A wind generator includes a revolving platform rotationally connected with a base; a tower body, where a bottom end of the tower body is connected to the revolving platform, a top end of the tower body is fixedly provided with a generator room, and a plurality of blades are rotationally connected to the generator room through a wheel hub; and the tower body is provided with at least one windward side in the circumferential direction of the tower body, and a bending stiffness of the windward side is not less than that of the remaining sides of the tower body; and a power source, where the power source is started when airflow is to the sides rather than the windward side to enable the airflow to flow to the windward side while the windward direction of the blades coincides with the airflow. A wind generator group is further provided.

A method of controlling a wind turbine is provided, comprising identifying an out-of-vertical load acting in a first direction on the wind turbine. A direction of a wind load acting on the wind turbine is determined. If there is a degree of alignment between the direction of the wind load and the first direction, the wind turbine is controlled to reduce the wind load.

Enabling control of wind turbines is provided. The method comprises receiving power production signals from wind turbines comprising a wind farm and estimating wake travel times from upstream wind turbines to downstream turbines. Correlations of the power production signals are calculated among all pairs of wind turbines in the wind farm. Wind turbines with a power production correlation above a specified threshold at an expected time are considered to have wake interaction. A probability density function of northing directions is calculated for the wind turbine pairs with wake interaction. A determination is made whether the probability density function has a dominant direction. Responsive to the probability density function having a dominant direction, the wind turbine pairs with wake interaction are identified as turbine clusters. A control strategy is applied to each turbine cluster as an operational unit to optimize power production of the wind farm.

Systems and methods of autonomous farm-level control and optimization of wind turbines are provided. Exemplary embodiments comprise a site controller running on a site server. The site controller collects and analyzes yaw control data of a plurality of wind turbines and wind direction data relating to the plurality of wind turbines. The site server determines collective wind direction across an area occupied by the plurality of wind turbines and sends yaw control signals including desired nacelle yaw position instructions to the plurality of wind turbines. The site controller performs wake modeling analysis and determines desired nacelle positions of one or more of the plurality of wind turbines. The desired nacelle yaw position instructions systematically correct static yaw misalignment for all of the plurality of wind turbines. Embodiments of the disclosure provide means to perform whole site or partial site level controls of the yaw controllers of a utility scale wind turbine farm. The overall effect of the coordinated yaw control of wind turbines across the whole or partial site is intended to keep the wake loss of the wind turbines from the upstream wind turbines to the minimum and to maximize the production of turbines that are not waking other turbines.

There is provided a method of avoiding edgewise vibrations during a non-operational period of a wind turbine. The method comprises defining a non-operational period for a wind turbine arranged at a specific site, determining expected wind conditions at the specific site during the non-operational period and defining a plurality of potential yaw orientations for the wind turbine. The method further comprises determining the relative probability of edgewise vibrations occurring during the non-operational period for each potential yaw orientation based upon the expected wind conditions during the non-operational period, determining one or more preferred yaw orientations, which are the yaw orientations in which the probability of edgewise vibrations occurring is lowest, and arranging the wind turbine in one of the preferred yaw orientations during the non-operational period.

The present invention relates to non-thermal renewable energy turbines (20,24,34, 38,40), in particular to the monitoring of turbine performance to identify a loss of performance indicative of faults or component degradation. The method involves comparison of measured power from a target turbine (20) with a predicted value for same turbine. The predicted value is calculated using the output from a plurality of other turbines (24,34,38,40) from an array and a predictive model including weightings for the other turbines (24, 34,38,40) based on the strength of correlation of their historical with historical data from the target turbine (20).

A vertical wind turbine that includes a plurality of vertical vanes, each of which is secured to a respective vertical vane axis so as to be rotatable about a respective vane rotational axis independently of one another by a motor and which are mounted on a common circular path in a rotatable manner about a vertical rotor rotational axis. A method for operating a vertical wind turbine. Angular positions about a respective vertical vane axis are specified for driven vertical vanes of the vertical wind turbine. The vertical wind turbine is operated in a particularly efficient and material-preserving manner in that the angular positions of the vanes are permanently regulated by directly driving the vanes using a pitch motor arranged concentrically to the respective vane axis.

A method of controlling pitch of individual blades in a wind turbine is described, together with a suitable controller. Wind speed is determined as a function of azimuthal angle. Wind speed is then predicted for individual blades over a prediction horizon using this determination of wind speed as a function of azimuthal angle. The predicted wind speed for each individual blade is used in a performance function, which is optimized to control individual blade pitches.

A power control method and apparatus for a wind power generator. The power control method comprises: predicting, according to historical wind resource data, wind resource data within a predetermined future time period (S10); estimating, according to the remaining design lifetime of a wind power generator, the maximum design lifetime allowed to be consumed within the predetermined future time period (S20); determining, according to the predicted wind resource data and the estimated maximum design lifetime, optimal output powers of the wind power generator in respective wind velocity ranges within the predetermined future time period (S30); and controlling operation of the wind power generator according to the determined optimal output powers of the wind power generator in the respective wind velocity ranges within the predetermined future time period (S40).

Aspects of the present invention relate to controlling a renewable energy power plant comprising a plurality of wind turbine generators (WTG)s and an energy storage system (ESS). A method includes: controlling the plurality of WTGs to stop generating power, and thereby to enter a non-exporting mode of operation of the renewable energy power plant, during which one or more auxiliary systems of the renewable energy power plant are powered to maintain at least one of the plurality of WTGs in a standby state, operable to start generating power upon demand; wherein the one or more auxiliary systems are powered during the non-exporting mode of operation.