60 results about "Weather factor" patented technology

The invention discloses an enhanced GAN extreme scene generation method and system considering weather factors, and relates to the technical field of scene generation in new energy power system planning and operation, and the method comprises the steps: extracting key factors from multi-time-delay meteorological data, forming an extreme label, converting the extreme label into a generation condition, and achieving the output through two-stage confrontation generation, wherein a scarce sample is stably amplified by WGAN-GP, a joint curve is generated according to conditions, and related structures, climbing and power boundary constraints are synchronously embedded to ensure statistical and physical consistency. According to the method, the authenticity of the distribution tail, the cross-variable correlation and the time structure can be considered when the sample is scarce. Extreme situation deduction of a novel power system can be supported while extreme situation coverage and credibility are improved, and an existing new energy scene analysis and planning process is integrated.

An integrated energy system short-term load prediction method based on an improved multi-task model includes the steps that in the input stage, the MIC is adopted to analyze the correlation degree of multi-element loads and weather factors, and STL is used for decomposing a load sequence to construct a component data set; in the modeling stage, the CNN is used as a feature extraction network, the spatial coupling relation of an input sequence is directly learned, the general representation of the multi-element load is learned by applying a hierarchical progressive routing strategy, and specific parameter information of different tasks is separated; in the output stage, modeling is conducted on time sequence characteristics through combination of LSTM, multi-element load prediction is achieved, aiming at the complex nonlinear relation between loads, a CPLE joint prediction model is established through combination of the characteristics of CNN and LSTM networks and a PLE multi-task learning method, and while multiple networks are adopted to learn the space-time coupling characteristics between the multi-element loads, the multi-element load prediction efficiency is improved. And different load specific knowledge is highlighted by using a progressive routing mode.

The invention discloses a power transmission line icing prediction method, system and device based on satellite data assimilation and a medium, and relates to the technical field of ice and snow monitoring, and the method comprises the steps: obtaining satellite microwave radiance observation data, fusing the observation data and a numerical mode background field through data assimilation, generating grid meteorological data, and carrying out the prediction of the icing of a power transmission line. The method comprises the following steps: processing gridding meteorological data by using a spatial-temporal feature joint modeling technology, reconstructing meteorological data of continuous time steps into a spatial-temporal coupled four-dimensional tensor, synchronously extracting spatial-temporal dimension dynamic evolution features through a three-dimensional convolution kernel, and fusing historical states and current features based on a gating mechanism to obtain a spatial-temporal feature fusion model; and outputting a spatial distribution prediction result of the icing thickness of the power transmission corridor. According to the method, the high-precision meteorological field is obtained, the time-space dynamic characteristics of icing evolution are synchronously extracted, the key meteorological factors are screened in combination with an improved gating mechanism and attention, and accurate closed-loop simulation of power transmission corridor icing is realized based on iterative prediction of physical constraints, so that the accuracy and reliability of icing early warning are remarkably improved.

The invention discloses an urban atmospheric pollution real-time monitoring method and system. The method comprises the following steps: acquiring pollutant concentration, weather and geographic position data through multi-source monitoring equipment; performing data fusion by adopting space-time Kriging interpolation and wavelet threshold denoising to generate a high-quality urban pollution distribution initial field; a machine learning model of an encoder-decoder structure is used for prediction, an encoder is a convolutional long-short term memory network, a decoder is a dynamic graph convolutional network fused with meteorological factors, and a dynamic pollution situation map is generated; polluted area identification is carried out based on a wind field streamline, and accurate tracing is carried out through combination of reverse simulation of a Lagrange particle diffusion model and a control variable method. The whole process optimization of pollution monitoring from data fusion, accurate prediction to quantitative traceability is realized, and the accuracy and timeliness of urban atmospheric pollution supervision are remarkably improved.

The invention relates to a digital intelligent trajectory prediction method and system based on logistics transportation order tracking. The method comprises the steps of collecting multi-source transportation data including vehicle GPS data, AI telephone interaction data, ETC passing record data and freight station transfer operation node data; performing space-time alignment, data cleaning and map matching based on road network information on the multi-source transportation data; utilizing the processed multi-source data to generate a continuous digital intelligent track through an interpolation algorithm and a path deduction method; calculating the latest predicted position of the vehicle through a prediction algorithm model based on the digital intelligent track in combination with real-time traffic information and a historical driving mode; residual paths, real-time road conditions, weather factors and driver behavior modes are comprehensively considered, and the predicted arrival time is calculated through a dynamic ETA model. According to the invention, the GPS signal blind area problem is effectively solved, the whole-course blind-area-free tracking and high-precision arrival time prediction are realized, and the transparency and intelligent management level of logistics transportation are greatly improved.

The short-term load forecasting method based on SARIMA-random forest combination model comprises the following steps: grouping the original load data by using a sliding window, decomposing the to-be-tested week-before-next day data set of each group to obtain a trend item, a seasonal item and a residual item; establishing a SARIMA model, predicting the trend item to obtain a preliminary prediction result and a residual; clustering weather factors to obtain similar days, grouping to construct a weather-residual data set and establishing a random forest regression model, learning the influence of the weather factors on the residual, and selecting model parameters by using a grid search method; combining the prediction results of the model, and comparing the influence of weather clustering and residual training on the load prediction accuracy. The method can accurately predict the next day load under the condition that the historical load and weather factors of the to-be-tested day are known, and improves the prediction accuracy.

This invention relates to a JP complete power distribution cabinet, belonging to the technical field of power distribution cabinets. It includes a housing with a pre-reserved cavity on its inner side. A temperature control platform is mounted on the inner side of the cavity. Several mounting brackets are arranged on one side of the inner side of the temperature control platform. Several temperature-conducting plates are arranged on the side of the temperature control platform closest to the inner side of the cavity. The temperature-conducting plates are wavy and composed of several semi-circular rings. This invention solves the problem that cooling efficiency is easily affected by weather factors, and that while vents allow air to pass through, liquid and contaminant particles can easily enter with the airflow. In this invention, by using a temperature control platform, the wavy shape of the temperature-conducting plates increases their surface area, thereby increasing the efficiency of absorbing heat energy inside the cavity and the heat release efficiency inside the solution cavity. The calcium chloride solution inside the friction wheel has the characteristics of high specific heat capacity and low freezing point.

The application discloses a complex environment water level monitoring system and method based on heterogeneous light field cooperation, which is characterized in that: a water gauge image is segmented from a water gauge point cloud and a joint external parameter; the water gauge image is further segmented after image enhancement, and the tilted water gauge is corrected; the intensity of the water gauge point cloud is accumulated, and the water level line is obtained through the maximum gradient method; the corrected water gauge image is detected by using a target detection algorithm to detect digital characters, the character recognition algorithm is used to perform OCR recognition on the detected digital characters, and the water level value is calculated according to the digital characters, the water level line and the water gauge image. Through the combination of laser radar and visible light field, the reflection characteristics of different materials are utilized, so that the water level in the complex environment of a river channel, a reservoir and a coast can be monitored in real time. The interference of floating objects and weather factors on water level detection is effectively avoided, and the accuracy and robustness of water level monitoring are significantly improved.

The application discloses a rain weather multi-view feedforward Gaussian reconstruction method and system based on weather factor gating, and the method comprises the following steps: acquiring rain weather context images under different views and camera parameters thereof; inputting the rain weather context images into a weather factor decomposition network to generate predicted weather factors; constructing a matching reliability graph for representing the corresponding reliability degree across views according to the predicted weather factors; extracting multi-scale features of the rain weather context images; generating gated features according to the multi-scale features, the matching reliability graph and reliability gating; performing multi-view aggregation based on the gated features to generate fusion representation; inputting the fusion representation into a three-dimensional reconstruction network for feedforward prediction to obtain a three-dimensional Gaussian set; inputting the three-dimensional Gaussian set into a differentiable renderer to render a clean predicted image of a target view in combination with target view camera parameters; acquiring clean context images of multiple views to construct rain weather training samples; and constructing a loss function to train the weather factor decomposition network and the three-dimensional reconstruction network.

A refueling prediction mode in a microgrid power system may include inputting historical load and weather date of the microgrid power system to a forecasting block and determining forecasted site load and weather factors for the microgrid power system. The forecasted site load and weather factors may be used along with fuel efficiency curves and asset fuel levels for power assets of the microgrid power system, along with other information, to determine an asset dispatch schedule and a refueling timeline for the power assets. Asset dispatch commands based on the asset dispatch schedule and an actual site load may be output to the power assets to meet the load demand on the microgrid power system. A sustained reliability mode may use the information plus real-time fuel costs for the power assets to determine an asset dispatch schedule for longest microgrid sustenance for the power assets.

This invention provides a method, system, computer equipment, and storage medium for predicting passenger flow at rail transit stations. The method extracts directed origin-destination (OD) pairs from the entry and exit records of an automated fare collection system using a fully directed network; determines the travel time for non-transfer and single-transfer journeys; determines the real-time location of passengers based on the OD pairs and travel time; determines the passenger flow at each station within a target time period based on the passengers' real-time locations; acquires and processes weather factors; constructs a CNN-BiLSTM-Attention passenger flow prediction model; and uses the passenger flow at each station within the target time period and weather factors as input variables to predict the passenger flow at each station using the CNN-BiLSTM-Attention passenger flow prediction model. This invention considers the influence of weather factors, time dependence, and spatial characteristics, enhancing the focus on key features and improving the accuracy of station passenger flow prediction.

The invention belongs to the technical field of power systems, and relates to a reliability evaluation method and system for an extreme meteorological new energy high-permeability power system. The method comprises the following steps: judging extreme meteorology, and constructing a new energy output and meteorological factor coupling model under the extreme meteorology; establishing a system operation model considering extreme meteorology, and obtaining system operation state parameters and power distribution parameters; calculating a short-time index reliability score and an ultra-short-time index reliability score of the system under each extreme weather and different time length scales; and fusing the reliability scores to obtain a comprehensive reliability score. The method can accurately describe the instantaneous impact and short-term influence of the extreme weather on the operation of the new energy high-permeability power system, and realizes the quantitative analysis of the reliability of the system; the reliability indexes of the system are divided into a short-time type and an ultra-short-time type, the power shortage risks under different time scales can be captured respectively, and more refined and dynamic reliability evaluation is provided for system operation under extreme weather.

The invention discloses a wind measurement data correction method based on flow field simulation, and the method comprises the following steps: obtaining the current topographic data and historical target data of a target mountainous area; identifying key weather factors according to historical target data; constructing a quantitative relation model of the key weather factors and the surface form change; obtaining a topographic data prediction value of the target mountainous area; constructing a prediction digital elevation model according to the topographic data prediction value; obtaining corrected wind speed prediction data; comparing the corrected wind speed prediction data with the actually measured wind speed data of the field anemometer tower, and calculating the deviation; and constructing a space correction function based on the deviation, and applying the correction function to subsequent wind resource evaluation or fan layout optimization to realize dynamic correction of the wind measurement data. The fan flow field prediction method solves the problems that fan flow field prediction precision has a large error and the prediction result is not high in accuracy.

The application discloses a vehicle type classification detection method based on a single geomagnetic sensor, and mainly solves the problems of delay of acquired vehicle type classification information caused by complex existing vehicle type classification detection algorithm, and precision of acquired vehicle type information caused by that data collection of the sensor is easily affected by environmental factors. The application places a geomagnetic sensor on a lane line on one side of a lane, adopts the single geomagnetic sensor to collect a magnetic field disturbance value of a vehicle, extracts a magnetic field feature in the magnetic field disturbance value of the vehicle, generates a SoftMax function model by using the screened effective magnetic field feature, and realizes vehicle type judgment of a small vehicle, a medium vehicle and a large vehicle. The vehicle type classification detection method based on the single geomagnetic sensor used by the application has low calculation complexity, reduces calculation pressure of the geomagnetic sensor, is convenient to install, has low cost, is not easily affected by weather factors, and can be used for road intelligentization.

The invention discloses an air supply system of a tobacco warehouse, and relates to the technical field of air conditioning of the tobacco warehouse, the air supply system comprises a shell assembly, two sets of air exhaust pipelines are arranged at the bottom of the front face of the shell assembly, and electromagnetic valves are arranged on the two sets of air exhaust pipelines; the output ends of the two sets of air suction pipelines are jointly connected with negative pressure suction equipment through a three-way pipe, two sets of power assemblies are arranged on the top and in the shell assembly, cleaning mechanisms are arranged at the bottoms of the outer sides of the power assemblies, and filtering mechanisms are arranged on the outer sides of the power assemblies. Two groups of shielding mechanisms are arranged on the inner side of the filtering mechanism; and the power assembly drives the adjacent shielding mechanism, so that the adjacent shielding mechanism locally shields the filtering mechanism. In the cleaning process, equipment does not need to be shut down, the automation degree is high, the cleaning process is not affected by weather factors while manpower is saved, and higher cleaning efficiency is achieved while manpower is saved.

The invention relates to a photovoltaic power station intelligent control method based on a large model and deep learning, which belongs to the field of photovoltaic solar energy intelligent control, and is characterized in that through crawling news policies and 9km * 9km grid weather information, meteorological policy interpretation and influence analysis based on the large model, and missing value prediction and complementation of weather data, the intelligent control of a photovoltaic power station is realized. The accurate acquisition of the weather data is realized; meanwhile, by means of an illumination intensity prediction method for predicting and complementing unknown data through known data and a sunrise and sunset information and sunshine information coding method, weather factors can be better analyzed and controlled, and accurate photovoltaic solar panel power generation control is achieved; besides, according to a weather time sequence prediction method and an intelligent decision-making method based on deep learning, a model is learned in an unsupervised manner by using historical data, and intelligent decision-making is carried out by using a cost function, so that intelligent control of the photovoltaic solar panel is realized; and finally, a result display and alarm method can accurately store and display a predicted value, and early warning is carried out according to an alarm condition.

The invention discloses a starry sky appreciation suitability forecasting method. The method comprises the following steps: determining a forecasting area, a forecasting time period and a forecasting time number which need to be subjected to starry sky appreciation suitability forecasting; determining a night time period corresponding to each regional grid; determining a forecasting time point for each area grid according to the forecasting time period, the forecasting time and the determined night time period; obtaining a starry sky viewing suitability evaluation value of each regional grid at each forecasting time point through a starry sky viewing suitability forecasting algorithm; and according to the star sky viewing suitability evaluation value, completing star sky viewing suitability forecasting for the forecasting area day by day and forecasting time by day. According to the method, the influence of the quantity index, the quality index, the disastrous weather factor and the hotspot astronomical image addition is integrated, the starry sky viewing suitability evaluation value for reflecting the starry sky viewing suitability level is given, the completed forecasting result is objective and accurate, and the method is suitable for popularization.

The embodiment of the invention discloses a fault cause detection method and device, electronic equipment and a readable storage medium. According to the embodiment of the invention, the to-be-detected charging device is determined according to the operation data of each charging device, and the meteorological information of the position of the to-be-detected charging device is acquired, so that the probability of the to-be-detected charging device is predicted according to the operation data of the to-be-detected charging device, the meteorological information of the position of the to-be-detected charging device and the pre-trained probability prediction model. And obtaining the probability that the to-be-detected charging equipment is influenced by extreme weather to generate a fault. In the embodiment of the invention, whether the factor causing the fault of the to-be-detected charging equipment is the weather factor or not can be judged according to the operation condition of the to-be-detected charging equipment having the fault and the weather condition, so that the fault charging equipment can be maintained in a more targeted manner subsequently, and the personnel waste is reduced.

The utility model relates to high altitude operation equipment technical field, and disclose a kind of welding platform with telescopic canopy suitable for high altitude welding, including lifting platform and the operating frame installed in the top of lifting platform, further include: canopy cloth is set to the top of operating frame one side, the side of operating frame is provided with the support member for supporting or storing canopy cloth, support member includes movable rod and support frame, the side of movable rod is rotatably connected with operating frame by pivot. By the setting of support member, the outward thrust generated by the compressed gas of first gas spring is utilized, the movable rod can be easily lifted up, the support frame is pushed up synchronously during the lifting of movable rod, and then the canopy cloth is unfolded smoothly, the unfolded canopy cloth can effectively block sunlight and rain for the working area, which improves the working environment of workers, avoids the interference of weather factors on construction, and significantly improves the practical value and use convenience of canopy cloth.

The invention relates to the field of gas water heaters, in particular to a gas water heater temperature and humidity self-adaption method which comprises the steps that the environment temperature and the environment humidity of a gas water heater, the length of a hot water pipeline, the weather forecast temperature of the area where the gas water heater is located and the water outlet speed of the hot water pipeline are obtained; determining a temperature compensation value according to the environment temperature, the environment humidity, the length, the weather forecast temperature and the water outlet speed; and the preset outlet water temperature of the gas water heater is adjusted according to the temperature compensation value. Therefore, multiple influence factors of the installation environment dimension (the environment temperature and the environment humidity of the gas water heater, the length of the hot water pipeline and the weather forecast temperature of the area where the gas water heater is located) and the dynamic water use scene dimension (the water outlet speed of the hot water pipeline) are comprehensively considered, and the temperature compensation value is obtained through multi-parameter cooperative operation; and therefore, the water outlet temperature can be accurately adjusted. By means of the design, it is avoided that the water outlet temperature is too cold or too hot due to weather factors, and the user experience is improved.

The application discloses a kind of over-ocean fishery safety early warning method, system and medium based on big data, by obtaining and analyzing the marine historical weather data of multiple marine fishing sub-regions and the marine environmental information of current region, obtain current warning information, determine the warning level of warning information, generate different navigation correction information for different warning levels, according to correction information, obtain suitable fishing route, thereby effectively improve fishing yield and economic efficiency of marine fishery.In addition, by analyzing the safe marine sub-region in the fishing area, a suitable return route is obtained, which can effectively reduce the economic loss caused by abnormal weather factors in marine production.

The water conservancy gate convenient to clean particularly relates to the technical field of gate devices and comprises a dam body, a gate frame is fixedly connected to the inner surface of the dam body, a gate plate is slidably connected to the inner wall of the gate frame, a cleaning assembly is arranged at the top of the dam body, and a scraping assembly is arranged on the front face of the gate frame. The cleaning assembly comprises two fixing bases, and the bottoms of the two fixing bases are fixedly connected with the top of the dam body. According to the water conservancy gate convenient to clean, the cleaning assembly is arranged, specifically, the double-shaft motor is started firstly to drive the four collecting frames to rotate to fish garbage on the water surface, workers do not need to fish the garbage manually, the cleaning work can be completed with less time, and the working efficiency is improved. Garbage can be quickly and effectively cleaned, the garbage cleaning efficiency is improved, and in addition, under the severe weather condition, the fishing work can be normally carried out without being influenced by environment and weather factors.

The application discloses a weather and icing relationship monitoring method based on icing mechanism analysis, and particularly relates to the field of weather and icing relationship monitoring, and comprises the following steps: constructing a factor combination vector sequence containing disturbance amplitude characteristics and icing response synchronous relationship; generating a composite input structure for a dynamic state recognition and determination process by performing weather factor time sequence calculation, disturbance change rate extraction and icing rate synchronous mapping operation, and realizing a disturbance dominant sensitivity state perception data organization mechanism; the application constructs a factor combination vector based on the synchronous mapping mechanism between the disturbance change rate and the icing response, and realizes model boundary self-adaptive adjustment in combination with a nonlinear rate evolution structure, so as to dynamically reflect the fusion trend of state continuous evolution and sudden transition, thereby solving the problem of model response lag in the physical transition of the icing state under complex weather conditions.

The present application belongs to the technical field of dispatching allocation, and particularly relates to a wet runway and contaminated runway downwind boundary and influence calculation method based on efficiency and operation cost, aiming to solve the problem that the prior art lacks technical methods for determining and calculating the downwind take-off and landing operation demand, operation boundary and operation reduction influence of the wet runway and contaminated runway of an airport, resulting in low weather factor disturbance resistance of the airport control operation, and high safety risk of the airport frequently switching the runway operation direction. The method comprises the following steps: collecting historical operation related data of the airport as input data; calculating the downwind take-off and landing operation demand of the wet runway and contaminated runway of the airport; determining the downwind take-off and landing operation boundary of the wet runway and contaminated runway of the airport; and obtaining the average daily wet runway and contaminated runway downwind take-off performance reduction of the airport based on the operation boundary and hourly capacity. The present application fills the gap in the prior art, improves the weather factor disturbance resistance of the airport control operation, and maximizes the overall operation safety level of the airport.

The invention discloses a method and a system for monitoring and collecting icing-prone temperature special points of a road surface based on a thermal spectrum map and XGBoost. At present, position data of easy freezing of a road surface cannot be fed back in time according to temperature changes, special jump points and hysteresis exist, and an existing monitoring method cannot be matched with dynamic changes of the freezing state of the road surface. According to the road surface icing temperature special point monitoring and collecting method, a three-dimensional data set combining weather, a road surface and a position is obtained to serve as multi-source data collection, and an XGBoost temperature prediction model combining multi-source data and quantitative weather factors is established; based on an XGBoost temperature prediction model, an improved Z-score algorithm is combined with thermal spectrum map spatial characteristics to determine accurate positioning, monitoring and real-time early warning processes of road surface freezing-prone temperature special points; according to the road surface icing temperature special point monitoring and collecting method based on the thermal spectrum map and the XGBoost, the quantitative accurate process capable of standardizing the system to determine the road surface icing temperature special point is provided.

The invention relates to the technical field of agricultural intelligence, discloses an agricultural machinery operation plan decision-making method based on weather forecast information, and aims to solve the problem of agricultural time delay caused by influence of weather factors during agricultural machinery scheduling operation in the prior art. In combination with the information of each machine and tool in the machine and tool cluster and the information of each field piece, the weather suitability of each machine and tool in each working time period of each field piece is calculated according to the weather information, the most suitable operation time period of each machine and tool in each field piece is distinguished, and the weather condition is integrated into the intelligent agricultural operation. The calculated weather suitability degree is input into the agricultural machinery scheduling model to solve a scheduling scheme when the machine cluster meets the maximum working efficiency, by adopting the technical scheme, scheduling of the machine cluster is achieved according to the weather condition, the influence of weather factors on agricultural machinery operation is reduced, and more efficient and faster agricultural machinery operation is achieved.

The application belongs to the technical field of construction management, and provides a highway engineering operation compliance analysis method based on construction process decomposition, which comprises the following steps: constructing a process relationship network based on construction process decomposition; extracting a preceding missing process of a current process, and obtaining an importance indicator value, a missing quantity of the preceding missing process, and an importance indicator value of the current process; establishing a basic risk analysis model according to the importance indicator value and the quantity of the preceding missing process, and generating a compliance basic risk probability; obtaining weather forecast data of a construction area, and generating a weather factor influence factor; combining the basic risk probability, the weather influence factor and the importance indicator value of the current process to establish a comprehensive risk analysis model, and obtaining a final compliance risk probability; and analyzing operation compliance according to the final compliance risk probability; and the application realizes comprehensive quantitative evaluation of highway engineering operation compliance risk by fusing missing process importance, missing quantity, weather influence and current process importance.

The utility model discloses a photovoltaic module support device capable of being easily mounted and dismounted for an electrochemical energy storage container. The photovoltaic module support device mainly comprises a fixed cross rod, a vertical telescopic rod and a fixed support, the fixed cross rod comprises a front fixed cross rod and a rear fixed cross rod which are arranged in parallel; fixing supports are arranged at the corresponding positions of the front fixing transverse rod and the rear fixing transverse rod respectively, and one end of the vertical telescopic rod is connected to the front fixing transverse rod through the fixing supports. The device is mainly used for connecting an electrochemical energy storage container and a finished photovoltaic module, and is convenient to mount and dismount by using a finished fixing piece. The sun-shading and heat-insulating effects of the electrochemical energy storage container can be improved, and the influence of environment temperature, weather factors and the like on the efficiency of the energy storage container is reduced. In conclusion, the utility model has the characteristics of simple structure, easiness in construction and the like, and is suitable for wide popularization and use.

The invention discloses a mountain area power distribution network voltage dynamic regulation and energy-saving operation method, and relates to the technical field of power distribution networks, the method adopts a double-frequency impedance detection mode, extracts low-frequency and high-frequency impedance values from preprocessed historical impedance data, calculates a difference value, accurately captures line impedance micro-change caused by mountain area meteorological change, and improves the power distribution network voltage dynamic regulation and energy-saving operation efficiency. The problem that inherent impedance and meteorological influence impedance cannot be distinguished through traditional single-frequency detection is solved. The method comprises the following steps: constructing a dual-frequency impedance difference-meteorological factor coupling model, associating multi-source data through a timestamp to form a data set, establishing a mapping relation between input and a voltage disturbance value through feature extraction and coupling fusion, realizing advanced prediction of voltage disturbance in the next 15 minutes, and reserving sufficient response time for adjustment operation; a differential dynamic adjustment mechanism is designed, inductive load grading input and reactive compensation grouping control are executed according to the positive and negative characteristics of a predicted value, accurate adjustment is achieved in combination with real-time voltage monitoring, and over-adjustment or insufficient adjustment is avoided.

The application discloses a weather-driven new energy power generation power prediction method, which comprises a new energy power generation power-weather factor correlation analysis method, a new energy power generation power core weather factor optimization identification method and a weather-driven new energy power generation power prediction method. The power generation power prediction model of the application has high prediction accuracy, the method considers the power generation characteristic differences caused by geographical and weather factors, and has more advantages compared with traditional prediction methods; the prediction efficiency is high, the dimension reduction measures based on weather correlation analysis can optimize the selection of key weather factors as input variables, reduce the complexity of the prediction model and improve the prediction efficiency; the method can be applied to few-data new energy stations, in view of the problem that some new energy stations lack historical power generation data, the spatial correlation and weather correlation analysis are comprehensively considered to supplement the data source of the prediction model, and the prediction accuracy of the power generation power of the few-data new energy station is improved. Therefore, the method is suitable for popularization and application.