19 results about "Wind resource" patented technology

This invention discloses a PIDNN-SO-based method for optimizing the layout of offshore wind farms, belonging to the field of wind farm optimization design technology. The method first inputs wind farm, turbine, and wind resource parameters, sets constraints on turbine spacing, boundaries, and wake overlap rate, and constructs a high-precision wake flow field physical model based on actuator disk theory, Navier-Stokes equations, and a weighted quadratic wake superposition model. Secondly, it builds a physical information dual neural network (PIDNN) with dual encoders, integrating physical equation loss and data loss to train the model, achieving rapid and accurate prediction of wake wind speed. Then, it uses the snake optimization algorithm (SO) to optimize the environmental evolution factor, completing an efficient search for turbine layout. Finally, it constructs a PIDNN-SO collaborative optimization framework, trains a PIDNN surrogate model through initial sampling, and outputs the optimal layout that maximizes annual power generation. This invention can effectively reduce wake loss and significantly improve the power generation efficiency of offshore wind farms.

This invention relates to the field of energy supply technology, and particularly to an integrated wind-solar-hydrogen-storage comprehensive energy utilization system and method. The system includes photovoltaic power generation equipment, wind power generation equipment, energy conversion and storage equipment, power conversion equipment, a balance of power (BOP) system, and material storage equipment. The energy conversion and storage equipment includes an SOEC electrolyzer, a PEMFC fuel cell, and a battery. The power conversion equipment includes an AC-DC converter and a DC-AC converter. During the day, when solar resources are abundant and wind resources are relatively scarce, excess photovoltaic power, besides supplying users, is used for hydrogen electrolysis and storage or for battery storage. Wind power is used to supply the user side and the BOP system. At night, when solar resources are scarce and wind resources are abundant, the SOEC is only in a heat preservation state. Wind power is supplied to the user side and for SOEC heat preservation, and excess wind power is stored in the battery. This invention achieves multi-level energy utilization from high to low energy levels, while ensuring rapid response on the user side, and possesses strong flexibility and adjustability.

The application discloses a wave energy and wind energy combined power generation device and a control method, which comprises a floating platform, a wind turbine unit and a wave energy mechanism; the floating platform is provided with an inclination detection mechanism, the inclination detection mechanism is used for obtaining platform inclination data of the floating platform and comparing the platform inclination data with preset standard inclination data to generate a comparison result; the wind turbine unit is installed on the upper end of the floating platform, and the wind turbine unit is used for obtaining wind energy by adjusting the orientation position in response to the received comparison result; the wave energy mechanism is movably connected with the floating platform, and the wave energy mechanism is used for obtaining wave energy by adjusting the wave-encountering angle in response to the received comparison result; the problems that the existing offshore power generation device is out of synchronization and mismatching with wind resources and wave resources, and the problem of low utilization efficiency of wind and wave resources are solved.

The application discloses a kind of wind turbine unit optimization layout method based on three levels dynamic variation rate, comprising the following steps: step one: obtaining target wind farm information, including (1) the annual average wind resource information of target wind farm;(2) unit specification parameter;(3) wind farm planning area boundary;Step two: combined with fan wake wind speed and turbulence model, calculate annual total average power generation and evaluate full life cycle degree electric cost;Step three: the wind farm planning area is gridded, with the optimization target of flat standardization energy cost, carries out unit grid location preliminary optimization using the improved genetic optimization algorithm based on three levels dynamic variation rate, obtains several grid optimization schemes by integration theory;Step four: according to the preliminary optimization result of grid location, constructs the grid boundary of each candidate unit, carries out fine coordinate position optimization in corresponding grid using adaptive weight particle swarm optimization algorithm, and obtains the final unit layout scheme.

This invention provides a method, system, equipment, and medium for monitoring blade root load calibration data, belonging to the field of wind turbine control technology. Based on wind resource parameters and IEC load calculation standards, the method iteratively calculates the turbine load to obtain the maximum design value of the blade root load. It performs coordinate transformation on the load and moving average filtering on the load signal. It calculates the average blade root load of each of the three blades and the difference between the average blade root load of each individual blade and the average load of the three blades. The difference is compared with the theoretical maximum value of the load in the blade root flapping direction to determine if it exceeds the load deviation alarm threshold. If it does, a wind turbine fault alarm is issued, and pitch optimization actions are performed based on the load deviation and a pitch angle limit table. This method can monitor blade root load calibration data, continuously optimize the wind turbine's operating status, reduce load deviation, and improve the safety and stability of the wind turbine.

The application provides a kind of offshore wind farm hub height wind speed calculation method, it is related to offshore wind resource evaluation technical field. Including: obtaining the satellite SAR of target sea area is retrieved sea surface wind speed, and simultaneously in the wind farm area is arranged not less than three floating laser radar to measure high altitude three-dimensional wind speed profile, the two kinds of data sources are matched in time and space, to the data after time and space matching constructs training sample set, and with sea surface wind speed, atmospheric stability, sea surface roughness as input characteristics, hub height wind speed as output label, trains machine learning model, the global SAR sea surface wind speed data is batch calculated to hub height, finally generates the hub height wind resource atlas covering the whole target sea area;Data source level realizes the organic complement of planar sea surface wind field and point vertical profile, improves the accuracy of data, improves the calculation accuracy, improves the accuracy and reliability from sea surface to hub height wind speed calculation.

This invention discloses a method and apparatus for evaluating wind turbine retrofitting schemes based on operational data, relating to the field of wind power engineering technology. The method includes: collecting at least five years of operational data from the target wind farm; preprocessing the data using the DBSCAN-segmented quartile combination algorithm; restoring the free-flow wind speed through primary and secondary correction functions to separate the impact of wind resource fluctuations and obtain the net power generation revenue increment from the retrofit; and establishing a multi-dimensional comprehensive evaluation system to assess the degree to which the technological upgrade improves the overall benefits of the wind farm. The apparatus includes a data acquisition module, a correction module, and an evaluation module, which execute the steps described above. This invention solves the problems of insufficient representative wind measurement data and single evaluation indicators for retrofitting schemes. By utilizing existing operational data from wind farms, it can effectively isolate the impact of wind resource fluctuations, explore the net power generation revenue increment brought about by the technological upgrade of wind turbines, improve the accuracy and comprehensiveness of the evaluation, and provide a scientific basis for the selection of retrofitting schemes.

A monitoring and early warning method and system based on fan bolt vibration ultrasonic coupling relate to the technical field of wind power equipment fatigue fault diagnosis. The vibration signal, ultrasonic signal and displacement signal of the bolt to be monitored are synchronously collected; the vibration signal, ultrasonic signal and displacement signal are compensated and extracted based on the real-time operating condition parameters of the wind turbine generator set, to obtain the vibration characteristic value, ultrasonic characteristic value and real-time displacement value; the vibration characteristic value, ultrasonic characteristic value and real-time displacement value are normalized and input into a preset fault recognition model for processing to obtain state information; the remaining service life is obtained through prediction calculation based on the material parameters of the bolt to be monitored, real-time operating condition parameters and state information; and the warning level and comprehensive maintenance scheme are generated based on the remaining service life, state information and wind resource prediction data. The method solves the problem that a single monitoring method cannot accurately extract early bolt faults in a strong interference environment.

The application discloses a wind resource assessment method, device, equipment, medium and product, and belongs to the technical field of wind power generation. Before wind resource assessment modeling is performed, the wind condition parameters of the location of the wind measurement tower are estimated according to different parameter value combinations, combined with the characteristics of the power field, the wind condition parameter estimation results corresponding to the different parameter value combinations are obtained, the optimal parameter value combination matched with the wind field is determined according to the estimation results and the true results, and then the wind resource assessment is performed according to the optimal parameter value combination, that is, the parameter verification and screening steps are added before the wind resource assessment is performed, the parameters required for the wind resource assessment can be optimized through the steps, and then the assessment accuracy of the wind resource can be improved.

The invention discloses a method for finely measuring and calculating the developable capacity of a wind power installation technology in a specified area, and the method comprises the following steps: S1, obtaining the geographic information and wind resource data of a target area, and superposing a restrictive factor layer to obtain available land resources; s2, dividing available land into a mountain land type and a flat land type based on topographic features; s3, preferentially extracting a ridge line corridor of a mountain type, and performing mountain unit arrangement in combination with a main wind direction and a fan wake flow model; s4, updating the available boundary of the flat ground type based on the wake flow influence area of the mountain unit, and performing boundary recursive unit arrangement in the flat ground type; s5, matching a corresponding model according to the wind speed data of the arranged point positions; and S6, accumulatively calculating the total installed capacity. According to the method, on the premise that the terrain and wake flow arrangement rule is met, the technology developable quantity of wind power installation can be rapidly and automatically measured and calculated in a large range.

This invention discloses an automatic optimization method for wind resource forecasting based on multi-parameterized scheme selection and WRF nested optimization. The method includes: automatically acquiring and standardizing GFS meteorological, geographic static, and high-precision topographic data; constructing a fixed parameterized scheme library, which can randomly generate extended schemes as needed; configuring key WRF physical processes according to scenario adaptability principles; dynamically determining WRF nested schemes and densifying the vertical layer near the hub height; running each scheme through multi-instance parallel computation to obtain simulated data of key meteorological elements; constructing a comprehensive evaluation system based on multiple indicators for quantitative scoring and dynamically adjusting scenario adaptability principles; selecting the optimal scheme, restarting the WRF simulation, and outputting high-resolution wind field data. This invention achieves intelligent selection and nested optimization of parameterized schemes, improving the accuracy and automation level of wind resource forecasting, and is adaptable to different scenario requirements.

The present application relates to renewable energy assessment and weather forecasting technical field, especially to a kind of wind and light resource fine estimation method based on numerical simulation and observation constraint. Global climate model driving field set is constructed, and the optimal GCM combination is screened out;Regional climate model framework is constructed;High spatio-temporal resolution simulated wind speed and solar radiation data are obtained;Generate kilometer level, hourly wind and light resource data set of history and future. The present application provides a kind of wind and light resource fine estimation method based on numerical simulation and observation constraint, by introducing high resolution, multi-source fusion ground surface wind speed and solar radiation long sequence historical observation data, using quantile mapping method to carry out systematic deviation correction to simulation result, realize statistical downscaling processing under the observation data constraint, finally obtain the wind resource data with 5 kilometers horizontal resolution, so as to significantly improve the high spatio-temporal resolution information capture ability to future wind resource change.

The application relates to the technical field of new energy resource simulation, and discloses a wind resource dynamic downscaling method based on a global stretching grid mode, which introduces grid stretching transformation in an initial global mode framework adopting an original cubic spherical uniform grid, realizes gradual grid encryption of spatial resolution in an arbitrary target region while keeping smoothness and physical consistency in a numerical calculation process, and realizes seamless transition from large-scale driving data to a local high-precision wind resource field while retaining large-scale meteorological information. Meanwhile, the short-time strong gust and extreme wind speed event simulation capability is improved by embedding a theoretical gust wind speed calculation module in the global stretching grid mode. Further, the target global stretching grid mode is used for downscaling processing of wind resources of a target region to be downscaled, so that seamless transition from large scale to a local high-precision wind resource field is realized.

This invention discloses a method for calculating and correcting the load on offshore wind turbines in typhoon-prone areas. The method includes ultimate load correction calculations and fatigue load correction calculations. The ultimate load correction calculation corrects the ultimate load through wind resource analysis and iterative optimization calculations. The fatigue load correction calculation corrects the fatigue load through wind resource analysis and wind speed distribution model corrections, combined with iterative optimization calculations. This method for calculating and correcting the load on offshore wind turbines in typhoon-prone areas involves calculations and corrections based on air density, turbulence intensity, mud surface stiffness matrix, and wind speed distribution model, resulting in more accurate load analysis, providing data support for structural design, and ensuring structural safety and economic rationality.

This application provides a marine moored wind measurement device, comprising a mooring device, a wind measurement device, and at least four movable mooring devices. The mooring devices are fixed to the sea surface, and the at least four mooring devices are arranged around the mooring device. Each of the at least four mooring devices is connected to the mooring device via a tow rope, allowing the mooring device to suspend at a target position. The wind measurement device is fixedly connected to the mooring device. This application, by arranging at least four movable mooring devices around the mooring device to suspend it at the target position, facilitates stable measurement of wind force and speed on the sea surface. Compared to marine wind measurement towers, it offers advantages such as convenient installation and dismantling, and low cost. Compared to floating lidar, it provides stable observation at a similar cost. Therefore, it achieves long-term, stable, and accurate observation of marine wind resources at any altitude at a relatively low cost.

The present disclosure relates to a method and device for reconstructing a unit load model, electronic equipment, a storage medium and a computer program product. The method comprises: obtaining an initial unit load model for a unit under test; obtaining wind resource data; obtaining actual load and actual operation data of the unit under test under the wind resource data; inputting the wind resource data into the initial unit load model for simulation to obtain simulated load and simulated operation data; and adjusting the value of the parameters of the initial unit load model to minimize the difference between the actual load and the simulated load and to minimize the difference between the actual operation data and the simulated operation data, thereby reconstructing the unit load model of the unit under test. In this way, the present disclosure can reconstruct the unit load model without the original design data of the unit, thereby providing strong data support for the safety evaluation of the technical improvement of the unit.

The present disclosure relates to a wind farm sector management method and device. It relates to new energy wind power generation technology, solves the problem that fixed sector optimization cannot adapt to complex and changeable application requirements, resulting in low management efficiency and power loss. The method comprises: obtaining simulated wind resource quantitative data of a wind farm, the simulated wind resource quantitative data indicating the airflow movement law of the wind farm; obtaining a machine position with fatigue load exceeding a preset fatigue threshold as an over-standard machine position according to the simulated wind resource quantitative data; obtaining at least one management sector of each over-standard machine position according to the over-standard reason causing fatigue load to exceed the standard; and generating a management strategy for the wind turbine generator on the over-standard machine position based on the management sector. The technical scheme provided by the present disclosure is suitable for wind farm project planning and design, and realizes wind farm sector management that can adapt to various complex application scenarios.

The application relates to a dual-mode switching wind turbine generator set and a control method. The control method comprises the following steps: acquiring power environment parameters and wind resource prediction data, defining multiple energy absorption gears and constructing a corresponding cost-energy absorption collaborative optimization model; extracting a corresponding input vector and inputting the input vector into the cost-energy absorption collaborative optimization model to generate a corresponding mode switching vector parameter; when the mode switching vector parameter response is completed, a corresponding deviation result is calculated, and the collaborative optimization model is closed-loop updated according to the deviation result. The unit can not only actively absorb the power grid power under the condition of negative electricity price or power grid power excess, but also avoid the waste of wind energy caused by shutdown or power reduction. In addition, the unit can perform energy absorption path distribution in an economic priority and power flexibility optimization mode, so that the wind turbine generator set is transformed from a single energy output device into a controllable load participating in power grid regulation, and the unit utilization and power grid support capability are improved.

A wind turbine location selection method for a wind farm, and a related apparatus. The method comprises: obtaining, by anemometer towers, wind resource fixed measurement data at a plurality of fixed locations in a reference area and obtaining a fixed measurement reference value of a target wind resource index; a surveying device performing surveying multiple times in the reference area along a plurality of surveying paths for data collection to obtain a plurality of sets of wind resource dynamic measurement data; calculating dynamic measurement reference values of the target wind resource index; determining a target surveying path on the basis of the matching between the dynamic measurement reference values and the fixed measurement reference value; constructing a surveying path in a non-reference area on the basis of the target surveying path, and the surveying device performing surveying along the path for data collection to obtain wind resource dynamic measurement data in the non-reference area; and on the basis of the wind resource dynamic measurement data in the reference area and the wind resource dynamic measurement data in the non-reference area, by analyzing wind power output, wind power generation cost , and grid electricity revenue, determining, in a wind farm area to be constructed, a plurality of wind turbine locations to be constructed.