Firstly, the main parameters of SVM model are optimized by grid optimization method, and then the parameters with the best recognition accuracy are selected to establish SVM classification and recognition model. The inventioncan enable the computer to automatically identify the diseases and pests of the leaves through training, greatly reducing the space and time overhead, and improving the identification accuracy, and has the characteristics of fast, accurate and strong robustness.

The invention discloses a power two-stage interactive optimization scheduling system of a virtual power plant in a haze environment, and specifically relates to a distributed energy resource optimization scheduling method. The method comprises the following steps: A, establishing a photovoltaic power generation prediction and load prediction system considering the influence of the haze environment; B, establishing a power system two-stage interactive scheduling system considering a virtual power plant; C, establishing a mathematical model considering two-stage interactive scheduling of the virtual power plant in the haze environment; D, improving the artificial bee colony algorithm; and E, carrying out solving based on an optimization model of the improved artificial bee colony algorithm. With the system, the energy crisis can be effectively relieved, and the environment can be protected. As new energy and the smart grid technology develop, it is difficult for a power system to directly schedule a lot of grid-connected DERs. The embodiment demonstrates the validity of the model and the feasibility of the algorithm, embodies the superiority of the aggregation of various DERs in power system scheduling, proves the influence of the haze environment on photovoltaic output, load prediction and scheduling, and provides a feasible reference for grid optimization scheduling.

The invention discloses a three-dimensional grid strain measurement method, which comprises the following steps of: step 1, grid preparation; step 2, sampling and shooting; step 3, picture orientation; step 4, grid node matching; step 5, grid node rebuilding; step 6, grid connection, step 7, grid optimization; and step 8, strain calculation. Through the operation steps, the method can be used for measuring the three-dimensional full field strain information in the metal plate material forming process, and the metal plate material forming performance and the advantages and disadvantages of the mold process design scheme can be evaluated, so the metal plate material forming quality is improved, the manufacture precision is improved, and the production cost is reduced. The three-dimensional grid strain measurement method has the characteristics that the measurement operation is convenient, the automation degree is high, the result is accurate and reliable, the measurement information is rich, the efficiency is high, and in addition, the non-contact measurement is realized.

The invention belongs to the technical field of digital images, and particularly relates to a grid-optimization-based registration method suitable for free view angle image splicing. In recent years,due to the application prospect in the fields of virtual reality, medical imaging and the like, the panoramic image is greatly concerned. The image registration is mainly used for obtaining position parameters of each image in a panorama. Traditional image registration needs to execute a series of operations such as feature point extraction, matching, homography matrix solving and camera parametercorrection. According to the grid-optimization-based registration method, a grid optimization-based registration method is used for replacing a classic registration technology, so that the speed is obviously improved, and the grid-optimization-based registration method is suitable for splicing images with large parallax shot at a free visual angle. According to the grid-optimization-based registration method, ORB rapid feature extraction is used for obtaining feature points of an image, and a strategy of step-by-step coarse and fine matching is introduced, and finally, three constraint termsbased on grid optimization are introduced, and an error function minimization method is used for obtaining optimal registration parameters between the images.

This paper discloses a method for optimal configuration of power sources in a wind-solar combined power generation micro-grid system, which belongs to the field of grid optimization planning. It includes the following steps: considering the correlation between new energy power generation output and different types of load power in the microgrid, and establishing the joint output of new energy power generation and the probability distribution model of the total load power based on the Copula theory; using the historical simulation method to obtain the microgrid operation The risk value in the planning realizes the risk assessment of the micro-grid; with the goal of considering the investment cost, low-carbon cost, and grid-connected operation power trading and other comprehensive economic costs, the optimal configuration model of the micro-grid power supply is constructed; the improved invasive weed optimization is adopted The algorithm solves the configuration scheme. Considering the correlation greatly improves the economy of the optimization scheme. At the same time, the risk value of the system is well combined with the economic loss, and the economy and reliability of the system are improved.

Data comprising a request specifying a desired change in electrical load for a defined period of time is received. The electrical load is associated with a plurality of resources under control of resource agents and on a utility grid. Available capacity of resources within the control of each resource agent over the defined period of time is determined. Each available capacity is determined at least using a resource load model. Using the determined available capacity of resources over the defined period of time, resource scheduling instructions are calculated for a subset of resources. The resource scheduling instructions satisfy the desired change in electrical load of the request. Data characterizing the resource scheduling instructions is provided. Related systems, apparatus, methods, and articles are also described.

The invention relates to a recognition method of motor imagery EEG (electroencephalograph) signals based on energy characteristics. The recognition method of the motor imagery EEG signals based on theenergy characteristics includes the steps of collecting EEG signals from subjects as sample sets during the time when the subjects are completely relaxed and when the subjects are conducting motion imagination, denoising the EEG signals of these sample sets and acquiring the average power of the EEG signals, acquiring the energy values of the Mu (8-12 Hz) band and the Beta (18-25 Hz) band of theEEG signals as the eigenvalues during the motion imaging state and the fully relaxed state based on Fourier transform and using the energy spectral density function, and conducting online optimizationof parameters of classification methods to realize the recognition of the motor imagery EEG signals with the characteristics as input and using a support vector machine classification method based ona radial basis kernel function as well as using an improved grid optimization algorithm. The recognition method of the motor imagery EEG signals based on the energy characteristics has the advantagesof consuming short time, guaranteeing high accuracy and providing a new idea for real-time BCI (bulk current injection) implementation.

The invention relates to an ecological environment Internet of Things monitoring method and system based on landscape ecology. The method comprises the steps of collecting ecological environment monitoring element data, determining natural elements and ecological environment monitoring elements in the aspect of physical perception on the basis of the content of a scene sensation ecology theory, arranging monitoring point locations by adopting an irregular grid optimization method, and finally arranging corresponding sensors on the monitoring point locations; conducting data transmission, specifically, transmitting the ecological environment monitoring element data acquired by the sensors to a data storage server of a field base monitoring station through a data transmission network; conducting data processing, specifically, completely performing classified storage and classified processing on information of various types of data according to a unified layout; carrying out data controlby designing omnibearing sensor interface arrangement, an intelligent management interface system, an intelligent monitoring control terminal system and a field base monitoring station; and carrying out real-time monitoring, forecasting and early warning and comprehensive analysis on the ecological environment on a remote monitoring platform.

The invention discloses an impact monitoring and energy assessment technology for a composite material structure and belongs to the technical field of intelligent detection and assessment of the composite material structure. According to the technology, a new two-step impact positioning method including an energy distribution smooth filtering method and a TOF (time of flight) based four-side central positioning method is applied in the aspect of impact positioning; in the aspect of impact energy assessment, a multipath integrated energy distribution assessment method for imaging processing based on pixel grid optimization is proposed and assessment for the absorbed energy distribution condition of the structure is realized. With the adoption of the technology, whole-layout impact positioning and energy assessment are realized; by means of the new two-step impact positioning method, precision, timeliness and reliability of impact positioning are improved; influence of structural complexity and composite anisotropy on the impact positioning and impact energy assessment performance is inhibited, effective impact positioning and energy assessment in a severe external environment are also improved, and wide application of the technology in technical fields of intelligent detection and assessment of the composite material structure is promoted strongly.

The invention provides a method for realizing digital twin modeling of an automatic circuit breaker detection assembly line. The method comprises the following steps: obtaining a three-dimensional digital model of each mechanical device in the circuit breaker detection assembly line; carrying out hierarchical relationship modeling according to an actual production process and an action state; performing grid optimization on the model; according to an actual production process, performing action design on each mechanical device to obtain a mechanical action track of the model; editing the mechanical action track of the model in combination with the actual action logic and the matching relationship between the actions; and introducing motion control, carrying out motion simulation in a digital twin scene, and realizing virtual synchronous motion with a real circuit breaker detection assembly line. According to the method, through information fusion and interaction between real physical equipment of the detection assembly line and the digital twinning model, centralized management of assembly line production data is realized, and remote visual operation, management and maintenance canbe carried out on the detection assembly line, and a basic platform is provided for digital manufacturing of miniature circuit breakers.

The invention provides a grid deformation optimization method for cutting simulation of a deformable object in the virtual surgery. Multiple tasks are subjected to parallel processing by adopting geometric optimization and topology optimization combined with a multi-threaded approach, so that the problem that morbid cells occur in the cutting simulate process is solved. The grid deformation optimization method comprises the four steps: step 1, target cell searching: searching grid cells required to be processed according to the grid quality; step 2, grid optimization preprocessing; step 3, grid topology optimization process; step 4, grid geometry optimization process. The step 2, the step 3 and the step 4 use multi-threaded parallel processing. The grid deformation optimization method provided by the invention has the benefit that while the grid quality is improved, the number of grids can be reduced, so that the efficiency and the stability of grid model deformation calculation can beeffectively improved.

The invention discloses a public building participated grid optimization operation method. The grid optimization operation method comprises the steps of S1, building a public building adjustable resource optimization operation control information base, wherein the information base contains all adjustable resources such as photovoltaic cells, wind power generation, EV and adjustable loads in public buildings; S2, establishing an adjustable resource optimization operation mode, and sending the adjustable resource optimization operation mode to the adjustable resources in the buildings, wherein the ith adjustable resource receives the notification and judges whether the optimization operation mode is allowed to be accepted or not; and S3, if not, updating the information base according to constraint conditions, if so, judging whether a multi-objective optimization objective is met or not, if so, performing an optimization operation according to the mode, and if not, continuing to update the information base according to the constraint conditions. Fluctuations of an output building overall load curve are enabled to be greatly reduced, an optimized load area is stable, and the difference between peak and valley is also obviously reduced.

The invention provides an unmanned aerial vehicle image splicing method based on grid optimization and global similarity constraint. The unmanned aerial vehicle image splicing method specifically comprises the steps of extracting feature points of a reference image I and a target image I'and the corresponding relation of the feature points through an SIFT feature point extraction algorithm; meshing the reference image and the target image; solving a local homography matrix of the reference image and the target image after meshing by adopting a local DLT method; performing grid optimization byusing a minimized energy function to align the gridded target image with the reference image so as to eliminate ghosting of an overlapping region and obtain a preliminary spliced image; taking the ground as a landmark, and performing global similar coplanar constraint on the preliminary spliced image to eliminate projection distortion of a non-overlapping part to obtain a final spliced image. Thebeneficial effects of the invention are that the method can achieve the better matching of the features of the images of the unmanned plane through combining the features of the images photographed bythe unmanned plane, achieves the precise registration, and achieves an ideal splicing effect.

The invention discloses a grid position optimization method for through silicon vias (TSVs) in a three-dimensional (3D) integrated circuit, and belongs to the field of 3D integrated circuit designs. When the 3D integrated circuit is produced and manufactured, a manufacturer cannot process a layout in which intervals among the TSVs are smaller than interval constraint of a processing technology. According to the invention, the grid method is used to optimize the intervals among the TSVs, so that an optimized layout is obtained and the intervals among the TSVs satisfy the technological processing requirement and the manufacturing can be completed. The method disclosed by the invention is implemented according to the steps as follows: firstly, a rectangular coordinate system is established in a layout initially set for the TSVs; afterwards, coordinates of the TSVs are determined, then a grid is produced and the distance between every two grid points in the grid is guaranteed to be larger than the minimum distance capable of being technologically processed; next, each TSV is moved to a closest grid point; and finally, the phenomena that multiple TSVs exist on a single point are arranged to guarantee that only one TSV exists on each grid point of the final layout, then the optimization is completed and the integrated circuit is produced and manufactured.

The invention discloses a fan blade image segmentation and grid optimization splicing method. The fan blade image segmentation and grid optimization splicing method comprises the following steps: S1,continuously collecting images of a single-sided fan blade to form a group of to-be-spliced original images; S2, using the U-net algorithm to carry out image foreground segmentation on each original image, and extracting a fan blade main body part to form a group of images to be registered; S3, gridding each image to be registered, establishing an index from 1 to m for a grid vertex of each to-be-registered image, then expressing x and y coordinates of the grid vertexes as a vector V of a 2m dimension, defining a global energy function about V, and minimizing the energy function to obtain a grid vertex optimal solution, and S4, completing image splicing according to the grid vertex optimal solution. The method has the advantages that the problem that target splicing fails due to the fact that the depth of field of the target and the background is too large is solved, natural splicing of multiple fan blades is achieved, and spliced images are small in visual effect distortion, continuous and real.

The invention discloses an enterprise family-oriented small and micro enterprise credit evaluation model construction method and system, belongs to the field of enterprise credit evaluation, and aimsto solve the technical problem of how to realize enterprise family-oriented small and micro enterprise credit evaluation. The enterprise family-oriented small and micro enterprise credit evaluation model construction method comprises the steps: obtaining sample data; dividing the sample data into a training set and an evaluation set; constructing an evaluation model through a random forest method,wherein the evaluation model is composed of an enterprise owner credit evaluation sub-model and an enterprise behavior credit evaluation sub-model, and the weighted sum of credit scores of the enterprise owner credit evaluation sub-model and the enterprise behavior credit evaluation sub-model serves as evaluation output of the evaluation model; taking the training set as input, and training the evaluation model through a ten-fold cross validation algorithm and a parameter grid optimization algorithm; and taking the evaluation set as input, and performing parameter fine adjustment on the initial evaluation model through a grid search method. The enterprise family-oriented small and micro enterprise credit evaluation model construction system comprises a data acquisition module, a sample division module, a model construction module, a model training module and a model optimization module.

The invention relates to a microgrid optimization scheduling method considering combined cooling heating and power supply. The method is used for optimizing the operation of the combined cooling heating and power supply micro-grid. The micro-grid comprises a fan, a photovoltaic generator and a micro gas turbine; according to the method, an improved butterfly algorithm is adopted to solve a pre-established microgrid optimization model, and the optimal solution is obtained; the micro-grid is provided with a storage battery for supplying power to the micro-grid when the fan and photovoltaic power generation are insufficient, and the improved butterfly algorithm optimizes an elitist butterfly population through a reverse learning strategy and optimizes a random number through a chaos function. Compared with the prior art, the comprehensive energy utilization rate of the micro-grid system is improved by utilizing multi-energy complementation, the energy storage capacity of each device in the system is reduced, and the operation cost of the micro-grid is reduced; through the improved butterfly algorithm, the convergence rate and reliability of solving the micro-grid optimization model are improved.

The invention discloses a power grid whole-grid reactive power optimization method based on an improved differential evolution algorithm. The method is characterized by including: performing active power grid loss analysis based on load flow calculation; performing whole-grid optimization according to the grid loss analysis result and based on the improved differential evolution algorithm. The method has the advantages that the receiving and outputting capacity of a power grid to new energy is increased greatly while safe and economical operation of the power grid is guaranteed, wind curtailment is reduced, and on-grid energy of the new energy is increased.

The invention discloses a shape-optimized rectangular panoramic image construction method based on feature selection, and the method comprises the steps of carrying out the splicing of two overlappedimages which are shot in a non-fixed mode based on a common camera, and obtaining a rectangular panoramic image which is not distorted in shape and is not lost in information; taking the shot image asan input image, performing feature point matching on the input image, and screening mismatched feature points and isolated feature points by using a clustering algorithm; performing image registration operation on the input image overlapping area by utilizing the screened feature points; gradually changing distortion transformation is carried out in the non-overlapping area so as to reduce perspective distortion generated by the image; and establishing a grid optimization model based on boundary constraint and central region reservation, obtaining an optimal rectangular grid vertex, and finally obtaining a final rectangular panoramic image through an interpolation method. According to the invention, the rectangular panoramic image is generated under the condition that the information lossis reduced as much as possible through non-fixed shooting of the image with the overlapped area.

The invention discloses a direction of arrival estimation method based on a rank-one denoising model. The method comprises the following specific steps: establishing a receiving signal model of radar, and determining a measurement matrix of receiving signals; according to the measurement matrix of receiving signals, constructing a signal covariance matrix based on the rank-one denoising model; carrying out sparse reconstruction on the signal covariance matrix based on the rank-one denoising model; and according to sparse reconstruction signal vectors, using an alternated grid optimization algorithm to estimate direction of arrival of a target signal source. According to the method, under unknown non-uniform noise conditions, based on the rank-one denoising model, non-uniform noise is eliminated by redesigning the covariance matrix of dimensionality reduction signals, then equivalent source vectors are obtained by using vectorization operation, and finally high-resolution direction of arrival estimation with a limited number of snapshots and high robustness of non-uniform noise prevention are realized by using and determining the direction of arrival of signals.

The invention provides a hydrogen-containing energy storage microgrid optimization operation method based on deep reinforcement learning, and the method comprises the steps: building an electrolytic cell efficiency characteristic model through a linear interpolation method, combining the electrolytic cell efficiency characteristic model with a gas turbine model, an electrochemical energy storage model, a hydrogen storage tank model, a fuel cell model and the like, and taking the microgrid operation cost as a target, constructing an optimized operation model of the hydrogen-containing energy storage micro-grid. And finally, solving a sequence decision problem of micro-grid optimization operation by adopting a depth deterministic strategy gradient algorithm. According to the method, the efficiency characteristic of the electrolytic cell is considered, the hydrogen energy storage capacity can be fully utilized, the optimization problem is solved according to the deep reinforcement learning principle, the operation cost of the hydrogen-containing energy storage microgrid is reduced, and good generalization is achieved.

The invention provides a honey detection method using grid optimization-based selection of parameters of a support vector machine classifier. The invention is characterized in that the method of exhaustion is employed in grid optimization, all the points in a range are searched one by one according to certain step length in a pre-estimated value range to determine final optimal parameters, and exhaustive search is carried out on r and c in a range of 2<-4> to 2<10>, with 2 as a base number. According to the invention, when c is equal to 5.2780 and r is equal to 0.1088, highest discrimination accuracy, 96.25%, of samples in a training set is realized, and under such a condition, a model is established and a prediction set is used for inspection; final discrimination accuracy is 96.20%, and discrimination accuracy of the samples is 76 / 79, wherein honey of rape flowers is 23 / 23, basswood honey is 16 / 17, and acacia honey is 37 / 39.

The invention provides a gridding arrangement method of air pollutant monitoring stations. The method comprises the following three steps: step 1, coarse grid layout, specifically, a hot spot region is encrypted on the basis of uniformly distributed grids according to investigation conditions of local population and industry distribution, pollution occurrence frequency and pollution influence range; step 2, the grid adaptation degree of the hot spot area is improved, the actual effective monitoring range of a monitoring station is reversely solved based on an adjoint probability method according to local meteorological conditions, and data reference is provided for the size of a fine grid; and step 3, grid optimization is conducted, an optimization analysis technology is utilized to solvethe gridding distribution density and the grid length-width ratio according to the obtained effective monitoring range of the monitoring station, and full coverage of the monitoring area is realized.According to the method, the arrangement scheme of the monitoring grids can be efficiently and accurately provided according to the actual situation, the method has guiding significance for position selection of monitoring stations and evaluation of the monitoring effect of existing stations, and treatment and improvement of urban air are facilitated.

The invention provides a three-dimensional overhead cable hierarchical power grid optimization method and device and computer equipment. According to the three-dimensional overhead cable hierarchicalpower grid optimization method, multiple algorithms and technologies are fused to optimize a three-dimensional overhead cable hierarchical power grid; simulation construction of a three-dimensional overhead cable hierarchical power grid model is ensured; the multi-source geographic information data is managed through a tile partitioning technology; data access is facilitated, spatial indexing algorithm is used, and then an efficient index mechanism can be established; geographic space objects irrelevant to space operation in the three-dimensional scene are filtered; the space operation speed and efficiency are improved; a Bezier curve interpolation algorithm is used; and the rendering effect of the three-dimensional overhead cable hierarchical power grid can be improved, through the LOD algorithm technology, the original patch geometric model can be optimized according to different schedules according to different long-range close-range scenes, the number of topological edges and structural surfaces in the patch structure is reduced, and access and rendering efficiency of the model is improved.