Disclosed is a wind turbine layout optimization method combining with a dispatching strategy for the wind farm. In the wind farm micro-siting stage, the installed wind turbines number and the arrangement positions are optimized. In this method, the dispatching strategy of wind turbines is considered during the layout optimization of wind turbines, and the axial induction factor of each wind turbine is introduced into the layout optimization variables. The dispatching strategy of maximizing the wind farm power generation is combined with the layout optimization of wind turbines in the construction stage of the wind farm, so that the wake effect is effectively reduced and the capacity cost is reduced, which meet the requirement of actual wind farm. A hybrid optimization algorithm is proposed in this method, with a greedy algorithm to optimize the turbine number and a particle swarm optimization (PSO) algorithm to refine the turbine layout scheme.

Methods and apparatus for reducing peak power consumption of a grid connected power plant having a plurality of wind turbines. In response to determining that a power production value of the power plant is below a power threshold, one method includes: after a first time delay of a first group of one or more wind turbines, control the first group to operate in a power saving mode for a predefined first power saving period; and after a first time delay of a second group of one or more other wind turbines, control the second group to operate in the power saving mode for a predefined second power saving period. The first time delay of the first group is less than the first time delay of the second group and the power saving mode inhibits a power consuming activity for the wind turbines operating in the power saving mode.

A test and control apparatus, system and method for a wind farm, are provided. The test and control apparatus includes a first communication interface, a second communication interface, and a processor card. The processor card receives, via the first communication interface, a frequency regulation instruction issued by the grid scheduling server, receives operation information of the wind power generation unit via the second communication interface, and calculates, based on the operation information of the wind power generation unit, a first frequency regulation capability of the wind power generation unit performing a frequency regulation without using the first energy storage battery. The processor card sends the frequency regulation instruction to the wind power generation unit without using the first energy storage battery, in a case that the first frequency regulation capability of the wind power generation unit satisfies a requirement of the frequency regulation instruction.

A method for determining an available power of a wind farm, wherein the wind farm comprises a plurality of wind power installations with a rotor having rotor blades, the blade angle of which can be adjusted is provided. A wind farm which is set up to carry out the method for determining an available power is provided. The method comprises providing a shading matrix which determines at least one effective wind speed of each of the wind power installations in the wind farm as a function of at least one wind speed and wind direction and wind farm throttling using a park wake model. The method makes it possible to accurately determine an available power of a wind farm even when the wind farm is operated with throttled power.

Systems and methods enable yaw offsets on wind turbines in a wind farm. A wind turbine yaw controller receives a present wind direction signal from a local wind direction sensor and aligns the wind turbine in a substantially perpendicular direction based upon the present wind direction signal. A yaw controller is retrofitted between the wind direction sensor and the yaw controller to provide an adjusted wind direction signal to the yaw controller based upon the present wind direction signal and a yaw offset signal. An offset table relating yaw offsets with wind direction signal values may be stored locally at a wind turbine or at a site controller in communication with the wind tribune. Each wind turbine in the wind farm may be retrofitted with the yaw controller to enhance the power output of the wind farm by adjusting the wake effect between wind turbines of the wind farms.

A method and an apparatus for controlling noise of multiple wind turbines. The method includes: determining a noise-influencing sector of each of the multiple wind turbines, based on positions of the multiple wind turbines and a position of a noise-influencing site; acquiring a current wind direction; determining whether there is at least one wind turbine of the multiple wind turbine under the current wind direction operating in the noise-influencing sector; and limiting output power of the at least one wind turbine, in a case that the determination is positive.

Provided is a method of feeding electric reactive power using a wind farm comprising wind turbines. The wind farm feeds a wind farm active power output and the wind farm active power output includes individual plant active power outputs each generated by one of the wind turbines. The wind farm feeds a wind farm reactive power output into the electrical supply network and the wind farm reactive power output includes individual plant reactive power outputs each generated by one of the wind turbines. The method includes determining a total wind farm reactive power output to be fed in by the wind farm and calculating, for each wind turbine, an individual plant reactive power output to be generated. The individual plant reactive power output is determined depending on the individual plant active power output and depending on the wind farm reactive power output to be fed in.

A method for determining a yaw position offset of a wind turbine (1) is provided. A neighbouring wind turbine (2) of the wind farm is identified, the neighbouring wind turbine (2) being arranged in the vicinity of the wind turbine (1). Produced power data and/or wind speed data from the wind turbine (1) and from the neighbouring wind turbine (2), is obtained during a period of time, and a yaw position offset of the wind turbine (1) is derived, based on the obtained produced power data and/or wind speed data, and based on the geographical positions of the wind turbine (1) and the neighbouring wind turbine (2). A local maximum and a local minimum being separated by an angular difference in yaw position being substantially equal to 180°.

A method for detecting anomalies during operation of an asset to improve performance of the asset includes collecting, via a server, data relating to operation of the asset or a group of assets containing the asset. The data includes normal and abnormal asset behavior of the asset or the group of assets containing the asset. Further, the method includes automatically removing, via an iterative algorithm programmed in the server that utilizes one or more inputs or outputs of an anomaly detection analytic, portions of the data containing the abnormal asset behavior to form a dataset containing only the normal asset behavior. The method also includes training, via a computer-based model programmed in the server, the anomaly detection analytic using, at least, the dataset containing only the normal asset behavior. Moreover, the method includes applying, via the server, the anomaly detection analytic to the asset so as to monitor for anomalies during operation thereof.

An optimal dispatching method and system for a wind power generation and energy storage combined system are provided. Uncertainty of a wind turbine output is characterized based on spatio-temporal coupling of the wind turbine output and an interval uncertainty set. Compared with a traditional symmetric interval uncertainty set, the uncertainty set that considers spatio-temporal effects effectively excludes some extreme scenarios with a very small probability of occurrence and reduces conservativeness of a model. A two-stage robust optimal dispatching model for the wind power generation and energy storage combined system is constructed, and a linearization technology and a nested column-and-constraint generation (C&CG) strategy are used to efficiently solve the model.