A control network for a wind turbine system, the wind turbine system comprising multiple rotor-nacelle assemblies mounted on a support structure, the control network comprising: a respective local network associated with each rotor-nacelle assembly, each local network comprising multiple nodes; a central network that is connected to each local network, the central network comprising multiple nodes; and a synchronisation synchronization device that synchronizes data transmission throughout the control network.

A system and method are provided for controlling a power generating system having at least one power generating subsystem connected to a point of interconnection (POI). A first data signal is obtained corresponding to a feedback signal of an electrical parameter regulated at the POI, the first data signal having a first signal fidelity. A second data signal indicative of the electrical parameter generated at the power generating subsystem is obtained, the second data signal having a second signal fidelity that is higher than the first signal fidelity. A correlation value between the first and second data signals is obtained by filtering a value difference between the first and second data signals. The correlation value is applied to a setpoint value for the electrical parameter regulated at the POI. The modified setpoint value and the second data signal are combined to generate a setpoint command for the power generating subsystem that is used for controlling generation of power at the power generating subsystem to regulate the electrical parameter at the POI.

Disclosed is a method of condition monitoring a WTG (Wind Turbine Generator) comprising acts of collecting and storage of at least the following data sets together with their time stamps. Collection of generator power production measurements. Collection of mechanical status measurements. Collection of generator torque measurements. Collection of nacelle direction measurements. Collection of meteorological conditions measurements. The method compromises a further act of synchronizing the data sets. The invention also relates to a system for condition monitoring a WTG. The invention further relates to a system for visually inspecting a WTG.

Disclosed is a method of condition monitoring a WTG (Wind Turbine Generator) comprising acts of collecting and storage of at least the following data sets together with their time stamps. Collection of generator power production measurements. Collection of mechanical status measurements. Collection of generator torque measurements. Collection of nacelle direction measurements. Collection of meteorological conditions measurements. The method compromises a further act of synchronizing the data sets. The invention also relates to a system for condition monitoring a WTG. The invention further relates to a system for visually inspecting a WTG.

Control of a multi-rotor wind turbine system. A local controller is arranged for each wind turbine module and implementing a local model predictive control (MPC) routine. A central controller is arranged to determine a set of operational constraints of the wind turbine modules. Based on a current operational state of the wind turbine module and the set of operational constraints, one or more predicted operational trajectories are calculated and used for controlling the wind turbine module.

A reinforcement learning method executed by a computer includes calculating a degree of risk for a state of a controlled object at a current time point with respect to a constraint condition related to the state of the controlled object, the degree of risk being calculated based on a predicted value of the state of the controlled object at a future time point, the predicted value being obtained from model information defining a relationship between the state of the controlled object and a control input to the controlled object; and determining the control input to the controlled object at the current time point, from a range defined according to the calculated degree of risk so that the range becomes narrower as the calculated degree of risk increases.

Estimating components of a grid impedance, Z, of a power grid being coupled to a power generating unit at a point of interconnection is disclosed. A voltage, Vmeas, across the point of interconnection; an active current, IP, and/or an active power, P, delivered by the power generating unit to the power grid; and a reactive current, IQ, and/or a reactive power, Q, delivered by the power generating unit are determined. A parameter estimation vector is estimated using a recursive adaptive filter algorithm, and on the basis of Vmeas, IP, P, IQ and/or Q. A model representation of the power grid is created on the basis of the parameter estimation vector, and a system DC gain vector for the power grid is calculated, using the model representation. Finally, Z, and/or a resistance, R, of Z, and/or a reactance, X, of Z, is derived from the system DC gain vector.

A method for evaluating resonance stability of a flexible direct current (DC) transmission system in an offshore wind farm includes: establishing an s-domain equivalent circuit of a flexible DC transmission system in an offshore wind farm, constructing an s-domain node admittance matrix of the flexible DC transmission system in the offshore wind farm, determining a resonant mode of the system based on a zero root of a determinant of the node admittance matrix, and determining stability of the system. In the method, an s-domain impedance model is used to describe dynamic characteristics of a wind turbine, a flexible DC converter, and other power devices, avoiding coupling between device modeling and an operation mode of the system. In addition, the node admittance matrix is used for analysis so as to fully consider a plurality of power electronic devices and a grid structure of the offshore wind farm, realizing comprehensive analysis.

The application relates to an oscillation active damping control method and system for grid-tied type-4 wind turbine generator. The method comprises: based on an interconnection model of multiple subsystems, constructing a stored energy function and a dissipated energy function of a current inner loop control subsystem, and interaction energy functions between the current inner loop control subsystem and other subsystems are constructed, then establishing an energy feedback model of Type-4 wind turbine generator; when the oscillation occurs, obtaining instantaneous angular frequency of the PLL, and then based on the energy feedback model, adjusting the current reference value of the q-axis current inner loop generated by the reactive power outer loop control subsystem, to make the stored energy function decrease with time, so as to suppress the oscillation.

According to embodiments described herein control of the auxiliary power system in a hybrid power plant is provided by determining a grid-draw threshold from an external power grid; monitoring power consumption for powered systems of the hybrid power plant; monitoring power generation of the hybrid power plant; discharging an alternative power source of one or more of an Energy Storage System (ESS) and an auxiliary generator in response to the power consumption exceeding the grid-draw threshold; and implementing prediction algorithms for power generation of the hybrid power plant and the power consumption. Accordingly, a source of power is managed between several alternative sources and the external power grid to meet plant operator defined criteria when maintaining power in various wind speed conditions.