2217results about How to "Improve power generation efficiency" patented technology

The invention relates to the technical field of thermal power plant parameter regulation and control, in particular to an intelligent temperature and pressure regulation method and system for a thermal power plant, and the method comprises the following steps: collecting temperature, pressure and flow data based on heat transfer and flow channels among a boiler, a steam turbine, a condenser and heat exchanger equipment in the thermal power plant; constructing a network structure representing interaction between devices, evaluating heat exchange characteristics of nodes, and constructing heat flow path structure matrix information; according to the method, the complex interaction among the boiler, the steam turbine, the condenser and the heat exchanger equipment is accurately quantified by constructing the heat flow path network structure among the equipment and evaluating the heat exchange characteristics of the nodes. Thermal inertia feedback matrix information is introduced, and transient changes of temperature and pressure are monitored in real time, so that delay and inertia effects in heat transfer and fluid flowing between equipment can be more accurately captured, and the response speed and precision to different loads and working conditions are improved.

The invention relates to the technical field of photovoltaic panel cleanliness detection, in particular to a photovoltaic panel cleanliness detection method which comprises the steps of data acquisition, image preprocessing, pollution feature extraction, cleanliness index calculation, cleanliness judgment, data output and result recording and feedback. According to the invention, pollution data is acquired through imaging equipment, and adaptive filtering and morphological analysis are combined, so that precise pollution feature extraction, detection precision improvement and system real-time calculation of a cleanliness index are realized, pollution conditions are fed back through a cloud platform or an Internet of Things interface, and the power generation efficiency of a photovoltaic panel is ensured. The system can also automatically trigger a cleaning device and control the cleaning process according to a cleanliness threshold value, full-automatic management is achieved, the labor burden is relieved, in addition, a machine learning algorithm automatically adjusts the threshold value according to environment monitoring data and seasonal changes, and parallel detection further optimizes the efficiency, shortens the detection time, improves the operation and maintenance effect and prolongs the service life of the photovoltaic panel.

The invention provides a wind turbine generator array wake flow management method and system for Doppler laser wind measurement, and relates to the technical field of laser, and the method comprises the steps: collecting the real-time wind speed data, wind direction data and turbulence intensity data of each generator in the front and back direction through deploying a Doppler laser radar in a wind turbine generator array; establishing a wake flow influence model containing a wake flow influence coefficient, an attenuation coefficient and a diffusion coefficient based on the data, and calculating to obtain a wake flow influence range, loss power and a recovery distance; according to the method, the wind turbine generator array is cooperatively controlled, and the power generation efficiency of the wind turbine generator array is optimized by adjusting the yaw angle or the pitch angle of the upstream unit and the rotating speed of each unit. The wind speed data acquisition precision of the wind field is improved, the wake flow influence evaluation accuracy is enhanced, and the overall power generation efficiency of the wind field is remarkably improved.

The invention is suitable for the field of photovoltaic technology, and provides a battery assembly and a photovoltaic system, and the battery assembly comprises a plurality of battery pieces, each battery piece comprises a chamfer edge and a straight edge which are parallel to each other, and the plurality of battery pieces are partially overlapped in a first direction to form a battery string. The plurality of battery strings are partially overlapped along the second direction to define a plurality of closed areas, the plurality of battery pieces are partially overlapped to eliminate the piece spacing, and the plurality of battery strings are partially overlapped to define a plurality of closed areas to reduce the string spacing; according to the photovoltaic module, more battery pieces can be arranged in a limited area, the utilization rate of the space area and the power generation power of the module are improved, in addition, due to the formation of the closed area, the light leakage condition of the battery module can be improved, and the power generation efficiency of the photovoltaic module can be improved by utilizing light rays in the intervals of the battery strings; the photovoltaic module is better in overall attractiveness, and the production efficiency can be improved.

The invention relates to the technical field of data processing, and discloses an operation mode switching control method and device for an offshore wind turbine generator. The method comprises the following steps: carrying out model classification on historical operation data of a unit to obtain operation mode classification data and a characteristic parameter library; performing reinforcement learning analysis on the current state evaluation data and the short-term prediction data of the unit to obtain a target operation mode; performing fuzzy control processing on the target operation mode to obtain a mode switching strategy and a parameter adjustment sequence; performing multi-objective optimization and cooperative control analysis on the mode switching strategy and the parameter adjustment sequence to obtain accurate control signals of each actuator in the target offshore wind turbine generator; and generating an operation mode switching control strategy according to the accurate control signal of each actuator, and performing mode switching control on the target offshore wind turbine generator through the mode switching control strategy. According to the invention, the efficiency and accuracy of the operation mode switching control of the offshore wind turbine generator are improved.

The invention provides a photovoltaic power station design system and method based on ecological collaborative optimization, and relates to the technical field of data processing. The system comprises an initial configuration module which is used for generating an initial layout structure of a photovoltaic module, performing energy-saving and consumption-reducing calculation and economic analysis according to generating capacity data, and obtaining initial energy-saving and consumption-reducing data and initial economic analysis data; the secondary optimization module is used for optimizing the parameters of the photovoltaic module based on the economical efficiency analysis data and determining energy-saving and consumption-reducing data and economical efficiency analysis data through the generating capacity optimization data; the ecological evaluation module is used for determining ecological benefit data of the photovoltaic power station according to the ecological influence parameters; and the collaborative optimization module is used for setting a power generation income weight and an ecological benefit weight so as to optimize the photovoltaic module layout structure and generate a photovoltaic power station design scheme based on ecological collaborative optimization. The method is used for realizing collaborative optimization of power generation benefits and ecological benefits of the photovoltaic power station, so that the power station gives consideration to ecological protection while improving the power generation efficiency.

The invention relates to the technical field of intelligent control and optimization of a photovoltaic power generation system, and discloses a self-adaptive photovoltaic module inclination angle adjusting method and system based on environmental conditions, and the method comprises the steps: obtaining short-term weather forecast data through a meteorological data interface, analyzing the weather forecast data, and predicting the environmental change in several hours in the future; monitoring pollution data of the surface of the photovoltaic module in real time through a sensor, and judging whether the pollution degree affects the power generation efficiency or not; according to the prediction result and the pollution degree, the inclination angle of the photovoltaic module is dynamically adjusted, the power generation efficiency under the upcoming illumination condition is optimized, the inclination angle of the photovoltaic module is dynamically adjusted in combination with short-term weather forecast data obtained by the meteorological data interface, and the power generation efficiency of the photovoltaic system under the complex environment is remarkably improved. The system can quickly respond to environmental changes, and efficiency loss caused by adjustment lag is avoided. And multi-factor collaborative optimization is realized, and the maximum power generation efficiency of the photovoltaic system under various conditions is ensured.

The invention relates to the technical field of photovoltaic power generation power prediction, in particular to a photovoltaic power generation power high-precision prediction method and system. According to the technical scheme, the method comprises the following steps: data acquisition and preprocessing: historical photovoltaic power generation power data are widely collected, the time span covers at least one year in the past so as to obtain power generation power change information under different seasons, weather conditions and time periods, and meanwhile, meteorological data corresponding to the power generation power change information are collected; and cleaning the collected data, and removing missing values through data integrity check. The power generation efficiency and economy are improved, the operation and maintenance plan can be optimized, and the energy storage utilization efficiency is improved; the power grid stability and reliability are enhanced, scheduling is assisted, resource configuration is optimized, power market operation is greatly improved, support is provided for transaction decision making, renewable energy consumption is promoted, the system adaptability and the intelligent level are improved, real-time tracking and updating can be achieved, and intelligent management of a power station is assisted.

The invention discloses a tunnel type underground gas storage combined with temperature control, belongs to the technical field of compressed air energy storage, and can solve the problems that the cost of temperature control measures in an existing gas storage is high, and maintenance is difficult. The gas storage comprises a lining; the sealing structure covers the inner wall surface of the lining; the breathable heat conduction structure sleeves the inner side of the sealing structure; an annular cavity is formed between the sealing structure and the breathable heat conduction structure; the annular partition pieces are sequentially arranged in the annular cavity in the axial direction of the gas storage and used for dividing the annular cavity into a first temperature control area and other temperature control areas which are sequentially arranged, and the simulated operation temperature of each temperature control area is sequentially increased from the first temperature control area; a water storage bag is arranged in each temperature control area; and the water circulation structure is arranged on the outer side of the gas storage, communicates with each water storage bag and is used for forming a circulation water path with the water storage bags. The method is used for temperature control of the tunnel type underground gas storage.

The invention discloses a floating type photovoltaic platform device capable of actively adjusting the angle of a photovoltaic module, which comprises floating bodies, a photovoltaic mechanism, a central control system, connecting floating bodies and gravity anchors, and is characterized in that the photovoltaic mechanism is mounted on the floating bodies, the floating bodies are connected with the gravity anchors, the gravity anchors are placed in a water area, the plurality of floating bodies are connected through the connecting floating bodies, and the central control system is connected with the central control system. The central control system is installed on the connecting floating body, the central control system is respectively connected with the floating body and the photovoltaic mechanism, the floating body comprises an adjusting air cushion and a supporting floating body, the adjusting air cushion is arranged on the supporting floating body, the photovoltaic mechanism is arranged on the adjusting air cushion, and the supporting floating body is respectively connected with the connecting floating body and the gravity anchor. The sun position and the illumination intensity are monitored in real time through the central control system, the angle of the photovoltaic mechanism is actively adjusted through the adjusting air cushion, it is ensured that the photovoltaic assembly can receive sunlight at the optimal angle all the time, and therefore the photoelectric conversion efficiency is remarkably improved.

The invention discloses a steel structure support for photovoltaic power generation, relates to the field of photovoltaic power generation supports, and solves the problem that the surface of a photovoltaic panel is easy to damage and the service life is affected due to the fact that an existing steel structure support for photovoltaic power generation is difficult to turn over and fold at multiple angles during use. Comprising a base, a supporting mechanism, an adjusting mechanism, a cleaning mechanism and two sets of photovoltaic panels, the base is rotationally connected with a first electric telescopic rod, the supporting mechanism comprises a guide frame, a connecting plate and a guide piece, the adjusting mechanism comprises a mounting ring and a second electric telescopic rod, and the cleaning mechanism comprises a cleaning roller. A first electric telescopic rod can conveniently drive a connecting plate to ascend and descend, so that the photovoltaic panel is rotated, overturned and contracted, the angle of a guide frame is adjusted through a second electric telescopic rod, the light receiving efficiency is improved, meanwhile, a cleaning roller is linked to clean the surface of the photovoltaic panel, and the cleaning roller is self-cleaned through the connecting plate; and the service life of the photovoltaic panel is prolonged.

The invention discloses an intelligent photovoltaic power generation system control method, and relates to the technical field of photovoltaic power generation management, and the method comprises the steps: collecting data in real time based on a sensor in a photovoltaic system, employing an edge computing technology, and transmitting important information to a cloud end; the future illumination change is predicted, so that the output of the inverter is adjusted in advance; based on an energy management system, the power demand and the generating capacity are monitored in real time, and interaction of photovoltaic power generation, energy storage and a power grid is coordinated; acquiring historical data, identifying a fault mode, and performing fault detection and prediction maintenance; based on the AR technology, the system state is displayed in real time. According to the method, environment data such as illumination, temperature and wind speed are collected in real time through a sensor, the edge computing technology is combined, the system state and the abnormal condition can be rapidly detected, the power generation efficiency is improved, illumination prediction based on the deep learning algorithm can dynamically adjust the working point of the inverter, the power generation capacity of the photovoltaic system is improved to the maximum extent, and the power generation efficiency is improved. And the method adapts to rapidly changing environmental conditions.

The invention discloses a digital twin-driven photovoltaic module monitoring and self-purification system, belongs to the technical field of photovoltaic module cleaning, and realizes intelligent management and maintenance of a photovoltaic system through mutual cooperation of a sensing layer, an information capturing layer, an information transfer layer, an intelligent analysis layer, a decision support layer and an interactive experience layer. The sensing layer deploys various sensors to collect key data of the photovoltaic module; the information capturing layer transmits the data to a back-end processing system in real time; the information transfer layer ensures efficient transmission of data in the system; the intelligent analysis layer predicts a maintenance demand by using a machine learning algorithm, realizes predictive maintenance, and maintains the optimal working state of the component through an intelligent cleaning mechanism; the decision support layer provides decision support based on data analysis for an operator of the photovoltaic power station, and optimizes a maintenance plan and a productivity plan; and the interactive experience layer provides a visual management interface, so that the component state can be remotely monitored conveniently.

The invention provides a floating attitude adjustment and optimization system for a floating type offshore wind power equipment group, and relates to the technical field of offshore wind power equipment, and the system comprises a sensing monitoring module which collects an equipment operation attitude parameter set and a marine environment data set in real time; the information is transmitted to the central control unit through the data transmission module, and is analyzed and processed by the equipment attitude prediction module to generate equipment attitude prediction information; the adjustment strategy generation module obtains a target attitude adjustment strategy based on the equipment attitude prediction information and the construction information of the buoyancy attitude adjustment device; the adjustment parameter generation module obtains attitude dynamic adjustment parameters; and the attitude adjustment execution module performs multi-point attitude adjustment and dynamic feedback optimization on the equipment group. The technical problem that an existing floating type wind power equipment set lacks a flexible floating posture adjusting means and is difficult to cope with floating posture changes caused by a complex marine environment is solved, the operation stability of the equipment set is improved, and therefore the power generation efficiency is improved, and the service life of the equipment is prolonged.

The invention discloses an old community photovoltaic building integrated reconstruction design method, and particularly relates to the technical field of building reconstruction design, and the method comprises the following steps: firstly, obtaining the three-dimensional structure data of a building through scanning equipment, and determining a suitable photovoltaic installation region based on a preset reconstruction region grade; calculating the bearing capacity of the photovoltaic module according to the transformation area, determining the total weight of the bearable photovoltaic module, and designing the initial distribution of the module; an inclination angle and an azimuth angle of a photovoltaic module are optimized through sunlight analysis, after installation is completed, an inverter is used for converting direct current into alternating current, the alternating current is connected to an intelligent power grid system, finally operation data are collected regularly, and a neural network is used for predicting faults and evaluating a health state. According to the invention, a feasible scheme is provided for large-scale popularization of renewable energy sources, the installation of the photovoltaic system can make full use of the idle space of old buildings, the utilization efficiency of solar energy resources is improved, the dependence on traditional energy sources is reduced, and the energy consumption of old communities is reduced.

The invention discloses a runoff prediction model based on multi-source information integration of an Informer model, and belongs to the technical field of hydropower station runoff prediction. The invention aims to solve the problem of poor accuracy of medium and long term runoff prediction, especially for runoff sequences with multi-source, non-linear and non-stationary characteristics. The monitoring power station range is selected, and historical runoff data of the hydropower station and hydrological information such as rainfall and temperature of a surrounding area are obtained; adopting a Pearson correlation analysis method to select strong correlation features as multi-source time sequence feature input of an Informer model; preprocessing the data by using an STL seasonal decomposition method, and extracting characteristics of a period term and a trend term; runoff prediction is carried out by adopting a sparse attention mechanism and a self-attention distillation mechanism of an Informer model; according to the method, the prediction speed and feature capture can be enhanced, the runoff prediction accuracy is improved, and powerful support is provided for water resource management and scheduling of the hydropower station.

The invention relates to a light storage and charging cooperative control method, electronic equipment and a medium. The method comprises the following steps: collecting related meteorological data influencing photovoltaic power generation, calculating a Spearman correlation coefficient, determining key meteorological characteristics, and constructing a data set; and predicting the photovoltaic generation power based on the data set by using a feature attention mechanism and a GRU model. Meanwhile, historical data of the charging piles at different geographic positions are collected and processed, space and time characteristics are extracted by using a K-Means clustering algorithm, and a charging pile load short-term prediction model is constructed. And according to the prediction results of the photovoltaic power generation and the charging pile load, a multi-target optimization model is established by using an MOPSO algorithm, and energy collaboration and optimization control among photovoltaic power generation, energy storage and electric vehicle charging are realized.

The invention discloses a wind power master control system based on a safe and credible software and hardware platform, which belongs to the technical field of wind power generation and comprises a data acquisition module, a data analysis module, a monitoring result judgment module, an abnormal unit optimization control module and a data backup module. According to the invention, the data acquisition module acquires the operation monitoring parameters of the wind turbine generator in real time, and the operation monitoring parameters are processed by the data analysis module to obtain the operation monitoring evaluation value, so that the operation state of the wind turbine generator is accurately judged, and accurate monitoring and timely early warning of the wind turbine generator are realized; the problem that in the prior art, a wind power master control system is insufficient in safety performance and reliability is effectively solved, and the safe operation level and the fault handling capacity of a wind power plant are improved.

The invention discloses a self-adaptive optimization method for a fan control strategy. The method comprises the following steps: acquiring real-time data of a fan, health state data of equipment in the fan and meteorological data around the fan; performing data preprocessing and fusion on the acquired real-time data, the equipment health state data and the meteorological data to generate processed data; based on the processing data, constructing a deep neural network model, and correcting a power curve of the traditional fan according to the real-time working condition through the constructed deep neural network model; adjusting control parameters of the fan according to the corrected power curve by using a particle swarm optimization algorithm; through a machine learning algorithm, real-time analysis is carried out on the operation data of the fan, and early warning is carried out on potential faults; according to the actual operation effect and the potential fault early warning information of the draught fan, the feedback mechanism is combined, the draught fan control strategy is optimized, the draught fan control strategy can be accurately and dynamically adjusted, and it is ensured that the draught fan is always kept in the optimal working state.

The invention belongs to the technical field of wind power, and particularly relates to an in-service fan in-situ transformation capacity expansion method. The method comprises the steps of foundation transformation, supporting tower lifting and transformation and generator set replacement. The foundation transformation comprises the steps that anchor rods are installed on an original foundation, reinforcing steel bars are implanted, flange screws are embedded, and concrete is poured so that the foundation face can be enlarged. The transformation of the supporting tower comprises the step of lifting and heightening an original supporting tower so as to adapt to a unit with a larger diameter; the generator set is replaced by installing components with larger power generation capacity on the top of a new tower drum, and the components comprise a cabin, a hub, blades and the like. The method is suitable for transformation and capacity expansion of the old wind power plant, the transformation cost can be greatly reduced, and the wind power generation efficiency is improved.

The invention provides a wind driven generator blade icing monitoring and deicing control system and method, and the system comprises a noise collection unit, a temperature collection unit, an actual calculation unit, a deicing scheme generation unit, and a deicing scheme selection unit. The operation parameters of the wind generating set are monitored and analyzed by combining with the operation parameters of the wind generating set, including wind speed, air temperature, humidity, blade rotating speed, power generation power and the like, and meanwhile, real-time monitoring, acquisition, processing and storage are carried out through a monitoring system and a sensor. Operation parameters and environment data of the wind generating set are monitored, collected, processed and stored, monitoring, alarming and analyzing of the icing condition of blades are achieved, the optimal deicing strategy and time arrangement are determined, the deicing effect is improved to the maximum extent, the energy consumption of the set is reduced, the power generation efficiency and economical efficiency of the set are improved, and the economic benefit is increased. The purposes of reliable, efficient and economical operation and maintenance of the wind generating set are achieved.

The utility model provides a photovoltaic panel pose adjusting device and a photovoltaic curtain wall system, the photovoltaic panel pose adjusting device comprises a photovoltaic support and a photovoltaic panel, and the photovoltaic support comprises a support frame, a telescoping mechanism, a rotating member and a driving mechanism. The first end of the supporting frame is hinged to a first preset position of the facade structure, and the hinge rotation axis is parallel to the horizontal plane. The direction from the first end to the second end of the supporting frame is n. One end of the telescopic mechanism is hinged to the second end of the supporting frame, and the other end of the telescopic mechanism is hinged to a second preset position of the facade structure below the first preset position. The rotating piece is rotatably installed on the supporting frame, and the rotating axis is in the n direction. The driving mechanism is installed on the supporting frame and used for driving the rotating piece to rotate. The back face of the photovoltaic panel is fixedly connected with the rotating piece, and the photovoltaic panel rotates along with rotation of the rotating piece. According to the technical scheme, angle adjustment in the vertical direction and the horizontal direction of the photovoltaic panel can be achieved, the photovoltaic panel fully receives solar rays, and the power generation efficiency is improved.

The invention provides a photovoltaic array optimization generation method and device, electronic equipment and a storage medium, and the method comprises the steps: calculating a target inclination angle of a photovoltaic module unit in a target photovoltaic power station based on meteorological data and factory site geographic data of the target photovoltaic power station; obtaining an inverter type of a target photovoltaic power station, and determining a target number of photovoltaic module units connected with each inverter according to the inverter type; according to the factory site geographic data, calculating a target distance between the photovoltaic module units; and inputting the target inclination angle, the target number and the target spacing into an array optimization model for array optimization, and generating an optimized array of the target photovoltaic power station. Compared with the prior art, according to the embodiment of the invention, illumination absorption is maximized through the target inclination angle obtained through calculation, so that the power generation efficiency is improved; and the target inclination angle, the assembly number and the spacing are input into the array optimization model, so that a scientific basis can be brought to the design of the photovoltaic power station, and the overall performance and economic benefits of the system are further improved.

The invention discloses an energy regulation and control method of a photovoltaic system, and relates to the field of energy regulation and control of the photovoltaic system, and the method comprises the steps: collecting comprehensive state data in a time period T, processing the comprehensive state data, and obtaining time sequence state data; performing primary processing on the time sequence state data by using moving average filtering to obtain a smoothed initial data set, taking the initial data set as observation input of Kalman filtering, further smoothing the data by using the Kalman filtering to obtain a high-precision gain data set, and using improved Pamp; performing disturbance judgment on the gain data set through an O algorithm; according to the method, power oscillation of voltage in a prediction interval is eliminated by using an IncCond method, subdivision demand judgment is performed, a maximum power point is accurately positioned by using a subdivision search method, and the maximum power point is output as a working point of the system, so that energy regulation and control of the photovoltaic system at the maximum power point are realized, and the energy efficiency of the photovoltaic system is improved.

The invention relates to the field of fan fault diagnosis, in particular to a fan blade fault diagnosis and early warning method based on multi-source data fusion, which comprises the steps of data acquisition, data preprocessing, feature extraction, data fusion and early warning strategy formulation. By fusing the vibration data, the strain data and the image data, the operation state of the fan blade can be reflected more comprehensively and accurately, the accuracy of fault diagnosis and the timeliness of early warning are remarkably improved, the false alarm rate and the missing report rate are reduced, unnecessary shutdown overhaul is reduced, and the availability rate and the power generation efficiency of a wind turbine generator are improved. Potential fault hidden dangers can be found in an early stage, powerful support is provided for preventive maintenance, and the maintenance cost and the operation and maintenance risk are reduced. Operation management of the wind power plant is optimized, and the overall economic benefit and market competitiveness are improved.

The invention discloses an intelligent self-adaptive cleaning system and method for a photovoltaic module, and mainly solves the problems that the cleaning effect of a photovoltaic module cleaning system on stains (such as bird droppings and oil stains) with strong adhesive force and fine dust particles is limited, and it is difficult to ensure that the surface of the module keeps good cleanliness all the time. The cleaning system comprises an environment sensing module used for detecting the cleaning state of the photovoltaic module, an intelligent cleaning module connected with the environment sensing module and used for executing the cleaning function, and self-adaptive control connected with the environment sensing module and used for controlling the intelligent cleaning module. And the energy recovery module is connected with the intelligent cleaning module and is used for realizing energy recovery and feeding back power supply to the environment sensing module. By means of the design, the multi-sensor fusion environment sensing technology and the intelligent cleaning technology are combined, the stain type and the pollution degree can be more accurately recognized, a targeted cleaning mode is adopted, and compared with a traditional cleaning technology, the cleaning effect is remarkably improved.

The invention discloses a wind power blade damage detection device, and relates to the technical field of wind power blade detection, and the device comprises a detection module which is responsible for carrying out the comprehensive detection of a wind power blade, and a solar power supply module which is responsible for collecting energy through a solar panel, and storing the energy in a battery, so as to improve the cruising ability of an unmanned plane body. The data fusion and analysis module is responsible for integrating the data of the detection module to form a comprehensive wind power blade damage detection report, and the real-time monitoring and feedback module is responsible for transmitting the detected data to a monitoring center in real time. Through the ultrasonic detection unit, the visual detection unit and the infrared detection unit, wind power blade damage detection in multiple modes can be realized, so that the defects of a single detection method are overcome, different modal information extracted by multiple detection methods is fully utilized, the detection precision is improved, accurate identification of the surface damage and the internal damage of the wind power blade is realized, and the detection efficiency is improved. And accurate three-dimensional positioning of the damage is realized.

The invention relates to the technical field of wind resource assessment and wind power plant optimization, and discloses a multi-source information fusion measurement system combining laser radar data and wind resource assessment, and the system comprises a data collection module which is used for collecting laser radar data, synthetic aperture radar data, numerical weather forecast data and ground weather station data; the data preprocessing module is used for carrying out noise filtering, time alignment, space alignment and data calibration on the collected data; the information fusion module is used for dynamically fusing the preprocessed multi-source data and outputting high-precision wind speed and turbulence characteristic distribution; and the wind field modeling and prediction module is used for constructing a dynamic three-dimensional wind field based on the fusion data and performing short-time wind speed prediction. Through multi-source data deep fusion, dynamic wind field modeling and intelligent optimization modules, the comprehensive effects of high-precision wind field evaluation, nonlinear wind speed prediction and fan layout global optimization are achieved.

The invention belongs to the technical field of wind power generation, and discloses a wind power plant digital twin modeling system and a use method, the system comprises an equipment module, the equipment module comprises a biological bionic adaptive fan blade system, a quantum sensing network, a laser radar system, a high-resolution multi-modal imaging system and an intelligent autonomous flying robot group system; the network module comprises a 5G private network, a quantum communication network and an edge computing network; the data module comprises a distributed database system, a big data processing platform and an AI training platform; the AI module comprises a wind regime prediction model, a power prediction model, an equipment health state monitoring model and a self-adaptive control algorithm model; the application module comprises a digital twinborn visualization platform, a holographic mixed reality operation and maintenance system and an intelligent scheduling system. Modeling and intelligent management of the wind power plant can be realized, the power generation efficiency can be improved, the operation and maintenance cost can be reduced, and the service life of equipment can be prolonged.

The invention discloses a Carnot battery system based on phase change cold storage and energy storage and a multi-mode operation method thereof, the Carnot battery system comprises a vapor compression refrigeration unit, a phase change cold storage device and a power cycle unit, in a charging stage, the vapor compression refrigeration unit is adopted to generate cold energy by using off-peak power; in the energy storage stage, cold energy prepared by the steam compression refrigeration unit is stored in a high-density mode through the phase change cold storage device; in the discharging stage, the stored cold energy serves as a cold source, external low-temperature waste heat serves as a heat source, a power circulation unit is adopted, meanwhile, the cold energy and the hot energy are utilized for heat-work conversion, and electric energy is released; according to the Carnot battery system provided by the invention, the round-trip efficiency and the energy storage density of an energy storage system can be improved, the energy storage cost is reduced, and large-scale long-time energy storage is facilitated; according to the multi-mode operation method provided by the invention, through dispatching application of the phase change cold storage device and the charge-discharge cycle, different types of low-temperature heat sources can be fully utilized, and the cold electricity energy consumption requirement of a user side is met.