The invention discloses improved versions of a horizontal axis wind turbine and new fundamental methodologies for the design of wind turbines, which are capable of extracting both kinetic and thermal energy from the wind. The wind turbines use a large diameter forward inlet fairing to accelerate the airflow to the more effective outer radii of the turbine rotor where the airflow is constrained by an airfoil-shaped flow control ring, which also serves to prevent rotor tip losses, to inhibit wake expansion, and to accelerate the airflow through the turbine. A similarly large diameter aft pressure recovery fairing promotes rotation and contraction of the wake downstream of the turbine. Further methodologies for optimization and an algorithm for detail design are disclosed.

A method is provided for controlling a wind power plant, in particular in case of a frequency drop in a utility grid to which the wind turbines are connected, the method including: Combining demand response, inertial response and spinning reserve for given wind speeds in order for wind power plants to deliver fast aggregate under frequency response for a wide wind speed range with minimal recovery time and minimal production loss at each wind speed. In case of the frequency drop the utility grid is additional stabilized by active power, which is provided from a static VAR-compensator and which is fed into the grid. The static VAR-compensator is connected with the wind turbine via a transmission system. The static VAR-compensator is based on using super-capacitors thus it can provide an amount of active power for grid support in case of the frequency drop.

The present disclosure is directed to systems and methods for automatically calibrating a load sensor system of a wind turbine and determining health of same. In one embodiment, the method includes receiving a plurality of sensor signals generated by the plurality of load sensors from the load sensor system. The method also includes determining, via a computer model, a load estimation of the wind turbine based on the sensor signals, turbine geometry, and one or more additional input parameters (e.g. rotor azimuth angle, pitch angle, rotor position, etc.). Another step includes comparing the load estimation to a load measurement to determine one or more correlation coefficients. Thus, the method also includes calibrating the plurality of sensors in the load sensor system based on the correlation coefficients.

An improved turbine over the old horizontal and vertical axis turbines because of its ability to capture several times the amount of wind. The basic design and process of this new machine can also work in the ocean at capturing ocean currents. Being Omni-directional (not having to turn into the wind) gives it one efficiency over the 3 bladed turbine. Another efficiency all embodiments have is its frictionless exponent. This quality helps save on wear and tear and maintenance cost. Most if not all past turbines have a static presents, being built in one basic wind capturing position. This new turbine is more dynamic because it can hide from wind damage and then open to capture more wind than its predecessors.

The invention relates to a method for establishing a sectional or modular wind turbine blade. The method comprises the steps of transporting at least two blade sections of said wind turbine blade and a mobile factory for joining blade sections to a location at or in proximity of a wind turbine site, positioning said blade sections with two blade section ends facing each other and supported on a platform in said mobile factory, moving said platform in relation to the ground at the location for levelling said platform, aligning said blade section ends in relation to each other, and establishing said sectional or modular wind turbine blade by joining blade sections in an area of connection at said blade section ends. The invention also relates to a system for establishing a sectional or modular wind turbine blade and a mobile factory for joining sections of a wind turbine blade.

The Vertical Axle or Axis Helically Swept Blade Wind Turbine, is by definition a vertical wind turbine using a blade or blades shaped as a spiral, with one side of the blade flat, the other side serving as an airfoil to create desired overall torque, all around its full turn, or integer number of full turns, using this the same cross section all along its stretch. Among its intrinsic advantages are; Simplicity, Greater Electric Power Output related to swept area facing the wind, Earlier “kick in” for lower wind speeds, Wind Direction Independent, Ease of Maintenance, due to ground level access to most of its components and Self-Controlling by definition. All of these advantages combined, make harnessing the wind power using this invention, more cost-effective in a multitude of aspects.

Structural preform layers of multiple rigid unidirectional strength elements or rods are constructed and arranged for use in fabricating load-bearing support structures and reinforcements of wind turbine blades. Individual preform layers include multiple elongate unidirectional strength elements or rods arranged in a single layer along a longitudinal axis of the preform layer. Each preform layer includes one or more fibrous carrier layers to which the multiple strength elements or rods are joined and arranged in the single layer. Each strength element or rod is longitudinally oriented and adjacent to other elements or rods. Individual strength elements or rods include a mass of substantially straight unidirectional structural fibers embedded within a matrix resin such that the elements or rods have a substantially uniform distribution of fibers and high degree of fiber collimation. The relative straightness of the fibers and fiber collimation provide strength elements or rods and the preform layers with high rigidity and significant compression strength.

A system for providing electrical power to a facility includes a generator configured to generate electrical power for the facility when a drive-shaft of the generator is rotated. A motor is configured to provide torque to rotate the generator drive-shaft and to be driven by a first power supply. A mechanical energy provider is configured to provide torque to the drive-shaft using mechanical energy generated from an intermittent local power source. The system is configured to defer to the mechanical energy provider to rotate the drive-shaft such that, when the intermittent local power source is active, less power is needed from the first power supply to power the motor than when the intermittent local power source is inactive.

A rotor blade includes a first blade segment and a second blade segment extending in opposite directions from a chord-wise joint. Each of the first and second blade segments has at least one shell member defining an airfoil surface. The first blade segment includes a beam structure having a receiving end with at least one span-wise extending pin extending therefrom. The second blade segment includes a receiving section that receives the beam structure. The receiving section includes a chord-wise member having a pin joint slot defined therethrough. The pin joint slot receives the span-wise extending pin at the receiving end of the beam structure so as to secure the first and second blade segments together. Moreover, the chord-wise member, the pin joint slot, and/or the span-wise extending pin includes at least one compliant structure formed of a compliant material that allows a deformation thereof to follow a shear deformation of the rotor blade.

A system for generating power includes an environmental engine that determines performance metrics for a plurality of wind turbines deployed at a plurality of windfarms, such that each windfarm includes a corresponding subset of the plurality of windfarms. The performance metrics for a given wind turbine of the plurality of wind turbines characterizes wind flowing over blades of the given wind turbine. The system includes an artificial intelligence (AI) ensemble engine operating on the one or more computing devices that generates a set of models for each wind turbine of the plurality of wind turbines, wherein each model of each set of models is generated with a different machine learning algorithm and selects, for each respective set of models, a model with a highest efficiency metric. The AI engine provides edge computing systems operating at the plurality of windfarms with a selected model and corresponding recommended operating parameters.