45 results about "Potential assessment" patented technology

The invention provides a power load regulation potential assessment method and system based on a total incoming line, and relates to the field of power data analysis, and the method comprises the steps: obtaining the total incoming line load data of a target power distribution system, and extracting feature factors; a causal directed graph with feature factors as nodes is constructed, the causal relationship between the nodes is determined through an improved PC algorithm, and the improvement comprises time delay expansion, chi-square statistic correction, time sequence constraint and dynamic adjacency optimization; performing anti-fact reasoning based on a causal diagram to obtain a predicted value of the total load; according to the multi-dimensional adjustment potential index, calculating the load adjustment potential under virtual intervention through the predicted value of the total load; according to the method, non-intrusive, explainable and dynamic evaluation of the user load flexibility adjustment potential is realized.

The invention belongs to the field of expressway traffic data analysis, and relates to an ETC system-based expressway traffic data analysis method, which comprises the following steps of: acquiring original vehicle passing data streams which are acquired by all ETC gantries in a preset time period of a monitored road section and comprise vehicle identifiers, passing timestamps, portal position codes and vehicle type codes; analyzing the original vehicle passing data flow to generate vehicle speed individual dynamic features and vehicle type group static features, constructing a multi-dimensional risk data set with road segment identifiers and time windows as indexes, and inputting the multi-dimensional risk data set into a pre-trained deep learning model, and outputting an accident potential probability value result, executing early warning state judgment based on a probability gradient judgment rule, generating an accident risk thermodynamic diagram of the monitored road section according to the early warning state, and feeding back the accident risk thermodynamic diagram, thereby effectively solving the problems of insufficient prospective prediction and low regional accident potential assessment precision in the prior art. And the timeliness and the accuracy of traffic risk assessment are obviously improved.

A green performance retrofitting design method for existing primary and secondary school buildings, comprising: investigating green retrofitting technical measures for existing school buildings, so as to screen for a certain number of most frequently used green retrofitting technical measures with energy-saving and emission-reduction effects; on the basis of the selected green retrofitting measures, constructing a green retrofitting potential assessment method for existing primary and secondary school buildings in hot-summer and cold-winter regions; using the assessment method to assess the existing primary and secondary school buildings, so as to determine existing primary and secondary school buildings with greater retrofitting potential; selecting the existing primary and secondary school buildings with greater retrofitting potential as cases, so as to construct a multi-objective optimization model; and using the multi-objective optimization model to optimize the green performance retrofitting technical solutions for the existing primary and secondary school buildings. The retrofitting design method better reflects dual-carbon goals, thus greatly improving the retrofitting effect.

The invention discloses an electric vehicle demand response potential assessment method, system and device, and a medium. The method comprises the following steps: establishing a demand side response time-of-use electricity price model; establishing a user objective response capability constraint model; calculating a charging response rate and a discharging response rate of the user according to the incentive electricity price and the current residual electricity quantity of the user; calculating an objective index coefficient and a subjective index coefficient according to the objective response capability value and the subjective response potential value of the user; and collecting user satisfaction feedback data according to the demand response potential evaluation value, and adjusting the time-of-use electricity price decision result according to the user satisfaction feedback data. According to the method, the demand side response time-of-use electricity price model and the user objective response capability constraint model are established, the battery safety electric quantity, the charging demand and the limitation of the charging pile rated power of the electric vehicle and the subjective response intention of the user are comprehensively considered, and the demand response potential of the electric vehicle user can be evaluated.

The invention discloses an enterprise electricity user grouping and label evolution method, relates to the technical field of artificial intelligence of a power system, and realizes accurate grouping, dynamic label updating and behavior trajectory tracking of enterprise electricity users by constructing a multi-level feature extraction system, improving an incremental clustering algorithm and establishing a label evolution and traceability graph. The method can effectively solve the problems of insufficient feature fusion, low clustering efficiency, tag staticization and the like in the traditional technology, provides a more accurate user portrait tool for a power grid enterprise, supports key power utilization enterprise identification, energy storage potential evaluation, demand response scheduling and other core services, and improves the user experience. The method plays an important technical support role in improving the load side management level of a power system, promoting new energy consumption and assisting the construction of a novel power system.

The invention provides a modular geological oil and gas intelligent investigation system and a scheduling method. The investigation system comprises a core agent and a specialized MCP Server cluster. The core agent is responsible for task analysis, module scheduling, result integration and exception handling, and core components of the core agent comprise a task analyzer, a module scheduler, a result integrator, an exception processor and a state monitor; the specialized MCP Server cluster utilizes a standardized model calling protocol to realize communication and data exchange between the core agent and each specialized Server; the specialized MCP Server cluster comprises a regional information extraction Server, an oil and gas feature recognition Server, a cross-document association reasoning Server, a data reliability evaluation Server, a space-time dimension classification Server, a reservoir forming element reasoning Server and a dynamic potential evaluation Server. The system has the capabilities of'modular architecture, standardized interface, flexible scheduling and resource optimization ', and can realize efficient construction, flexible expansion and intelligent scheduling of a modular geological oil and gas intelligent investigation system.

This invention discloses a data-driven method and terminal for assessing demand response potential. It constructs an objective function for demand-side response costs based on user demand response data and an electricity price model. By combining Wasserstein distance, a fuzzy set of response behaviors considering user behavioral uncertainty is obtained. Furthermore, the fuzzy set is corrected using moment information, avoiding assessment biases caused by a small sample size. This method not only considers the impact of user demand response on the potential assessment results but also incorporates the probability distribution information of user demand response behavior, thereby effectively narrowing the boundary of the uncertain set and better calculating the scale of user demand response. This helps to formulate more reasonable user demand response strategies and further optimize power system operation and planning.

This invention belongs to the field of deep learning and renewable energy assessment technology, specifically a method and system for assessing urban photovoltaic potential based on multimodal deep learning. The method includes: acquiring and preprocessing multimodal data of the study area; constructing and training a multimodal deep learning model, which includes a roof recognition module based on a semantic segmentation network and a multimodal fusion module consisting of image branches, table branches, and a fusion output layer to output roof masks and potential correction parameters; based on the model output, sequentially calculating the roof's radiation potential, installation potential, technical power generation potential, carbon emission reduction potential, and economic potential, forming a multi-level potential assessment system. This invention, by fusing multi-source heterogeneous data, achieves high-precision, high-efficiency, and systematic assessment of rooftop photovoltaic potential at the urban scale, providing strong support for urban energy planning and decision-making.

This application relates to a method, apparatus, and electronic equipment for assessing the demand response potential of a zero-carbon hydrogen metallurgical system. The method includes: constructing an operating model of a hydrogen-based shaft furnace considering the metallization rate of direct reduced iron; establishing an objective function based on the production baseline load of the zero-carbon hydrogen metallurgical system; constructing a demand response potential assessment model for the zero-carbon hydrogen metallurgical system based on the objective function, constraints of the electrolyzer in the zero-carbon hydrogen metallurgical system, and constraints of the operating model of the hydrogen-based shaft furnace; determining the demand response potential assessment index for the zero-carbon hydrogen metallurgical system; and assessing the demand response potential of the zero-carbon hydrogen metallurgical system under real-time electricity pricing based on the assessment model and the assessment index. This solves the problems in related technologies, such as the lack of assessment of the flexibility of the zero-carbon hydrogen metallurgical system and the limited utilization of flexibility resources, leading to severe wind and solar power curtailment, grid backflow, and voltage exceedances, resulting in high production costs.

This invention provides a system and method for online monitoring and cathodic protection assessment of corrosion in well site oil pipelines, belonging to the technical field of online monitoring and cathodic protection for oil pipeline corrosion. The system includes an online corrosion monitoring system for well site oil pipelines, a cathodic protection potential assessment system, a corrosion and cathodic protection data acquisition unit, a local online corrosion and cathodic protection monitoring unit, a well site oil pipeline, and a remote monitoring center unit. The corrosion and cathodic protection data acquisition unit is electrically connected to the remote monitoring center unit via the local online corrosion and cathodic protection monitoring unit. The corrosion and cathodic protection data acquisition unit is also electrically connected to the online corrosion monitoring system and the cathodic protection potential assessment system located on the well site oil pipeline via corresponding network cables. This invention, through the combined use of multiple corrosion detection methods, ensures the reliability of the detection results and reduces the limitations of single-method detection results.

The embodiment of the invention discloses a tobacco waste hydrothermal solution resource utilization potential evaluation method and system. The method comprises the steps that basic property data of waste biomass and the egg incubation inhibition rate of hydrothermal solution to root-knot nematode attached to the waste biomass at different temperatures at multiple temperatures are collected through a data input layer; the basic property data and the egg incubation inhibition rates at the multiple temperatures are preprocessed, and a waste biomass data set and an egg inhibition rate data set are obtained; predicting a target recycling potential score corresponding to each waste biomass type based on the waste biomass data set through a deep belief network of a module processing layer; determining an optimal hydro-thermal treatment parameter combination based on the target recycling potential score and the worm egg inhibition rate data set through a deep Q network of a module processing layer; and generating a recycling potential evaluation report and a processing parameter optimization scheme based on the target recycling potential score and the optimal hydrothermal treatment parameter combination through a result output layer.

This invention discloses a method and apparatus for optimizing and ranking oil and gas exploration blocks, relating to the field of oil and gas resource exploration technology. The method includes: acquiring raw data from multiple blocks; processing the raw data from multiple blocks using a tree model to output the intrinsic potential value of each block; extracting the weights of each potential assessment dimension using the tree model and determining the intrinsic potential value of the block using these weights; processing the raw data from multiple blocks using a pre-set data envelopment analysis model to output the relative efficiency value of each block; performing cluster analysis on the multiple blocks using the raw data to obtain multiple clusters, and determining the clustering attractiveness value of each block based on these clusters; fusing the intrinsic potential value, relative efficiency value, and clustering attractiveness value of each block to obtain a comprehensive score for each block; and ranking the multiple blocks based on their comprehensive scores. This invention can improve the objectivity, accuracy, and interpretability of the block optimization and ranking analysis results.

This invention discloses a system for assessing the development potential of pumped storage power stations based on the geographical characteristics of reservoirs. It relates to the field of pumped storage power station site selection and planning technology, including acquiring data on existing reservoir dams and satellite remote sensing topographic data; selecting existing reservoirs as downstream reservoirs for pumped storage power stations based on their capacity; searching for sites around downstream reservoirs as upstream reservoirs for both mountainous and flat terrain based on topographic data of existing dams; estimating the potential capacity and energy storage capacity of upstream reservoirs to calculate the theoretical potential for developing pumped storage power stations; and excluding areas with human activity, transportation facilities, and water body restrictions to calculate the achievable potential for developing pumped storage power stations. This invention provides technical support for the development of pumped storage power stations by adding upstream reservoirs to existing reservoirs on a large spatial scale, solving the problems of traditional potential assessment methods being limited by single terrain features and inefficient, and contributing to the sustainable development of pumped storage power stations.

The invention discloses a new technical scheme-oriented standard association relationship analysis method. The method comprises the following steps of constructing a data set of new technical related data and existing standard data in the field of intelligent driving; carrying out standard incidence relation modeling based on a heterogeneous graph neural network on the data set, and constructing a technology-standard heterogeneous graph; initializing node features in the atlas, and performing multi-modal fusion; performing multilayer message passing by adopting an adaptive graph attention network, and dynamically adjusting an attention weight to capture high-order dependence between a technology and a standard; after multi-layer message transmission, calculating a final correlation score; the multi-dimensional features are fused, and the feature similarity is quantized; and predicting the standardization potential of the new technology by adopting a quantitative scoring method, and outputting a technical standard potential score of the new technology. According to the invention, the efficiency and accuracy of correlation determination of the new technology and the standard are improved, and a scientific basis is provided for standardized potential assessment.

The application discloses a kind of air conditioner load demand response potential evaluation method and system, it is related to power system demand response technical field.The present application includes: constructing air conditioner user before response load data set and after response load data set;Adaptive load prediction model is constructed, and time series distribution adaptation mechanism is introduced, the distribution difference of different time period data on each layer output of encoder is calculated, and is added to model training target as regularization term;Before response and after response load data set is input into two adaptive load prediction models respectively for training, the feature data of the time to be evaluated are input into two models respectively, obtain before response load prediction value and after response load prediction value, calculate the difference value of both, it is evaluation result.The present application fuses Transformer network and distribution adaptation mechanism, can effectively capture air conditioner load long-term dependence relationship and adapt time series distribution drift, for realizing high-precision potential evaluation in the case of lack of historical response data.

The invention discloses a power utilization growth potential evaluation and potential grading result output method for a park enterprise, relates to the technical field of cross-park power and carbon flow management, and aims to solve the problem that the power utilization growth potential of the park enterprise cannot be evaluated due to data islands, evaluation distortion and insufficient carbon flow accounting precision in a cross-park scene. The method comprises the following steps: S1, constructing a cross-park unified green electricity authentication block chain system, and realizing green electricity full-link cross-domain traceability through data standardization adaptation and a multi-subject consensus mechanism; s2, a dynamic carbon flow accounting model is constructed based on dynamic prediction of a multi-park power supply structure, and accurate carbon flow accounting is completed in combination with real-time power transmission data; and S3, establishing a three-dimensional grading evaluation system for verifying the credibility of the fused data. The method has the advantages that the evaluation and carbon flow accounting accuracy is improved, and the dynamic adaptation of power resources to enterprise demands and targets is realized.

The invention discloses a strong bad alteration tunnel surrounding rock disintegration-argillization test device and method, and relates to the technical field of tunnel engineering geological testing and rock and soil disaster risk assessment. The disintegration-argillization test method for the tunnel surrounding rock with strong bad alteration mainly comprises the following steps: soil sample pretreatment, cyclic disintegration-argillization test, sample collection and drying, argillization preparation, performance test (argillization degree test and full-amount intelligent detection) and potential evaluation, and synchronous acquisition of multi-dimensional quantitative indexes. According to potential evaluation, index weights are distributed based on an analytic hierarchy process, a comprehensive scoring model and an alteration degree index model are established through weighted summation, and four-level potential grading is achieved. By implementing the disintegration-argillization test device and method for the strong bad alteration tunnel surrounding rock, the test precision and efficiency of the disintegration-argillization test for the strong bad alteration tunnel surrounding rock can be improved.

The invention relates to the field of data processing and intelligent recommendation, and discloses a post pushing method and system based on artificial intelligence, and the method comprises the steps: obtaining a user resume, post preference and a description text; resume time sequence features are extracted and quantified, and occupational development and cooperation mode features are obtained; mining a behavior pattern based on occupational development characteristics and predicting a path; performing semantic extraction on the post text, and constructing a feature semantic representation set; calculating the matching degree of the path and the post semantic set, and combining preference weighting to obtain a preliminary result; determining a candidate set through hierarchical screening; and performing potential evaluation and sorting, and filtering according to a cooperative matching threshold to obtain a final recommendation set. According to the invention, the vocational evolution rule can be accurately mined, and the matching precision of vocational path prediction and post pushing is improved.

The invention provides a distributed wind power generation development potential assessment method and system, and relates to the technical field of new energy and information. The method comprises the steps of collecting meteorological data, topographic features, surface vegetation features and historical wind power data of a target area; analyzing topographic features and surface vegetation features through an MLP model, and capturing a mapping relation between spatial distribution features of a target area and wind power; historical wind power data are processed through a TCN model, and time dependence characteristics of wind power are extracted; the meteorological data are processed through a ConvLSTM model, and the space-time correlation of the wind power is obtained; the optimal weight of the MLP model, the optimal weight of the TCN model and the optimal weight of the ConvLSTM model are solved through a linear programming method, and an MLP-ConvLSTM-TCN combined prediction model is obtained; and the wind power of the target area is predicted through the MLP-ConvLSTM-TCN combined prediction model, so that the distributed wind power generation development potential of the target area is evaluated. According to the invention, the wind power generation power of a specific area can be accurately predicted, so that an accurate resource scheduling and power transaction strategy is provided.

The invention provides an engineering layout-based new cultivated land potential evaluation method for global land comprehensive improvement, relates to the technical field of land space planning and geographic information, and realizes semantic unification of multi-source land utilization data through a land type intelligent conversion engine. And performing engineering adaptability screening on the potential land parcels by adopting a dynamic threshold mechanism. Constructing a chain topology erasure model to realize cooperative processing of the multi-stage restricted area; an engineering-oriented potential evaluation model is innovatively provided, and accurate evaluation is realized through comprehensive calculation of'potential plots + engineering radiation cultivated land '. According to the method, the technical bottlenecks of data processing fragmentation, weak engineering relevance and the like in traditional evaluation are broken through, a quantitative association system of engineering layout and resource potential is constructed, the accuracy of cultivated land potential identification is remarkably improved, the application range of the method in land space planning is expanded, scientific decision support is provided for global land comprehensive renovation, and the method is suitable for popularization and application. The method plays an important role in promoting the deep application of the GIS technology in the field of cultivated land protection.

The invention relates to the technical field of data reasoning, and discloses a building solid waste resourceful treatment decision-making method and system, and the method comprises the steps: obtaining waste feature data of building solid wastes, and carrying out the matching of the waste feature data with a preset resourceful potential evaluation rule library, and obtaining a waste resourceful potential grade; obtaining a physicochemical property set corresponding to the waste recycling potential grade, and performing suitability comparison on the physicochemical property set and a preset recycling treatment path; based on an adaptability comparison result, selecting a resourceful treatment path with the highest adaptability, and generating a preliminary resourceful treatment scheme of the building solid wastes according to the selected path; performing environmental-economic comprehensive benefit evaluation on the preliminary resourceful treatment scheme to obtain a target resourceful treatment scheme of the building solid wastes; the target resourceful treatment scheme is fed back to a resourceful treatment execution terminal of the building solid waste; the method can improve the decision accuracy of the resourceful treatment of the building solid wastes.

This invention discloses a multi-level autonomous operation and control method for medium- and low-voltage distribution systems. In the day-ahead phase, each distribution substation establishes a substation adjustable potential assessment model based on the operational characteristics of its adjustable resources, calculates the interactive power range for the next day, and reports it to the distribution network dispatch center. The distribution network then establishes a corresponding day-ahead safe operation range planning model for each substation based on the interactive power range, calculates the maximum allowable fluctuation range of interactive power for each substation, and transmits this value to the substation to provide interactive power boundaries for its autonomous operation. In the intraday phase, based on the safe operation range, the substations conduct autonomous rolling dispatch with the goal of optimal substation economics, and transmit the interactive power curves obtained from dispatching at each time period to the distribution network. Then, the distribution network formulates corresponding dispatch strategies based on the interactive power information of each substation, with the goal of optimal economics, to achieve efficient autonomous operation of the entire medium- and low-voltage distribution system.

This invention discloses a method, apparatus, terminal equipment, and storage medium for assessing the spatiotemporal load transfer potential of a data center, relating to the field of load assessment technology. The method includes: acquiring load transfer assessment parameters for the data center; determining a divisibility coefficient based on the maximum number of parallel subtasks and a preset parallelism benchmark value; determining a time flexibility coefficient based on the latest completion deadline and expected execution duration; determining a state dependency coefficient based on the total amount of migration state data and a preset state quantity benchmark value; determining a spatial transferability coefficient based on available link bandwidth, scheduling period length, data volume required for task migration, and data center transmission distance; and weighted summing of the above coefficients to obtain a load spatiotemporal transfer potential coefficient, thereby determining the load spatiotemporal transfer potential. By implementing this invention, the problem of prior art using only maximum tolerable latency to measure flexibility, leading to a deviation between the assessment results and actual schedulable capacity, can be solved, improving the matching degree of potential assessment results.

The invention discloses an industrial important security load safe operation potential assessment method and related equipment, and relates to the field of load monitoring. Comprising the steps that industrial total load data is collected in a non-intrusive mode, a security load super-state set is established based on improved K-means clustering and a finite state machine, a hidden Markov model is introduced to achieve key security load power decomposition, short-term power prediction is conducted on key security loads through a long-short-term memory network, and the security load super-state set is obtained. On the basis of considering equipment rated power, voltage allowable deviation and emergency starting time requirements, safety margin indexes such as a power margin, a response time margin and a voltage stability margin are calculated, and the safety margins before and after regulation and control are compared to obtain the safety operation potential. According to the invention, fine identification and prospective safety evaluation of the industrial security load are realized without adding an equipment side monitoring channel.

The application discloses a kind of fusions non-intrusive identification and thermal inertia decoupling resident air conditioner load portrait construction method.First, the intelligent electric meter total incoming line electrical data of the user to be monitored is obtained and synchronous outdoor meteorological data are acquired, and time series alignment is carried out;Second, the total incoming line electrical data is non-intrusively unmixed using a sequence-to-point convolutional neural network model, and the air conditioner equipment operating state sequence and operating power curve are extracted;Then, a dimension reduction thermal dynamics feature model is constructed, and the thermal-electric elastic coefficient, user comfort threshold temperature and normalized thermal inertia factor are decoupled, and a multi-dimensional user feature vector is constructed in combination with daily average power consumption;Finally, clustering is performed using a Gaussian mixture model, and the corresponding load portrait semantic label is assigned to generate a resident air conditioner load portrait.The application can identify the physical characteristics of the user's air conditioner load without installing an indoor temperature sensor, and improve the accuracy of demand response potential assessment.

The invention relates to the technical field of physical store marketing scheme recommendation based on user portraits, and discloses a physical store marketing scheme recommendation method based on user portraits. The data-driven and behavior-oriented physical store precision marketing method is formed through nine steps of interaction matrix construction, affinity matrix construction, social graph construction, sowing potential evaluation, diffusion simulation and grading recommendation. Comprising the following steps: numbering users, counting like private message sharing behaviors to construct an interaction matrix, generating an affinity matrix through normalization, constructing a social graph based on positive affinity, and defining a neighbor set; calculating the sowing potential, selecting seed nodes, setting a diffusion threshold value, then carrying out two-stage diffusion, forming an active set, and calculating the coverage rate; and finally, grading the activated users according to the seeding potential, and distributing marketing schemes of different grades. According to the scheme, interaction strength and propagation potential are introduced, the key node identification precision is improved, marketing resource configuration is optimized through a hierarchical strategy, and the marketing efficiency is remarkably improved.

The invention belongs to the technical field of new energy, and provides a resident user behavior feature-oriented comprehensive energy flexible demand response guiding method, which comprises the following steps of S1, constructing a resident behavior feature recognition model based on a multi-energy consumption track; s2, establishing a scenarized energy consumption preference analysis mechanism, and mapping resident living habits and typical energy consumption scenes; s3, designing a response guide strategy generation method based on behavior preference matching; according to the invention, through constructing a resident behavior feature recognition model based on a multi-energy consumption track, establishing a scenarized energy consumption preference analysis mechanism and designing a response guidance strategy generation method based on behavior preference matching, intelligent and personalized guidance and multi-energy cooperative response control of resident side flexible demands are realized; the behavior recognition precision and the accuracy of response potential evaluation are remarkably improved, the acceptability of flexible response and the participation willingness of the user are enhanced, and the flexible adjustment capability of the system and the comprehensive energy response efficiency are improved.

This invention provides a flight potential prediction method based on expert experience and dynamic profile generation technology, belonging to the field of flight potential prediction technology. The invention first constructs a multi-dimensional evaluation table including flight capability dimensions and non-capability factor dimensions, with two experts independently scoring to form an initial subjective assessment; it then establishes a mapping relationship between expert assessment scores and key objective flight parameters, parametrically calibrating the initial subjective assessment; it aggregates the calibrated expert assessments, objective parameter aggregation indicators, and psychological test data, forming a flight potential classification model based on potential profile analysis; finally, it generates and dynamically updates the flight potential profile, constructs a future flight performance prediction model, and dynamically corrects it. This method improves the stability, completeness, and predictive accuracy of flight potential assessment.

The invention relates to the technical field of photovoltaic potential assessment, in particular to an intelligent photovoltaic potential assessment method and system, and the method comprises the steps: carrying out the multi-scale feature extraction based on original image data, recognizing an area meeting a photovoltaic installation condition, and generating a boundary vector polygon; calculating an effective installation area in combination with obstacle information; identifying the roof type and the inclination angle, and determining the orientation according to the geographic coordinates; combining solar radiation time series data to predict unit area annual energy output; mapping the effective photovoltaic installation area and the annual energy output per unit area to a GIS (Geographic Information System) to generate a photovoltaic potential thermodynamic diagram; the method can automatically identify the roof and accurately consider the shielding influence, improves the reliability of the prediction precision of the generating capacity, and achieves the whole-process support from roof identification to investment evaluation.

The invention relates to the technical field of demand response analysis, and discloses an uncertain demand response potential analysis and calling method and system for a virtual power plant, and the method comprises the steps: building a physical constraint model according to a resource operation state set of a target virtual power plant, carrying out the causal analysis of the resource operation state set, generating an initial causal graph, and carrying out the calculation of the initial causal graph; identifying a latent variable with an implicit dependency relationship in the resource operation state set, embedding the initial causal graph to obtain an updated causal graph, performing proxy observation construction on the updated causal graph by using a direct influence variable of the latent variable, and performing demand response potential analysis on a target virtual power plant by using the target causal graph to obtain a demand response potential analysis result; and obtaining a resource response potential table and a hierarchical scheduling strategy, and carrying out rolling optimization calling on the target virtual power plant to obtain a target response calling result. According to the method, the cause and effect structure definition and the response potential evaluation accuracy are effectively improved, and the prediction deviation and uncertainty influence are effectively reduced.