A system and method are provided for damping power system oscillations in a power system network having one or more local inverter-based generators within a plant, the plant connected to a grid at a point of intersection (POI). The system and method include a plant-level controller or local controller that receives one or more grid signals having a characteristic indicative of a power system oscillation. The plant-level controller or local controller generates an auxiliary signal from the grid signals that is used by the local controller of the inverter-based generators. At the local controller, the auxiliary signal is used to modulate reactive power output from the inverter-based generator to change a voltage at the POI, the voltage change damping the power system oscillations.

An example method comprises receiving historical wind turbine failure data and asset data from SCADA systems, receiving first historical sensor data, determining healthy assets of the renewable energy assets by comparing signals to known healthy operating signals, training at least one machine learning model to indicate assets that may potentially fail and to a second set of assets that are operating within a healthy threshold, receiving first current sensor data of a second time period, applying a machine learning model to the current sensor data to generate a first failure prediction a failure and generate a list of assets that are operating within a healthy threshold, comparing the first failure prediction to a trigger criteria, generating and transmitting a first alert if comparing the first failure prediction to the trigger criteria indicates a failure prediction, and updating a list of assets to perform surveillance if within a healthy threshold.

A method and a device for checking the integrity of modules of a technical facility. The technical facility has multiple modules and sets of controls for controlling the technical facility. For starting up each set of controls and the overall technical facility, a master key is used which is utilized for decrypting an encrypted region of the set of controls. The master key for starting up a set of controls of the technical facility is derived from features of all sets of controls installed in the technical facility, and a start or a start-up of the technical facility can take place only when the master key is found to be satisfactory.

The present disclosure is directed to a system and method for assessing farm-level performance of a wind farm. The method includes operating the wind farm in a first operational mode and identifying one or more pairs of wind turbines having wake interaction. The method also includes generating a pairwise dataset for the wind turbines pairs. Further, the method includes generating a first wake model based on the pairwise dataset and predicting a first farm-level performance parameter based on the first wake model. The method also includes operating the wind farm in a second operational mode and collecting operational data during the second operational mode. Moreover, the method includes predicting a first farm-level performance parameter for the second operational mode using the first wake model and the operational data from the second operational mode. The method further includes determining a second farm-level performance parameter during the second operational mode. Thus, the method includes determining a difference in the farm-level performance of the wind farm as a function of the first and second farm-level performance parameters.

Provided are a power control method and apparatus for a wind farm. The power control method includes: calculate an adjustable power range for each wind turbine according to a current power output state of each wind turbine in the wind farm, in response to receiving a whole-farm active power adjustment signal for the wind farm sent by a power grid; and calculate a power allocated to each wind turbine based on the adjustable power range for each wind turbine and a whole-farm target power indicated by the whole-farm active power adjustment signal, so as to generate an active power adjustment command and send the generated active power adjustment command to each wind turbine.

A control system for a dynamic system including at least one measurement sensor. The system includes at least one computing device configured to generate and transmit at least one regulation device command signal to at least one regulation device to regulate operation of the dynamic system based upon at least one inferred characteristic.

The disclosure relates to a method for operating a wind turbine. The method comprises providing several software modules as an operating software for operating the wind turbine, wherein the software modules each have at least one communications input and/or at least one communications output, as well as providing a configuration list with several entries, wherein the entries assign to a respective communications input of a software module a communications output of another software module. For each entry, the method further comprises transmitting information of the respective entry to a software module of the software modules with at least one communications input which allows the software module to access data of the communications output of another software module, which in the entry is assigned to the communications input, and operating the wind turbine with the software modules. The disclosure further relates to a computer program product, a wind turbine controller for a wind turbine, and a wind turbine with a controller.

The present disclosure is directed to a system and method for micrositing a wind farm having a plurality of wind turbines. The method includes (a) determining, via a loads optimization function, one or more wind directions with or without turbine shadow for each of the wind turbines in the wind farm, (b) determining, via the loads optimization function, at least one additional wind parameter for each of the wind directions, (c) calculating, via simulation, loads for each of the wind turbines in the wind farm based on the identified wind directions with or without turbine shadow for each of the wind turbines in the wind farm and the at least one additional wind parameter for each of the wind directions, and (d) determining a site layout for the wind farm based on the calculated loads.

The application involves a stability evaluation method and system of direct-drive wind turbine generator, which belongs to the technical field of wind power generation. It solves the problems of poor stability of direct-drive wind turbine generator, low safety performance, failure to realize mutual cooperation between online stability evaluation and parameter adjustment in the existing technology. Firstly, the variation of direct-drive wind turbine generator terminal voltage, current, power and PLL angle of direct-drive wind turbine generator is measured, the terminal energy and the energy negative gradient of direct-drive wind turbine generator is calculated. Then, the system stability is assessed according to the value of energy negative gradient, the influence of the critical parameters on system stability is analyzed and the preliminary adjustment strategy is proposed. It realizes the mutual cooperation between stability level evaluation and parameter adjustment, and improves the working efficiency of the system.

A wind turbine is provided. The wind turbine includes a plurality of control systems. The wind turbine further includes a reflective memory system. The plurality of control systems is coupled with the reflective memory system. Each of the plurality of control systems may include a respective memory of the reflective memory system. In response to data being written into one of the respective memories, the reflective memory system may automatically replicate the data to other respective memories.