The present invention relates to a method for screening a correlated seed turbine for wind direction prediction. The method includes the following steps: (1) modeling a yaw event of a wind turbine based on a wind direction, a wind speed and a yaw parameter, and obtaining a wind turbine yaw event flag of each wind turbine in a wind farm during a modeling period; (2) classifying and counting the wind turbine yaw event flag, and obtaining a yaw correlation coefficient of other wind turbines each with a target wind turbine in the wind farm; and (3) screening a seed turbine based on the yaw correlation coefficient. Compared with the prior art, the method of the present invention has the advantages of high discriminant validity of the seed turbine, small error, high correlation, and close wind speed characteristics.

The present disclosure relates to a wind park (10) comprising wind turbines arranged in a convex polygon comprising straight sides (3, 4, 5) connecting vertices of the polygon. A node wind turbine (1a, 1b, 1c) of a first type is located at each vertex of the polygon. One or more intermediate wind turbine (2a, 2b, 2c, 2d) of a second type is/are located along each side (3, 4, 5) of the polygon between two node wind turbines. The polygon forms an interior area (A) within the sides (3, 4, 5). The interior area (A) is free of turbines of the first and second type.

A method for controlling the rebuilding of an electrical supply network, wherein the electrical supply network has a first network section and at least one further network section, at least one wind farm is connected to the first network section, the wind farm can be controlled via a wind farm control room, the first network section is coupled to the at least one further network section via at least one switching device in order to transmit electrical energy between the network sections, the at least one switching device is set up to disconnect the first network section from the at least one further network section in the event of a fault, a network control station is provided for the purpose of controlling the at least one switching device, wherein, in the event of a fault during which a network fault acting on the first network section occurs, the first network section is disconnected from the at least one further network section by the at least one switching device, the wind farm control room interchanges data with the network control station via a control room connection, wherein the control room connection is a failsafe communication connection between the wind farm control room and the network control station and can be operated independently of the electrical supply network, in particular can be operated even in the case of the fault in the first network section, and the wind farm receives data from the network control station via a wind farm connection, wherein the wind farm connection is a failsafe communication connection between the wind farm and the network control station and can be operated independently of the electrical supply network, in particular can be operated even in the case of the fault in the first network section, and further data which are not transmitted via the control room connection and are not transmitted via the wind farm connection are transmitted via a further data connection provided that the latter has not failed.

A method for monitoring and controlling a wind turbine to minimize rotor blade damage includes receiving sensor data from one or more sensors indicative of at least one blade parameter of the rotor blade over a predetermined time period. The method also includes trending the sensor data for the predetermined time period with respect to at least one wind parameter. Further, the method includes determining at least one characteristic of the trended sensor data. Moreover, the method includes comparing the at least one characteristic of the trended sensor data to an operating threshold. In addition, the method includes implementing a control action if the comparison of the at least one characteristic of the trended sensor data and the operating threshold indicates blade damage is occurring or is likely to occur.

A method for operating a first wind turbine and a second wind turbine, the second wind turbine being located in the wake of the first wind turbine. A prediction model is fed with a current wind value of the first wind turbine, in order to predict a future time point at which the area swept by the rotor of the second wind turbine becomes partially overlapped by the wake of the first wind turbine. The second wind turbine reacts to the prediction in that a control signal is generated in order to alter the pitch angle of a rotor blade of the second wind turbine relative to the pitch angle of another rotor blade of the second wind turbine. The invention additionally relates to a control system suitable for executing the method. Implementation of the disclosed method by a control system can reduce the loading of the second wind turbine.

An energy-harvesting compute grid includes computing assemblies that cooperate with mobile energy harvesters configured to be deployed on a body of water. The plurality of energy harvesters are positioned on and move adjacent to an upper surface of a body of water, and the locations of the energy harvesters can be monitored and controlled. The wide-spread gathering by the harvesters of environmental data within that geospatial area permits the forecasting of environmental factors, the discovery of advantageous energy-harvesting opportunities, the observation and tracking of hazardous objects and conditions, the efficient distribution of data and/or tasks to and between the harvesters included in the compute grid, the efficient execution of logistical operations to support, upgrade, maintain, and repair the cluster, and the opportunity to execute data-gathering across an area much larger than that afforded by an individual harvester (e.g., radio astronomy, 3D tracking of and recording of the communication patterns of marine mammals, etc.). The computational tasks can be shared and distributed among a compute grid implemented in part by a collection of individual floating self-propelled energy harvesters thereby providing many benefits related to cost and efficiency that are unavailable to relatively isolated energy harvesters, and likewise unavailable to terrestrial compute grids of the prior art.

A method for the maintenance of a first wind energy installation from a group of wind energy installations. In the method, a future maintenance time period is identified in which a boost power of the group of wind energy installations is greater than a prescribed threshold value, wherein the boost power results from a wind speed predicted for the future maintenance time period, said wind speed being greater than a rated wind speed. The power of the first wind energy installation is reduced after the start of the maintenance time period and a boost power is drawn from a plurality of wind energy installations from the group of wind energy installations. A maintenance process is carried out at the first wind energy installation. The invention furthermore relates to a control unit suitable for carrying out the method.

The present invention relates to a method allowing short-term prediction of the wave motion (force, elevation, . . . ), from a time series of past wave measurements. The prediction method according to the invention is based on the estimation of the variable coefficients of an autoregressive model while allowing multi-step minimization, that is over a horizon of several time steps in the future, of the prediction error.

A computer system and method for improving the accuracy of predictions of the amount of renewable energy, such as solar energy and wind energy, available to an electric utility, and/or refine such predictions, by providing improved integration of meteorological forecasts. Coefficient values are calculated for a renewable energy generation model by performing a regression analysis with the forecasted level of renewable energy posted by the utility, forecasted weather conditions and measures of seasonality as explanatory variables. Accuracy is further enhanced through the inclusion of a large number of time series variables that reflect the systematic nature of the energy/weather system. The model also uses the original forecast posted by the system operator as well as variables to control for season.

A method for protecting a wind turbine from extreme and fatigue loads associated with high wind speed events includes receiving, via a wind turbine condition estimator programmed in a turbine controller of the wind turbine, operating data indicative of current wind turbine operation. Further, the method includes determining, via the wind turbine condition estimator, a plurality of estimated wind turbine conditions at the wind turbine by solving a control algorithm having one or more equations using the operating data. The estimated wind turbine conditions include, at least, an estimated wind speed at the wind turbine and a loading proxy of the wind turbine. As such, the method includes implementing, via the turbine controller, a corrective action only when each of the estimated wind turbine conditions indicates that one or more loading conditions of the wind turbine exceeds a predetermined limit.