16 results about "Economic analysis" patented technology

The application discloses a park energy-carbon coordination early warning management and control method, relates to the technical field of energy saving and emission reduction and intelligent decision support, and comprises the following steps: establishing a unified atomic time reference, setting a unified time reference for a plurality of energy subsystems, generating a cross-source time anchor set under the unified time reference, and using the time anchor set to calibrate the sampling start time of each energy subsystem. The application realizes time alignment and real time sequence restoration of energy consumption data of multiple energy subsystems by establishing a unified atomic time reference and a cross-source time anchor set, and improves energy consumption fusion accuracy. By introducing conflict isolation and breathing time domain patching mechanism, the time distribution and load balance of peak value aggregation section are dynamically controlled, the energy consumption superposition amplification effect is inhibited, and the accuracy and stability of carbon emission reduction simulation and economic analysis results are ensured.

This invention discloses a multi-dimensional analysis system and method for regional economic development potential, aiming to solve the problems of scattered data, single dimensions, and subjective and lagging assessments in traditional regional economic analysis. It adopts a three-layer architecture: a data layer, a model layer, and an application layer. The data layer integrates multi-source data from statistical yearbooks, government information disclosure, the internet economy, and geospatial data, forming a unified analytical foundation through standardization and outlier processing. The model layer constructs a six-core dimension indicator system, including economic scale and industrial structure, and uses entropy weighting, TOPSIS, and regression analysis to achieve quantitative assessment, supporting dynamic updates and adjustments. The application layer outputs analysis results through visualization and customizable functions. This invention achieves deep integration of multi-source data, comprehensive characterization of multi-dimensional potential, and objective, accurate, and timely assessment results, adapting to various scenarios such as government decision-making and corporate investment, providing scientific and efficient decision support for high-quality regional economic development.

This invention relates to the field of rural economic data analysis technology, specifically an artificial intelligence-based method for rural economic data analysis. The method includes: delineating an economic data perception domain in a geographic information system based on the administrative division vector data of the target administrative village; collecting multi-source heterogeneous economic data through a protocol parser of an agricultural IoT terminal and converting it into standardized economic behavior data; extracting entities using natural language processing technology to generate a structured rural economic behavior fact table; inputting the fact table into a pre-trained economic activity association model and constructing a rural industry relationship graph using a graph embedding algorithm; and calculating the centrality index of economic entities based on the graph topology to identify core operating entities. This method enables accurate processing and association analysis of rural economic data, clearly presenting industry relationships and providing effective technical support for rural economic analysis.

The application discloses a kind of track traffic full life cycle economy estimation system based on multidimensional data, it is related to track traffic engineering economic estimation technical field, the system includes following component parts: data acquisition module, time sequence linkage mapping module, substage estimation model module, feedback correction module and dynamic output module;The application is through covering track traffic full life cycle, establishes effective association, to substage estimation model accurately calculates each stage economic cost, provides solid data support for economic analysis;Dynamic feedback correction mechanism is built, real-time response deviation changes, improve estimation accuracy;Whole-process closed-loop optimization design, solve prior art defects, adapt to project dynamic change, provide timely reliable reference for project full cycle economic management.

The application provides a wind power hydrogen production system economic analysis method and device based on a dedicated line power supply mode. The wind power hydrogen production system comprises a heating device for maintaining the temperature of an electrolytic cell within a preset temperature range. The method comprises the following steps: inputting preset wind power output power into the hydrogen production system, determining the size relationship between the wind power output power and the minimum rated power and the standard rated power, and determining the interval of the wind power output power; determining the actual power consumption and the working temperature of the hydrogen production system based on the wind power output power in different intervals; determining the total hydrogen production and the total power consumption of the hydrogen production system within a preset time according to the correlation between the current working temperature, the current actual power consumption and the hydrogen production, and determining the total operation income of the hydrogen production system. The application quantitatively analyzes the system economy under different input conditions or control strategies of the wind power hydrogen production system based on the dedicated line power supply mode under the condition that the alkaline electrolytic cell has a shutdown heat preservation function.

The application provides a kind of integrated energy system capacity planning method and system, belong to integrated energy station capacity configuration technical field, including: the reversible solid oxide cell power generation / hydrogen production system model and integrated energy system model are constructed;The mixed integer linear programming model of the integrated energy system model is established, the objective function is system thermal power total cost, constraint condition includes energy balance, mass balance, reversible solid oxide cell full working condition constraint and each component constraint;Input renewable energy output time series data, user demand time series data and component technical and economic parameters;Solve the solution of objective function under constraint condition, output integrated energy system each component optimal capacity configuration and each typical day under different time scene operation optimization result. By considering the dynamic change of reversible solid oxide cell efficiency with its load in capacity planning process, it is favorable to improve the accuracy of capacity optimization and economic analysis of system components.

The invention discloses a short-term offshore wind power prediction method, and the method comprises the steps: S1, collecting wind power time sequence data, and carrying out the preprocessing of the wind power time sequence data; s2, realizing fine division of the wind power plant group based on multi-source fusion spatial-temporal clustering analysis, and obtaining spatial-temporal correlation among the wind power plants; s3, constructing an offshore wind power prediction model based on a bidirectional space-time convolution module, a space-time attention module and a residual feature fusion module, and performing preliminary prediction on the offshore wind power; s4, performing maximum overlapping double-domain cooperative decomposition on the prediction error of the preliminary prediction of the offshore wind power, and extracting error information of different frequency bands; s5, introducing an attention mechanism to dynamically distribute weights, focusing key information to drive model feedback learning, improving offshore wind power prediction precision, and outputting a prediction result; and S6, performing comparative analysis, error analysis and economical efficiency analysis on the output prediction result. The problem that an existing offshore wind power prediction model is poor in prediction precision is solved.

The present disclosure provides a real-time data management and statistics method and system for wide load index of thermal power generating unit. The method comprises: collecting and managing multi-source real-time operation parameters from SIS; dividing multiple continuous load intervals based on rated power; in a statistical period, judging the interval to which the real-time load belongs, and respectively calculating the statistical values of performance indexes in each interval. Through pre-data management and fine load segmentation statistics, the present disclosure solves the problems of poor data quality and different statistical caliber under wide load operation, realizes accurate calculation of indexes, and provides reliable data support for unit operation optimization and economic analysis.

The application claims a cascaded feature extraction method for agricultural product price prediction, belonging to the technical field of artificial intelligence and agricultural economic analysis. The method adopts a three-level cascaded processing architecture: first, a filter-type coarse screening is realized through K-neighbor mutual information estimation, realizing preliminary dimension reduction; second, embedded feature selection is realized through an XGBoost model, and core prediction features are screened out; finally, multi-scale enhancement is realized through discrete wavelet decomposition on the time series core features, and trend and fluctuation components with clear physical meaning are constructed. Based on the processed enhanced features, a bidirectional long short-term memory network prediction model is constructed, and an ablation experiment of the system is designed to verify the effectiveness of each level of processing. Through systematic feature extraction and enhancement, the precision and stability of agricultural product price prediction are significantly improved, providing reliable technical support for market early warning and agricultural economic decision-making.

This invention discloses a peak-valley electricity pricing intelligent equipment control system based on multimodal video analysis, including a video acquisition module, an electricity pricing strategy acquisition module, an AI multimodal analysis engine, a dynamic scheduling controller, and an economic analysis module. The advantages of this invention compared to existing technologies are: Instead of focusing solely on energy costs in traditional equipment control, this invention introduces equipment lifespan and carbon emissions as optimization objectives, constructing a multi-objective optimization model to achieve synergistic optimization of economic and environmental benefits, aligning with the global trend of low-carbon development. Through this innovation, in industrial applications, the total lifespan cost of equipment can be reduced by 15%-20%, and carbon emissions reduced by 10%-15%.

This invention discloses a method, system, equipment, and medium for multidimensional data analysis and supply chain collaborative decision-making, belonging to the field of intelligent economic analysis and decision optimization technology for the supply chain. The method includes: collecting multidimensional raw data; preprocessing the multidimensional raw data through regression analysis; extracting latent components of independent and dependent variables; constructing low-dimensional feature representations; purifying the output value of the power grid company through a first-level algorithm; establishing the correction relationship between the output value of upstream and downstream enterprises and long-term cointegration and short-term errors; performing regression analysis on the purified independent and dependent variables; decomposing the output value of the power grid company; and generating supply chain collaborative adjustment decision-making suggestions. This invention provides precise support for supply chain collaborative adjustment decisions, overcoming the limitations of existing methods in terms of insufficient flexibility and insufficient consideration of the combined influence of multiple external factors when facing complex electricity demand, thus improving the accuracy and effectiveness of electricity analysis under volatile market conditions.

The invention discloses an artificial intelligence and mechanism model fused compressed air energy storage system rapid design method. The method comprises the following steps: firstly, constructing a thermodynamic model-economical efficiency analysis coupling model of the compressed air energy storage system capable of reflecting a physical mechanism, and establishing a multi-dimensional performance database; secondly, training an artificial intelligence agent model on the basis of a gradient boosting decision tree, introducing a Shapley Address Explanation (SHAP) method, quantitatively revealing the influence of system configuration parameters and operation conditions on system core efficiency indexes, and constructing a comprehensive efficiency explicit correlation; and finally, embedding the explicit correlation into a multi-objective optimization and objective empowerment decision process by taking the explicit correlation as a performance evaluation kernel to realize rapid optimization of key design parameters of the compressed air energy storage system. Compared with a traditional method depending on numerical simulation or a black box model, the method has the advantages that the calculation cost is remarkably reduced on the premise that physical reasonability and interpretability are guaranteed, and a design result with clear parameter contribution interpretation and application domain boundaries is output.

The present application relates to a method and algorithm system for determining the cleaning time of photovoltaic modules, which aims to solve the technical problems of insufficient accuracy and unclear physical mechanism of existing dust coverage evaluation methods. The method includes: first, obtaining four specific dust coverage physical parameters of the surface of the photovoltaic module: dust coverage average particle size (de), dust coverage thickness (d), module pollution rate (SR), and dust coverage visual color variation coefficient (k) obtained through a machine learning model; second, substituting the four parameters into a specific nonlinear logarithmic model to calculate the current power loss rate (PL); finally, converting the power loss rate (PL) into the economic cost of power generation loss, and comparing it with the preset cleaning cost to determine the optimal cleaning time. The present application can accurately quantify the impact of dust on the power generation of photovoltaic modules through a nonlinear logarithmic model based on specific multi-physical parameters, and scientifically determine the optimal cleaning time of photovoltaic power stations by combining economic analysis.

The application discloses a kind of based on mixed integer programming's light storage system optimization configuration method, it is related to light storage system optimization technical field, the present application includes the time series data and equipment parameters of project related as model input are comprehensively collected;Establish the mixed integer programming model with the shortest investment payback period as target, including equipment selection and operation strategy variable;Calling mathematical optimization solver calculates model, obtains optimal configuration and operation scheme;The solution result is parsed as specific equipment configuration list, operation strategy instruction and economic analysis report.The present application is globally optimized to photovoltaic capacity, energy storage model and quantity, inverter selection and hour-by-hour charging and discharging strategy by constructing and solving mixed integer programming model, can scientifically quantify the cost and benefit in the whole life cycle of system, automatically generate the configuration scheme and executable operation strategy table more optimal in technology and economy.

This application provides a three-dimensional simulation-driven method and apparatus for treating karst caves at the dam abutment. The method involves first acquiring multi-source geological survey data of the target karst cave on a server to determine its characteristics, spatial relationships, and original state parameters. A three-dimensional geological structure model including the dam body and foundation is then constructed. Next, a finite element analysis model coupling the dam foundation and dam body is built using experimental data and engineering specifications to simulate and output the baseline values ​​of safety evaluation indicators before treatment. Multiple elevation-boundary layered treatment schemes are designed, and the actual calculated values ​​of each scheme are obtained through simulation under multiple preset working conditions. Finally, through comparison of indicator improvement magnitudes, verification with engineering specifications, and economic analysis, the target treatment scheme that meets safety standards and has the optimal cost is determined. This application improves the scientific nature of karst cave treatment decisions, effectively ensures the stability of the dam foundation structure, and reduces overall construction costs.

The application discloses a coal-fired power plant flue gas multi-pollutant collaborative treatment and carbon capture virtual simulation experiment system and method, belonging to the technical field of virtual simulation experiment teaching. The system comprises three-dimensional visualization, coal combustion simulation, equipment selection simulation, process building, process operation debugging, CCUS economic benefit analysis and experiment evaluation modules. The equipment selection module supports multiple device parameter settings and calculations; the process building module supports drag-and-drop connection type process construction and automatic verification; the CCUS module realizes the deep integration of process simulation and economic analysis; and the innovative process exploration module supports user-defined new device types and code compilation. The application solves the technical problems of the existing simulation system, such as insufficient openness, weak multi-pollutant collaborative simulation capability and separation of process simulation and economic analysis, and realizes open exploration type full-process flue gas treatment virtual simulation experiment.