71 results about "Potential assessment" patented technology

The invention discloses a multi-domain collaborative flexible load schedulable potential evaluation and energy management method, and relates to the technical field of park energy management, and the method comprises the steps: obtaining space-time multi-source data of a smart park, constructing a graph neural network power consumer clustering model based on iterative self-organization analysis, and generating a power consumption behavior portrait of a power consumer; based on power utilization parameters of building air conditioners, electric vehicles, park ponds and energy storage batteries in the smart park, the schedulable potential of the multi-element flexible resources is evaluated; and based on the hybrid neural network and the Harris eagle optimization algorithm, constructing a load prediction model, and predicting various types of energy loads in a future time period. The invention aims to establish an accurate model and method, accurately evaluate the schedulable potential of different types of flexible loads in different scenes, realize efficient utilization, energy conservation and emission reduction and optimal configuration of park energy, and improve the overall energy management level and operation efficiency of the park.

The invention discloses a building three-dimensional reconstruction method and system for distributed photovoltaic potential assessment, and a medium, and the method comprises the steps: carrying out the data fusion according to the OpenStreetMap block vector data and three-dimensional building model data of a region, obtaining a three-dimensional model of a single building, carrying out the merging and classification algorithm of multi-layer patches, and obtaining a three-dimensional model of a single building; automatically identifying a surface patch to which the building roof belongs, and dividing the building into a roof layer and a main body layer; a digital elevation model of a roof layer is generated, and roof structure reconstruction is carried out according to different roof types; and carrying out adaptive elevation stretching based on the OSM vector data contour to obtain a main body layer reconstruction result, and finally outputting reconstruction results of all buildings in the area. Large-scale urban building rapid modeling based on the method is achieved, and details of related roof structures are effectively reserved.

The invention relates to the technical field of ecological restoration and carbon sink evaluation, and discloses a river and lake ecological buffer zone carbon sink potential evaluation and restoration construction system which comprises a carbon sink potential evaluation module, an intelligent restoration construction module and a collaborative verification module. The carbon sink potential evaluation module is used for collecting soil and vegetation data and calculating the carbon sink potential; the intelligent restoration construction module executes ecological restoration based on a carbon sink potential evaluation result; and the collaborative verification module verifies the repair effect through multi-source data fusion, and returns an optimization instruction to the carbon sink potential evaluation module and the intelligent repair construction module. The vegetation coverage index and the root biomass density are acquired by using a multispectral sensor array, a carbon sink model is constructed by combining the organic carbon content of soil, dynamic weight adjustment is introduced, and the weight is updated according to aerial survey data of an unmanned aerial vehicle in each quarter, so that a more accurate and more economical carbon sink potential evaluation basis can be provided for ecological restoration, and the ecological restoration efficiency is improved. And resource waste and invalid repair are avoided.

The invention provides a building energy-saving potential assessment method and system based on an energy consumption quota, and the method comprises the steps: carrying out the energy consumption analysis of a to-be-assessed building through a clustering analysis algorithm and a regression analysis algorithm according to the energy consumption multi-factor data of the to-be-assessed building, and obtaining the energy consumption quota data and the carbon emission quota data; based on the energy consumption multi-factor data and the energy consumption quota data, performing power consumption prediction on the to-be-evaluated building by using a multiple linear regression algorithm to obtain power consumption prediction data; calculating target energy efficiency data according to the electricity consumption prediction data; according to the energy consumption quota data, the carbon emission quota data and the target energy efficiency data, performing energy-saving potential assessment on the to-be-assessed building to obtain a comprehensive potential score of the to-be-assessed building; according to the method, the energy-saving potential of the building is evaluated by combining the energy consumption quota data, the carbon emission quota data and the power consumption prediction data obtained by using the multiple linear regression algorithm, the actual energy consumption of the building can be comprehensively reflected, and thus the potential energy-saving opportunity of the building can be identified more accurately.

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.

The invention relates to the technical field of building capacity expansion, and discloses a multi-stage collaborative optimization green intelligent building capacity expansion planning system, which comprises a building evaluation analysis module, a capacity expansion planning design module, a construction management module and an operation maintenance module, and the building evaluation and analysis module comprises a current building situation diagnosis and analysis unit, a capacity expansion potential evaluation unit and a capacity expansion demand evaluation unit. According to the method, the current situation of the existing building is diagnosed and analyzed, and the maximum capacity expansion potential evaluation and the capacity expansion demand at the current stage are evaluated; generating a plurality of capacity expansion schemes, comparing and selecting the schemes, and selecting an optimal scheme according to requirements; digital management is carried out in the expansion construction engineering process, resource scheduling is optimized to meet construction requirements, and meanwhile construction quality and safety are monitored; and finally, intelligent operation and maintenance are carried out on the expanded building, energy efficiency optimization is achieved, collaborative optimization is carried out on building expansion in multiple stages, and a green intelligent building is achieved.

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 relates to the field of agricultural science and technology, and discloses a regional crop production potential assessment method and system based on a planting mode, and the method comprises the steps: collecting accumulated temperature data and rainfall data of a target assessment region, and calculating a theoretical multiple cropping index corresponding to the target assessment region; determining an ideal planting mode of the target evaluation area according to the theoretical multiple cropping index in combination with an existing planting mode; setting a target evaluation area for planting according to an ideal planting mode, and determining a theoretical sowing area of crops in the target evaluation area; setting a multi-scene mode, and selecting a theoretical planting mode; according to the theoretical sowing area, the actual sowing area and the actual crop yield per unit area, the crop production potential of the target evaluation area is evaluated, the method combines the theoretical multiple cropping index and the planting mode, is closer to production reality, sets a multi-contextual mode, flexibly adjusts the planting mode, and evaluates the crop production potential; and a scientific basis is provided for formulating a regional crop production policy.

Method for evading locally impending dangers, wherein an evasion route (14) for a vehicle (10) is calculated to avoid the impending danger, wherein a message about the impending danger is received by the vehicle (10), whereupon the vehicle (10) makes a danger potential assessment with respect to the reported impending danger and the vehicle (10) automatically resumes the driving operation in which it follows the evasion route (14) to avoid the impending danger, characterized in that a list of potentially reachable locations and passable stretch segments is established and a danger potential assessment is carried out for the reachable locations and passable stretch segments and is noted in the list, and the list with the noted reachable locations is sorted according to the lowest danger potential assessment and the shortest distance.

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 embodiment of the invention provides a wind energy resource development potential assessment method and device, equipment and a storage medium. Comprising the following steps: acquiring target meteorological data, a limited land area and an accessible range of a power system in a research area; wherein the target meteorological data represents meteorological data, based on a time sequence, of preset grid points in a research area; determining an effective area in the research area according to the target meteorological data, the limited land area and the accessible range of the power system; wherein the effective area represents an area where wind energy resources can be developed; and determining an evaluation result of the wind energy resource development potential of the research area according to the target meteorological data, the limited land area, the accessible range of the power system and the effective area. According to the method, the evaluation efficiency of the wind energy resource development potential can be improved.

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 discloses a chlor-alkali industry byproduct hydrogen and carbon footprint accounting method and management system. The method comprises the following steps: step 1, defining a system boundary; step 2, stage division; compared with the prior art, the method has the advantages that the emission amount of greenhouse gas generated in the whole life cycle of the chlor-alkali industry production process can be comprehensively quantified, the carbon footprint of the byproduct hydrogen can be accurately calculated and distributed, and the method has the advantages that the emission amount of the greenhouse gas generated in the whole life cycle of the chlor-alkali industry production process can be accurately calculated; and a comprehensive management system of the carbon footprint data is established, so that efficient carbon emission reduction planning and application potential evaluation are realized, a scientific basis is provided for evaluating the chlorine-alkali industry carbon emission level, a solid data foundation and decision support are laid for resource utilization of the byproduct hydrogen, and low-carbon development of the industry and resource utilization of the byproduct hydrogen are further assisted.

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 present invention relates to the technical field of urban management, and discloses a city potential assessment method and system based on multi-indicator fusion. The method comprises the following steps: deploying multiple data source collection points for a target potential assessment city, preprocessing initial environmental indicator data, and determining target environmental indicator data; extracting target environmental indicator data of the same type, constructing a target environmental indicator data series, and calculating environmental indicator data pointing coefficients; performing set division of environmental indicator data pointing coefficients based on a preset environmental indicator data pointing coefficient series, and calculating initial potential assessment factors; generating potential assessment identifiers for data source collection points; counting positive and negative quantities, setting a potential assessment optimization coefficient, optimizing the initial potential assessment factor, and obtaining a target potential assessment factor. The method evaluates the city potential based on the multiple environmental indicator data, thereby ensuring the accuracy and comprehensiveness of the city potential assessment and providing a basis for comprehensive urban development and key city selection by operators.

The invention relates to a building energy-saving potential evaluation system based on a dynamic prediction model and a block chain technology, and belongs to the field of building energy efficiency evaluation. The system comprises a dynamic energy consumption prediction module which is used for predicting the future energy consumption change of a building to be evaluated by using an artificial intelligence dynamic energy consumption prediction model and combining real-time data, and dynamically adjusting energy-saving potential evaluation; the block chain storage module is used for storing data and results involved in the evaluation process in a block chain; and the report generation module is used for generating an energy-saving potential evaluation report of the to-be-evaluated building in combination with the multi-dimensional dynamic data, and outputting an energy-saving optimization suggestion. According to the method, the problems that the building energy consumption change cannot be predicted in real time, an effective data traceability and tamper-proof mechanism is lacked and the dynamic energy-saving potential evaluation capability in a complex building environment is limited in the existing method are solved.

The invention relates to the technical field of potential evaluation, in particular to an industrial user multi-time-point adjustable potential quantitative evaluation method and system. The method comprises the following steps: setting a noise intensity coefficient of each time point based on a variance of an original load curve at each time point; based on the variance of the original load curve at each time point, the noise intensity coefficient at each time point and the Gaussian white noise with the mean value being 0 and the variance being 1, obtaining adaptive Gaussian white noise added to each IMF component; decomposing an original load curve into a plurality of IMF components through an improved ICEEMDAN algorithm by using the adaptive Gaussian white noise added to each IMF component; constructing an adjustable potential set based on the data set of each adjustable potential influence factor in continuous multiple days and the adjustable potential of each IMF component; and obtaining an adjustable potential value of the industrial user in each time period of the response day through the adjustable potential evaluation model. According to the method, the accuracy of multi-time-point adjustable potential quantitative evaluation of the industrial user is improved.

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 a resource regulation potential evaluation method and device, computer equipment, a medium and a product, and relates to the technical field of data processing. The method comprises the following steps: acquiring at least one initial building to be evaluated and power consumption data of each initial building at different historical moments; the power consumption data of the initial building comprises air conditioner power consumption data corresponding to the initial building; selecting at least one target building from the at least one initial building based on the power utilization data of each initial building; for each target building, at least one air conditioner power consumption data set corresponding to the target building is obtained; and for each air conditioner power utilization data set, according to the air conditioner power utilization data set, determining resource regulation potential information of the target building under the influence of the corresponding air conditioner operation mode and at least one target power utilization factor. By adopting the method, the resource regulation potential information of each building can be accurately obtained, and the process is relatively simple.