254 results about "Potential evaluation" patented technology

The invention belongs to the technical field of oil and gas reservoir energy development, and discloses a three-dimensional injection and production well pattern construction method based on a multi-objective algorithm. The problem that the delimited potential area is difficult to effectively use due to the fact that existing potential evaluation is only based on a single index is effectively solved. Comprising the steps that a fault inner core, a fault outer core, a fracture development dense zone and a secondary fracture zone are proposed; carrying out inter-well connectivity analysis on the oil reservoir units by utilizing an oil reservoir engineering method and a numerical simulation streamline method; based on the embedded discrete fracture model, analyzing a remaining oil distribution mode under the control of the nuclear band structure; a multi-parameter comprehensive evaluation system is constructed by combining the remaining oil utilization potential, the displacement power, the flow capacity, the connectivity relation and the reserve abundance; a three-dimensional injection-production well pattern construction technology is formed for an oil reservoir with or without bottom water; based on a multi-objective optimization algorithm, three-dimensional collaborative optimization of the recovery ratio, the well control reserves and the net present value is taken as a core, and a high-efficiency well location deployment technology for different fault zones is constructed.

The invention relates to the technical field of forest wetland carbon sink monitoring and evaluation, and particularly discloses a forest wetland carbon sink intelligent monitoring and evaluation system and method. According to the method, a vegetation carbon sequestration potential evaluation result is obtained by analyzing vegetation structure feature data of forest, water and soil composite ecology of the forest wetland, a water-soil-carbon cooperative evaluation result is obtained by analyzing specific hydrological-soil carbon cycle key elements of the forest wetland, and environmental disturbance response factors are obtained by combining various environmental disturbance factors. Through multi-source data fusion and intelligent modeling, a carbon sink quantitative evaluation value is output, and abnormal feedback is triggered; the problems that in the prior art, adaptability to a forest wetland compound ecological system is insufficient, evaluation refinement is insufficient, and dynamic response is lacked are solved. According to the method, accurate and dynamic monitoring and evaluation of forest wetland carbon sink are realized, carbon sink short plates can be accurately positioned, optimization support is provided, and technical support is provided for protection, restoration and optimization management of forest wetland carbon sink resources.

The invention discloses a method for constructing a large mineralization potential evaluation model based on LLM, and relates to the field of models.The method for constructing the large mineralization potential evaluation model based on LLM comprises the following steps that 1, a mineral geological map file is converted into a structured JSON format data set; step 2, constructing cue words, wherein the cue words at least comprise geological information extraction cue words, function task cue words and entity, relation and attribute extraction cue words; compared with the prior art, the method has the beneficial effects that the large mineralization potential evaluation model constructed by the method realizes text and map multi-mode mineral product geological map information identification and analysis, automatic mineralization geological feature analysis, mineralization feature information extraction and mineralization potential evaluation; the problems that in the prior art, man-made subjective influence exists, professional knowledge dependence is high, the geological information recognition accuracy rate in the recognition process is low, and information is lost during knowledge retrieval are solved.

The invention discloses a new energy power grid hybrid energy storage system multi-dimensional regulation and control capability quantitative evaluation method and system, and mainly relates to the technical field of new energy power grid hybrid energy storage system regulation and control. Comprising the following steps: respectively constructing layered evaluation index systems of the hybrid energy storage unit in frequency modulation and peak regulation based on short, medium and long time scales; determining the weight of each level index in the index system; based on the hierarchical evaluation index system and the weight of each hierarchical index, performing comprehensive potential evaluation on the hybrid energy storage unit; and according to an evaluation result, the regulation and control capability of the hybrid energy storage system under different time scales is comprehensively evaluated, and an optimization and scheduling strategy of the energy storage unit is formulated according to the evaluation result. The method has the beneficial effects that the frequency modulation, voltage regulation and peak regulation potentials of the hybrid energy storage system can be quantified under different time scales, and the optimal energy storage configuration and operation strategy can be formulated according to the frequency modulation, voltage regulation and peak regulation potentials.

The invention relates to the technical field of geothermal resource development, and discloses a geothermal resource prediction method and system based on multi-source data fusion, and the method comprises the steps: obtaining a multi-source geothermal basic data set, carrying out the weighted fusion analysis of the multi-source geothermal basic data set, and extracting a comprehensive geothermal feature vector meeting a resource enrichment condition; carrying out potential evaluation and weight fusion according to the feature vector, generating an earth heat flux density distribution potential map and determining a high potential area; on this basis, potential development point locations are identified, and a candidate well location preliminary set is formed; performing comprehensive evaluation and sorting on the candidate well positions to obtain an optimized well position set; performing combined influence evaluation and interference judgment by combining well location distance constraint conditions, and constructing a constraint relation matrix; and through multi-round combination screening and optimization, an optimal well position combination scheme is determined, and a complete implementation scheme is generated and used for small-scale geothermal development and implementation. According to the method, high-precision well position selection and development scheme optimization can be realized.

The invention provides a reserve land development potential grading evaluation method and system based on pattern spot data, and relates to the technical field of reserve land development management, and the method comprises the steps: carrying out the pattern spot data mining of reserve land, and obtaining an original pattern spot data set with pattern spot attribute information; performing multi-level classification and layering according to a spatial planning hierarchical relationship, and extracting a potential constructable base range; performing pattern spot spatial topology processing, extracting pattern spot geometric feature parameters, and performing pattern spot scale division based on a preset area threshold value; establishing a pattern spot potential evaluation index system, and performing pattern spot development potential category division; and executing the refined extraction of the available space to form a visual board for the reserve land. The technical problems that in the prior art, the development potential of the reserve land is evaluated by depending on manual judgment and a rule-based simplified evaluation model, the evaluation precision is insufficient, the development potential of the land cannot be comprehensively reflected, and the scientificity and rationality of a development decision are further influenced are solved.

The invention discloses a mineralization potential evaluation and target region optimization method and system based on machine learning, and relates to the technical field of mineral resource exploration. The method comprises the following steps: acquiring multi-dimensional data of a target area; preprocessing the multi-dimensional data to obtain preprocessed key data; a metallogenic system conceptual model is constructed, and a hydrothermal migration path and a metallogenic fluid pressure field of the key data are calculated through finite element simulation for visual display; generating an evidence layer based on the key data to obtain multi-dimensional evidence layer data; and constructing a mineralization potential evaluation model, and inputting the multi-dimensional evidence layer data into the mineralization potential evaluation model for prediction to obtain a mineralization probability prediction result. Through multi-source data fusion and machine learning algorithm innovation, intelligentization and precision of mineralization potential evaluation and target region optimization are realized, and an efficient technical means is provided for mineral resource exploration.

The invention discloses a forsythia suspensa growth vigor monitoring method based on unmanned aerial vehicle remote sensing, and particularly relates to the technical field of unmanned aerial vehicle remote sensing monitoring. S2, calculating a vegetation index; s3, obstacle recognition; s4, evaluating the growth vigor; and S5, grade drawing. According to the method, a structured data set is constructed through integration of multispectral data and space coordinates, a high-resolution vegetation index map is generated in a pixel-by-pixel calculation mode, non-vegetation obstacles are accurately recognized by combining band ratio analysis and threshold judgment, vegetation index change trends are analyzed through time series data, and phenological period standard interval deviation is calculated. Spatial growth trend grade distribution is generated through mapping evaluation coefficients, the processing logic realizes closed-loop linkage of data acquisition and analysis, eliminates interference of non-target ground features, improves the accuracy of monitoring results, establishes a dynamic evaluation mechanism, and provides reliable basis for precise agricultural management.

The invention discloses a front subframe structure MaOP method and device based on TPT, a medium and a program product, and the method comprises the steps: (1) constructing a MaOP design model capable of optimizing the weight, modal, strength and rigidity at the same time based on front subframe longitudinal beam and load analysis; (2) generating an elite population based on a diversity criterion and Latin hypercube, obtaining target values of the elite population, establishing a data set, and constructing a radial basis function model; (3) designing co-evolution operation driven by TPT to generate a candidate frame set; (4) an individual potential evaluation criterion is constructed based on the advantage and disadvantage target sets, and an optimal candidate frame is screened; and (5) obtaining each target value of the optimal candidate frame, updating the data set and the radial basis function model, returning to the step (3) until all optimization targets meet requirements, and outputting an optimal parameter value. According to the method, a TPT-driven coevolution mechanism is adopted, radial basis function model prediction is combined, and the multi-performance index optimization process for the front auxiliary frame can be effectively balanced.

The invention provides an energy monitoring method based on user working condition identification and energy-saving space prediction, and the method comprises the steps: carrying out the dynamic adjustment and collection of multi-source data based on a self-adaptive data collection strategy according to a user load rate, carrying out the data fusion of the collected multi-source data according to the spatial-temporal characteristics, and constructing high-dimensional working condition feature data; based on the high-dimensional working condition feature data, generating a working condition identification result by using a pre-trained light-weight deep learning working condition classification model in combination with an adaptive sliding window mechanism; and constructing a dynamic energy efficiency reference model, calculating optimal energy consumption under the current working condition based on matching of historical data and a real-time working condition identification result, and quantifying a single-point energy-saving space, predicting multi-point collaborative energy-saving potential and performing real-time energy efficiency monitoring intervention based on a preset layered energy-saving potential evaluation framework. According to the invention, dynamically changing user working conditions can be effectively identified, and energy space prediction can be accurately detected and quantified.

The invention discloses a power utilization potential prediction and response regulation and control system, and the system comprises a panoramic sensing module which is used for the synchronous collection of data; the dynamic modeling module is used for fusing multi-source data according to space, time and semantic association rules to generate a standardized electric power characteristic spectrum; the situation deduction module is used for identifying industrial adjustable capacity, commercial peak shifting potential and resident elastic interval and constructing a three-dimensional potential matrix; the collaborative optimization module is used for establishing an economy-environmental protection-user satisfaction multi-objective function by taking power grid security as a hard constraint, and driving a basic strategy library, a real-time optimization engine and emergency mode hierarchical regulation and control; and the efficiency verification module is used for tracking closed-loop optimization of indexes such as load peak-valley difference reduction rate and the like. According to the method, adjustment potential space-time quantification, multi-target collaborative optimization and strategy dynamic evolution are realized, and the adjustment potential evaluation time of the actual measurement region is shortened.

The invention discloses a corn planting suitability comprehensive evaluation method which comprises the following steps: step 1, data collection and index system construction: a system collects multi-source information of meteorological data, crop growth data and historical disaster data, and a comprehensive corn planting suitability evaluation index system is constructed, the method comprises the following steps of 1, selecting a corn growth period, 2, dividing the growth period: determining four key stages of the corn growth period in combination with related data and local production practice experience, 3, constructing a comprehensive evaluation model, 4, evaluating the planting potential and carrying out weighting processing, 5, carrying out comprehensive evaluation and zoning, and 6, carrying out comprehensive evaluation and zoning. According to the method, the blank of the existing research in comprehensive evaluation of the corn planting suitability is filled, a new thought and method are provided for coping with agricultural risks caused by climate changes, a scientific regionalization reference is provided for agricultural decision makers by constructing a perfect corn planting suitability evaluation system, and the corn planting suitability evaluation method has a wide application prospect. The guarantee of global grain safety and the sustainable development of an agricultural ecosystem are facilitated.

The invention relates to the technical field of low-carbon park carbon reduction potential estimation, and discloses a low-carbon park flexible resource aggregation carbon reduction potential evaluation method, system and device and a medium. Multi-stage preprocessing and analysis are performed on operation data and carbon emission data of flexible resources in the low-carbon park, and the polymerization carbon reduction potential of the low-carbon park can be accurately evaluated. In the data processing process, each preprocessing stage has unique mechanisms and logics, such as spatial-temporal feature extraction, resource clustering and aggregation parameter calculation in the second preprocessing, and carbon footprint dynamic prediction, time-varying capability evaluation and fuzzy weight self-adaption in the third preprocessing. And index calculation, uncertainty analysis, report generation and the like in the fourth preprocessing are carried out.

The invention relates to a transformer substation bus-level adjustable load potential evaluation and hierarchical regulation and control method and system for regional differences, and belongs to the technical field of intelligent power grid regulation and control. The method comprises the steps of obtaining transformer substation bus load data, and performing missing value processing on the transformer substation bus load data through a data missing processing model to obtain bus load reference data; performing curve clustering on the bus load reference data to obtain a load characteristic curve; performing potential evaluation based on the load characteristic curve and outputting a bus load potential evaluation result; and constructing a regional aggregation load characteristic model, and outputting an optimal load regulation and control strategy through hierarchical regulation and control according to the regional aggregation load characteristic model and a bus load potential evaluation result. And transformer substation bus-level adjustable load potential evaluation and hierarchical regulation and control oriented to regional differences are realized.

The invention relates to the technical field of geological information, and discloses a mineral resource potential rapid evaluation method and system based on big data, and the method comprises the steps: automatically collecting geological, remote sensing, geophysical and geochemical exploration and mining data through a multi-source interface, executing intelligent format recognition and structural analysis, and storing the data into a distributed data lake; scheduling parallel computing nodes according to task parameters, synchronously operating five sub-models including space superposition, geochemical anomaly identification, construction of mine control factor extraction, remote sensing alteration enhancement and mining intensity regression; and generating a comprehensive potential evaluation map through dynamic weighted fusion, and outputting a visual result and an uncertainty quantitative index. According to the technical scheme, the evaluation period is shortened from several weeks to several hours, the data processing accuracy is improved to 97% or above, the hit rate of the evaluation result in the known ore deposit area reaches 89%, and the mineral exploration efficiency and decision scientificity are improved.

The invention discloses a foreign language learning potential assessment method and system based on multi-modal data fusion, and the specific implementation scheme is as follows: creating a task event, collecting the multi-modal data of a subject in real time, and carrying out the time alignment of the multi-modal data and the task event through a timestamp or a trigger signal; performing data preprocessing on the multi-modal data and extracting behavior features and neurophysiological features; performing deep fusion analysis on the behavior features and the nerve physiological features in time dimension and space dimension to generate optimal comprehensive features; and performing quantitative evaluation on foreign language learning potential by using a deep fusion analysis result, and generating a feedback report. According to the method, foreign language learning potential is expanded into a behavior and cognitive nerve double-dimensional structure, and the problems of single evaluation dimension and insufficient mechanism interpretation caused by the fact that a traditional method only depends on behavior scores are solved; through synchronous acquisition and real-time analysis of the multi-mode reaction of the learner in the task, the change of the cognitive state along with time can be dynamically monitored.

The invention belongs to the field of power distribution area resource scheduling, and provides a power distribution area adjustable resource complementary potential evaluation method and system fusing subjective and objective, and the method comprises the steps: constructing a power distribution area complementary potential evaluation index system; based on the sorting result of each index, determining the subjective weight of each index by using an order relation analysis method; acquiring actual operation data corresponding to the indexes, and determining objective weights of the indexes based on the standard deviations of the indexes and conflicts among the indexes; performing fusion optimization based on the subjective weight of each index and the objective weight of each index to obtain a subjective and objective evaluation fusion weight; and obtaining actual operation data corresponding to each index, determining cloud model digital features of each index based on subjective and objective evaluation fusion weights, and performing weighted fusion by using a cloud model to obtain an evaluation result. According to the method, the operation characteristics of the multi-type adjustable resources in the power distribution area can be comprehensively depicted from the three aspects of source, load and source-load complementation.

The application discloses a kind of control fishing yield seal population recovery potential evaluation method and device, it is related to marine ecological protection and restoration field, mainly includes: four steps of modeling, predation rate calculation, fishing quantity reduction stage determination and seal population recovery potential evaluation.The application is based on Ecopath model, by introducing predation rate parameter, dynamically adjusts seal food habit matrix, reduces the data requirement of modeling, realizes the quantitative evaluation of fishing control measure protection benefit, provides practical method tool for seal population recovery potential evaluation.Therefore the seal population recovery potential evaluation method and device based on control fishing yield provided by the application have good seal population recovery potential evaluation ability, and can be widely applied to marine biological population resource recovery potential evaluation field.

The invention relates to the technical field of enterprise development evaluation, and particularly discloses an enterprise development potential evaluation method based on big data, and the method comprises the steps: collecting agricultural enterprise multi-source heterogeneous data through distributed nodes, importing a deep learning driven multi-modal fusion model, and generating a high-dimensional feature vector through cross-modal feature alignment and weighting; inputting the high-dimensional feature vector into a risk and pressure resistance evaluation model, constructing a dynamic risk conduction network mining risk association, generating a risk evaluation vector in combination with a time sequence feature, cascading the risk evaluation vector with the high-dimensional feature vector, and then generating a fusion feature vector through nonlinear transformation; and on the basis, a quantitative index is generated through multi-dimensional feature matching, and a comprehensive evaluation result is output through multi-scale decision analysis. According to the method, deep fusion of multi-source data is realized, risk changes are dynamically captured, evaluation comprehensiveness and accuracy are improved, and a reliable basis is provided for decision making of agricultural enterprises.

The invention discloses an electrified flexible source load adjustable potential evaluation method considering cold load characteristics, and particularly relates to the technical field of electric power system evaluation and control, and the method comprises the steps: S1, obtaining the environment and equipment parameters of a cold load monomer, S2, constructing an electric-thermal coupling refined model considering a comfort level elastic interval, and S3, constructing an electric-thermal coupling refined model considering a comfort level elastic interval; the method comprises the steps of S1, obtaining a plurality of monomers, S3, calculating the adjustable potential of the monomers and generating a constraint envelope line representing the dynamic attenuation characteristics of the monomers, S4, obtaining a regional cluster potential evaluation result through aggregation according to the spatial dimension and the time scale, and S5, uploading the result to a power grid dispatching system for security defense and intelligent dispatching of a power grid of 750 kilovolts and above. According to the method, accurate quantification and dynamic representation of the adjustable potential of the cooling load are realized, the blank of cognition of a large power grid on the distributed cooling load is filled, and the flexible resource utilization level and the operation safety of the power grid are remarkably improved.

The invention relates to the technical field of costume design of artificial intelligence, and particularly discloses an AI costume style customization design method based on multi-modal user portray.The method comprises the steps that firstly, multi-source heterogeneous data of network e-commerce, entity stores, free design communities and social media are collected; through feature extraction and alignment processing, the style semantic features of the text and the design element visual features of the image are mapped to a unified'style-element-market expression 'semantic space; analyzing a popularity change track of a design element based on the multi-modal feature vector set, and identifying a potential style vector in combination with a historical implosion feature mode; meanwhile, multi-modal user portrait vectors including consumption ability, social influence and aesthetic preferences are constructed; fusing the potential style vector and the user portrait vector, and inputting into a conditional generative adversarial network to generate a costume design atlas; and finally, optimizing and outputting a design scheme through explosion potential evaluation and multi-stage sorting.

The application provides a kind of industry typical user electric power demand response potential evaluation method, this method includes: S1, based on integrated empirical mode load decomposition and demand response willingness extraction industry user demand response characteristic;S2, based on industry user demand response characteristic and convolution self-attention mechanism realizes the evaluation of industry typical user demand response potential. The effectiveness of the method is verified by analyzing the demand response case of metal processing machinery manufacturing industry in a city of Zhejiang Province, China. The results show that the demand response potential evaluation results obtained based on the method are consistent with the actual response amount of the user. The application overcomes the modal aliasing problem, can capture the long-term and short-term dependence in time series, and considers the local context information of each period feature, which can ensure high accuracy and provide support for power supply companies or load aggregators to fully utilize user-side adjustable resources.

The invention discloses a method, a system, equipment and a medium for constructing a flexibility auxiliary service market clearing model considering energy storage and demand side resources, and belongs to the technical field of electric power auxiliary service market optimizing.The method comprises the steps that basic modeling is completed through a multivariate heterogeneous resource unified modeling system, resource differences are depicted, a comprehensive flexibility potential index is calculated, and the comprehensive flexibility potential index is calculated; establishing a flexibility potential evaluation model to quantify the resource adjustment capability; setting a multi-objective function and integrating the key constraint conditions to form a multi-objective flexibility auxiliary service market clearing model; and designing a model solving method based on a chaotic particle swarm-simulated annealing fusion algorithm. According to the method, key parameters such as energy storage life loss and demand side user comfort are introduced, so that a traditional homogenization hypothesis is broken through; constructing an adjustment capability-response speed-economy multi-index evaluation system, and quantifying the resource flexibility potential in combination with an entropy weight method; a multi-target clearing model of flexible value is established, and market cost, system benefit and resource cost are optimized.

The application provides a hierarchical and orderly regulation method based on flexible load group schedulable potential evaluation, aiming at solving the problems of inaccurate model, single evaluation dimension, uneven resource allocation and poor response fairness in the coordinated scheduling of multiple types of flexible load. The hierarchical and orderly regulation method based on schedulable potential evaluation constructs an energy-power-time three-dimensional evaluation system to improve the comprehensive characterization of the regulation ability of flexible load; through clustering, hierarchical and dynamic rotation mechanism, the precise screening and fair calling of high potential load are realized; the closed-loop feedback and system reconstruction mechanism is introduced to enhance the adaptability of the regulation strategy and the stability of the system, and meet the efficient identification and coordinated scheduling demand of flexible resources under the new power system.

The application discloses a kind of arid region reservoir water and sand prediction and coordinated regulation potential evaluation method and system, belong to water resources, silt treatment and reservoir optimization scheduling technical field.The technical problems of traditional model prediction accuracy insufficient caused by arid region hydrology data scarcity, water and sand prediction process is fragmented and reservoir desilting and silt reduction and water storage benefit difficult to be synergistically optimized, its gist is that: long short-term memory network is used to predict future runoff sequence by fusing attention mechanism, and the sediment concentration is calculated by combining the water and sand relationship formula;By setting the critical sediment concentration threshold, the high sediment concentration period is identified and the available water for dredging is calculated;At the same time, the flood resource potential is evaluated by combining reservoir capacity and water demand constraints;Finally, the coordinated scheduling scheme is generated by comparing the two potentials.The application realizes the integrated accurate prediction of water and sand process in arid region and the simultaneous quantitative evaluation of regulation potential, and provides intelligent decision support for multi-objective optimization scheduling of reservoir.

The invention discloses a regional prospecting method and system based on multi-element space coupling of a metallogenic system, and belongs to the technical field of mineral resource prospecting prediction and comprehensive modeling of the metallogenic system. The method comprises the following steps: acquiring multi-source spatial data covering a mine concentration area; according to a process mechanism of a metallogenic system, converting and constructing the multi-source spatial data into a background domain, a transmission domain, an ore containing domain and a target domain to indicate spatial distribution indexes; constructing a comprehensive metallogenic potential index for representing a spatial distribution pattern of the regional metallogenic potential; an uncertainty prediction index is constructed based on the consistency deviation degree between the domain index responses and the local difference, and synchronous credibility quantification is carried out on the comprehensive mineralization potential evaluation result; and in combination with a joint discriminant relationship between the mineralization potential index and the uncertainty index, performing classified screening and target region delineation on the regional mineralization abnormal unit, so as to realize continuous quantitative prediction of the regional scale mineralization potential and optimization of the prospecting target region, and provide a mineral geological exploration service developed by using a high technology.

The application provides a roof photovoltaic potential evaluation method combining land use types and image recognition, comprising: dividing the whole evaluation area into a plurality of sub-regions; in each sub-region, selecting a sub-region with the strongest correlation with the whole evaluation area in roof area distribution as a typical region by using an analytic hierarchy process; obtaining high-precision remote sensing images of the typical region; performing roof recognition and extraction on the high-precision remote sensing images by using a roof recognition AI model to obtain roof area spatial distribution; calculating the roof coefficient of each building land use type; estimating the roof area of the whole evaluation area according to the roof coefficient of each building land use type of the typical region, and further obtaining the roof photovoltaic installation potential. The application considers the efficiency and accuracy of roof photovoltaic potential evaluation, and realizes large-scale roof photovoltaic resource potential evaluation in a province. In addition, the application can roughly divide the potential values of different types of roof photovoltaic development potential, such as household and industrial and commercial roofs.

The invention provides a railway freight market potential evaluation method and apparatus, and an electronic device. The method comprises the steps of obtaining historical freight market data and a customer portrait; inputting the historical freight market data and the customer portrait into a potential evaluation model constructed based on a neural network to obtain a subject evaluation result and a corrected evaluation result; and obtaining a market potential evaluation result based on the subject evaluation result and the corrected evaluation result. According to the method and the device provided by the invention, the historical freight market data and the customer portrait are respectively input into the potential evaluation model constructed based on the neural network, the subject evaluation result and the corrected evaluation result output by the potential evaluation model are obtained, and the customer portrait is evaluated based on the subject evaluation result and the corrected evaluation result. The accuracy is higher, the reference value is larger, and the railway freight enterprises can be effectively helped to optimize transport capacity resource allocation.

The invention relates to the technical field of power system analysis, and discloses an electrograph analysis method for adjustable resources. The method comprises the following steps: establishing a unified topology model comprising a power station, a power transmission line, a transformer substation, a user and adjustable resource nodes, wherein the adjustable resource nodes comprise photovoltaic equipment, energy storage equipment and charging station equipment; collecting real-time operation parameters of each node, and generating a dynamic topological data set containing a voltage fluctuation sequence, a power transmission rate and equipment response delay data; performing multi-dimensional space mapping on the set to generate a distribution characteristic spectrum containing voltage gradient distribution, a power flow thermodynamic diagram and an equipment collaborative response matrix; deducing a resource state based on the map to obtain an adjustment potential evaluation result and a topological relation traceability path; and dynamically reconstructing the model according to an evaluation result, and generating an optimized resource scheduling instruction set. According to the method, power node information is integrated, accurate management and control of adjustable resources are realized, and complex operation requirements of a modern power system are met.

The invention discloses a shale gas reservoir horizontal well foam drainage process yield increase potential evaluation method, and relates to the technical field of petroleum and natural gas engineering, and the method comprises the following steps: S1, collecting related parameters, S2, analyzing a friction factor, S3, determining a stability coefficient, and S4, outputting a performance grade. Quantitative evaluation on diffusivity and stability of the foam scrubbing agent is realized by combining the flow pattern of the shaft, performance parameters of the foam scrubbing agent and the temperature and pressure of the shaft, and the yield increasing potential index is provided by integrating the diffusivity and stability of the foam scrubbing agent, so that the yield increasing capacity of the foam scrubbing agent of the shale gas well can be accurately reflected, and a yield increasing potential analysis grade is established; according to the method, different agents can be optimized through grading, meanwhile, a good guiding effect can be achieved during field application, the risk that the effect is not ideal and the economic cost is increased due to the fact that the agents are added according to experience is greatly reduced, and the method has application prospects and popularization value for shale gas wells of different blocks.