In the context of global energy structure transformation, the rationality of wind power plant layout directly affects power generation efficiency and investment return. the United StatesDAVISMeteorological stations, with their high-precision sensors and multi parameter monitoring capabilities, can provide key data support for wind turbine site selection and array optimization. The optimization mechanism is explained from three dimensions: technical principles, implementation path, and application effectiveness

1、 Core monitoring parameters and data value

DAVISThe meteorological station can collect the following key data in real time by integrating anemometers, wind indicators, temperature sensors, and turbulence intensity analysis modules:

Three dimensional wind speed profile: Through6332anemometer/Sensor transmitter kit, synchronous monitoring10Mi to100The wind speed gradient at a height of meters reveals the vertical distribution characteristics of wind energy resources at different heights.

Turbulence intensity analysis: using6316The wireless weather messenger is equipped with a three-dimensional ultrasonic anemometer to accurately calculate turbulence intensity（TIIdentify high turbulence areas to avoid fatigue damage to the fan.

temperature-Density compensation:6382The atmospheric temperature data collected by wireless temperature and humidity stations can be used to correct the impact of air density on wind energy conversion efficiency (with a power curve correction factor of)±3%）.

Identification of dominant wind direction:6415Implementation of ultrasonic anemometer0.1°Wind direction resolution, combined with30Annual climate statistics data, determineoptimalWind rose chart.

2、 Implementation path for optimizing wind turbine layout

1. Micro site selection stage

In50km²In the planning of wind farms, deployment10-15TaiwanDAVIS Vantage Pro2 PlusMeteorological station (including6162A grid monitoring network is formed using ultraviolet radiation sensors

Wind Energy Resource Assessment: Through12Continuous monitoring for months, generating wind speed frequency distribution map（Weibulldistributed parameterkThecValue), identify wind speed>3m/sThe proportion of duration.

Terrain adaptability analysis: combined with6345Soil moisture station data, evaluate the acceleration effect of terrain uplift on wind speed (terrain coefficient reaches)1.2-1.8）.

Wake effect modeling: utilizing6312The wind direction change rate data recorded by the wireless console, throughCFDSimulate to determine the minimum spacing between fans (usuallyrotor diameterof5-8Double).

2. Dynamic optimization stage

For an existing wind farm, it can be achieved throughDAVIS 6327Wireless integrated sensor kit implementation:

Real time power prediction: inputting monitoring dataSCADASystem, correctionIECStandard power curve to reduce prediction error from±15%drop to±8%.

Yaw correction support:6410The instantaneous wind direction data provided by the anemometer can optimize the response speed (response time) of the wind turbine yaw system<5s）.

Ice warning system:6372Wireless temperature station and6464Rain bucket linkage, when the ambient temperature<-5℃And humidity>85%Trigger the de icing command.

3、 Typical application effectiveness

case1Coastal Mountain Wind Farm

In a certain location in Fujian100MWDeployment in wind power projects22TaiwanDAVISAfter the meteorological station, it was discovered that:

The original planning layout resulted in15%The wind turbine is located in the shadow area of the wake, and the annual average power generation has increased after adjustment12.7%

By dividing turbulence intensity zones3Replacing the high turbulence zone fan with a low wind speed unit reduces the cost of electricity per kilowatt hour0.03yuan/kWh

Wind direction rose chart correction enables wind turbines to correct wind errors from±8°drop to±3°Increase in power coefficient4.2%

case2: Plain distributed wind power

A certain place in Inner Mongolia50MWThe project adoptsDAVISMobile monitoring solution:

利用6322wirelessISSThe portability feature of the sensor kit, in3Complete within a month200Evaluation of candidate locations

Discovery of local thermal circulation leading to increased nighttime wind speed30%Based on this, optimize the nighttime power generation strategy

The final layout improves the utilization rate of the venue25%The land acquisition area per kilowatt has decreased18%

4、 Technological extension value

DAVISMeteorological station data can also create additional benefits through the following methods:

Ecological Impact Assessment:6490Monitoring with UV sensorsUVBData can be used to evaluate the impact of wind farms on the photosynthesis of surrounding vegetation.

Asset Health Management: Combining6440Soil moisture data, predicting the risk of foundation settlement, and extending the service life of wind turbines.

Carbon trading support: Accurate wind energy resource assessment data, which can provideCDMProject development provides a reliable basis for predicting power generation.

passDAVISThe construction of meteorological stations'Ground monitoring-spatial analysis-dynamic optimization'A closed-loop system can enhance the overall lifecycle revenue of wind farms8%-15%With the advancement of LiDAR wind measurement technology andDAVISThe fusion application of data will lead to the optimization of wind turbine layout in the millimeter level precision era, providing more solid technical support for energy transformation in the future.