Abstract:
Embodiments of the invention provide methods, systems, and apparatus for determining a property of wind approaching a wind turbine. A light detection and ranging equipment may be used to determine a property of the wind at a plurality of locations ahead of a turbine. A wind flow model may be used to determine the property of wind expected at the rotor of the wind turbine based on the readings of the light detection and ranging device.
Abstract:
Wind turbines of a wind power plant may be selectively over-rated by measuring the difference between the nominal and actual power plant outputs and deriving an over-rating request signal based on that difference which is sent to each turbine. The same value may be sent to each turbine. Alternatively, each turbine may be given its own over-rating amount based on an optimization of the turbine. Over-rating may also be used when external economic factors such as energy costs are sufficiently high to out-weigh any potential harmful effect of over-rating. The fatigue lifetime of turbines and their critical components may also be taken into account when deciding whether and to what extent to implement an over-rating command.
Abstract:
A wind turbine has a Lidar device to sense wind conditions upstream of the wind turbine including wind speed, direction and turbulence. Signals from the Lidar are processed to detect an event which could give rise to low cycle fatigue loading on one or more components of the wind turbine. On detection the system controller takes the necessary evasive action depending on the nature and severity of the extreme condition detected. This may include a significant reduction in power generated through reduction in rotor speed or torque, complete shutdown of the generator and yawing of the nacelle and rotor in response to a change in wind direction.
Abstract:
A method of controlling combustion in an homogenous charge compression ignition engine through indirect mechanisms. The method utilizes a predictive model so that combustion can be controlled over a wide range of operating conditions while maintaining optimum operation with respect to efficiency and emissions. The methods include an adaptive aspect, which allows the predictive model to be updated if deemed necessary. Furthermore, the methods include a model with a plurality of control modes. A control mode can be chosen to optimize the engine for one of a plurality of output characteristics, including response time, efficiency, or emissions characteristics.
Abstract:
There is described a method for controlling a system, for example a Diesel engine, that is subject to transient changes of target outputs. The target outputs specify outputs required from the system. “Steady state” information is used to give optimum inputs for the system when the target outputs are substantially constant. A model of the system is used to predict the outputs of the system in response to candidate new values for the inputs of the system. The method combines the steady state information with the predicted response of the system to determine inputs to the system which will cause the system outputs to match the target outputs as closely as possible. For each candidate (in one embodiment), the method calculates the difference between the steady state inputs and a candidate, and the difference between the target outputs and the predicted outputs that would result from the adoption of that candidate, to determine an optimum candidate which is then used to update the inputs to the system.
Abstract:
The application describes a wind turbine having a control method and controller for performing predictive control of a wind turbine generator. Based on the measured instantaneous wind speed, it is known to provide control signals to a wind turbine in order to control the pitch of the wind turbine rotor blades and the speed of the generator. However, it is difficult using instantaneous wind speed measurements to achieve smooth control, due to finite response speeds of the associated electro-mechanical systems, as well as the constantly changing control system inputs. The predictive control system described in the application assumes a model of generator speed based on the values of the incident wind speed v(t) and the values of a control signal u(t) output to the wind turbine in a feed forward loop. Here, the control signal can be for one or more of controlling either the power setting of the generator, or the pitch angle of the rotor blades. The predictive controller uses a rolling time series of values for v(t) and u(t) and based on a predicted response of the generator speed w(t) optimizes the time series control signal u(t). The predicted response of the generator speed w(t) is based on model, that can be refined in real time as the wind turbine operates.
Abstract:
A wind turbine has a Lidar device to sense wind conditions upstream of the wind turbine. Signals from the wind turbine are processed to detect an extreme event. On detection the system controller takes the necessary evasive action depending on the nature and severity of the extreme condition detected. This may include a significant reduction in power generated, complete shutdown of the generator and yawing of the nacelle and rotor to reduce loading on the rotor blades.
Abstract:
Embodiments of the invention generally relate to using remote sensing equipment such as a Light Detection and Ranging (LIDAR) device to detect wind characteristics for use by wind turbines of a wind park. A wind park controller may received raw wind data from the remote sensing device and determine one or more turbines that can use the raw wind data. The raw wind data may be converted to customized data for each of the one or more wind turbines. Upon being provided the customized wind data, the one or more wind turbines may adjust one or more operational characteristics to improve power production or avoid damage to turbine components.
Abstract:
A wind turbine has a Lidar device to sense wind conditions upstream of the wind turbine. Wind speed signals from the wind turbine are processed to detect an extreme operating gust. The detection is performed by differentiating the axial wind velocity and filtering for a period of time. On detection of extreme operating gust the system controller takes necessary evasive action which may include shutting down the turbine or varying the blade pitch angle.
Abstract:
A wind turbine has a scanning Lidar arranged on the nacelle. The Lidar has a single scanning beam which scans about a substantially vertical axis to sense wind related data in a measurement volume a predetermined distance from the Lidar. Fast Fourier transforms of data from a plurality of points in the measurement volume are analysed to derive a peak velocity and a measure of variance. A controller receives the peak velocity and measure of variance as inputs and generates an output if the controller determines that the input data shows that the wind conditions are such that damage to the wind turbine is likely.