National Technology & Engineering Solutions of Sandia, LLC

Sandia Corporation

Michigan Technological University

South Dakota Board of Regents

Other

Rush D Robinett, Iii

David G Wilson

Giorgio Bacelli

Ossama Abdelkhalik

Wayne W Weaver

Steven F Glover

John T Feddema

Ryan Geoffrey Coe

Shangyan Zou

Steven Y Goldsmith

Gordon G Parker

Clark R Dohrmann

Umesh Korde

John E Hurtado

Ben J Petterson

Kenneth N Groom

Mark R Vaughn

Raymond H Byrne

Tu Anh Nguyen

Madelyn G Veurink

Jiajun Song

Don M Van Zuiden

John R Phelan

Ronald Matthews

Diana L Bull

A DC bus collection system for a wind farm reduces the overall required number of converters and minimizes the energy storage system requirements. The DC bus collection system implements a power phasing control method between wind turbines that filters the variations and improves power quality. The phasing control method takes advantage of a novel power packet network concept with nonlinear power flow control design techniques that guarantees both stable and enhanced dynamic performance.

Wind turbine power phase control with DC collection bus for onshore/offshore windfarms

One of the biggest challenges for all renewable energy sources (RES) is that they are variable power generators which will require reactive power or energy storage systems (ESS) to provide reliable power quality (ideally power factor of one) at the power grid generation side. The present invention is directed to a power packet network (PPN) for integrating wave energy converter (WEC) arrays into microgrids. Specifically, an array of WECs can be physically positioned such that the incoming regular waves will produce an output emulating an N-phase AC system such that the PPN output power is constant. ESS requirements are thereby minimized whilst maintaining grid stability with high power quality. This will enable RES integration onto a future smart grid for large-scale adoption and cost reduction while preserving high efficiency, reliability, and resiliency.

Power packet networks for wave energy converter arrays

A nonlinear control design technique capitalizes on a wave energy converter comprising a shaped buoy having a variable geometry wave energy. For example, the shaped buoy can have an hourglass (HG) geometry having a variable cone or steepness angle. The HG buoy is assumed to operate in the heave motion of the wave. The unique interaction between the HG buoy and the wave creates a nonlinear cubic storage effect that produces actual energy storage or reactive power during operation. A multi-frequency Bretschneider spectrum wave excitation input was simulated for the HG design both with constant and varying steepness angle profiles which demonstrated further increased power generation with changing sea states for the variable design.

Wave energy converter buoy with variable geometry

Increased energy harvesting is realized using a nonlinear buoy geometry for reactive power generation. By exploiting the nonlinear dynamic coupling between the buoy geometry and the potential wideband frequency spectrum of incoming waves in the controller/buoy design, increased power can be captured in comparison to conventional wave energy converter designs. In particular, the reactive power and energy storage system requirements are inherently embedded in the nonlinear buoy geometry, therefore requiring only simple rate-feedback control.

Nonlinear hydrostatic control of a wave energy converter

Pulsed power loads (PPLs) are highly non-linear and can cause significant stability and power quality issues in an electrical microgrid. According to the present invention, many of these issues can be mitigated by an Energy Storage System (ESS) that offsets the PPL. The ESS can maintain a constant bus voltage and decouple the generation sources from the PPL. For example, the ESS specifications can be obtained with an ideal, band-limited hybrid battery and flywheel system.

Energy storage systems for electrical microgrids with pulsed power loads

The present invention is directed to a nonlinear controller for nonlinear wave energy converters (WECs). As an example of the invention, a nonlinear dynamic model is developed for a geometrically right-circular cylinder WEC design for the heave-only motion, or a single degree-of-freedom (DOF). The linear stiffness term is replaced by a nonlinear cubic hardening spring term to demonstrate the performance of a nonlinear WEC as compared to an optimized linear WEC. By exploiting the nonlinear physics in the nonlinear controller, equivalent power and energy capture, as well as simplified operational performance is observed for the nonlinear cubic hardening spring controller when compared to an optimized linear controller.

Nonlinear controller for nonlinear wave energy converters

A method for designing feedforward and feedback controllers for integration of stochastic sources and loads into a nonlinear networked AC/DC microgrid system is provided. A reduced order model for general networked AC/DC microgrid systems is suitable for HSSPFC control design. A simple feedforward steady state solution is utilized for the feedforward controls block. Feedback control laws are provided for the energy storage systems. A HSSPFC controller design is implemented that incorporates energy storage systems that provides static and dynamic stability conditions for both the DC random stochastic input side and the AC random stochastic load side. Transient performance was investigated for the feedforward/feedback control case. Numerical simulations were performed and provided power and energy storage profile requirements for the networked AC/DC microgrid system overall performance. The HSSPFC design can be implemented in the Matlab/Simulink environment that is compatible with real time simulation/controllers.

Nonlinear power flow control for networked AC/DC microgrids

Multi-resonant control of a 3 degree-of-freedom (heave-pitch-surge) wave energy converter enables energy capture that can be in the order of three times the energy capture of a heave-only wave energy converter. The invention uses a time domain feedback control strategy that is optimal based on the criteria of complex conjugate control. The multi-resonant control can also be used to shift the harvested energy from one of the coupled modes to another, enabling the elimination of one of the actuators otherwise required in a 3 degree-of-freedom wave energy converter. This feedback control strategy does not require wave prediction; it only requires the measurement of the buoy position and velocity.

Multi-resonant feedback control of multiple degree-of-freedom wave energy converters

A multi-resonant wide band controller decomposes the wave energy converter control problem into sub-problems; an independent single-frequency controller is used for each sub-problem. Thus, each sub-problem controller can be optimized independently. The feedback control enables actual time-domain realization of multi-frequency complex conjugate control. The feedback strategy requires only measurements of the buoy position and velocity. No knowledge of excitation force, wave measurements, nor wave prediction is needed. As an example, the feedback signal processing can be carried out using Fast Fourier Transform with Hanning windows and optimization of amplitudes and phases. Given that the output signal is decomposed into individual frequencies, the implementation of the control is very simple, yet generates energy similar to the complex conjugate control.

Multi-resonant feedback control of a single degree-of-freedom wave energy converter

A parametric excitation dynamic model is used for a three degrees-of-freedom (3-DOF) wave energy converter. Since the heave motion is uncoupled from the pitch and surge modes, the pitch-surge equations of motion can be treated as a linear time varying system, or a linear system with parametric excitation. In such case the parametric exciting frequency can be tuned to twice the natural frequency of the system for higher energy harvesting. A parametric excited 3-DOF wave energy converter can harvest more power, for both regular and irregular waves, compared to the linear 3-DOF. For example, in a Bretschneider wave, the harvested energy in the three modes is about 3.8 times the energy harvested in the heave mode alone; while the same device produces about 3.1 times the heave mode energy when using a linear 3-DOF model.

Model predictive control of parametric excited pitch-surge modes in wave energy converters

A controller for an electric power storage device is described herein, wherein the electric power storage device is included in a microgrid. The electric power storage device has at least one of a charge rate, a discharge rate, or a power retention capacity that has been customized for a collective microgrid. The at least one of the charge rate, the discharge rate, or the power retention capacity of the electric power storage device is computed based at least in part upon specified power source parameters in the at least two connected microgrids and specified load parameters in the at least two connected microgrids.

Controller for a customized electric power storage device in a collective microgrid

The invention provides optimal control of a three-degree-of-freedom wave energy converter using a pseudo-spectral control method. The three modes are the heave, pitch and surge. A dynamic model is characterized by a coupling between the pitch and surge modes, while the heave is decoupled. The heave, however, excites the pitch motion through nonlinear parametric excitation in the pitch mode. The invention can use a Fourier series as basis functions to approximate the states and the control. For the parametric excited case, a sequential quadratic programming approach can be implemented to numerically solve for the optimal control. The numerical results show that the harvested energy from three modes is greater than three times the harvested energy from the heave mode alone. Moreover, the harvested energy using a control that accounts for the parametric excitation is significantly higher than the energy harvested when neglecting this nonlinear parametric excitation term.

Pseudo-spectral method to control three-degree-of-freedom wave energy converters

A wave energy converter and method for extracting energy from water waves maximizes the energy extraction per cycle by estimating an excitation force of heave wave motion on the buoy, computing a control force from the estimated excitation force using a dynamic model, and applying the computed control force to the buoy to extract energy from the heave wave motion. Analysis and numerical simulations demonstrate that the optimal control of a heave wave energy converter is, in general, in the form of a bang-singular-bang control; in which the optimal control at a given time can be either in the singular arc mode or in the bang-bang mode. The excitation force and its derivatives at the current time can be obtained through an estimator, for example, using measurements of pressures on the surface of the buoy in addition to measurements of the buoy position. A main advantage of this approximation method is the ease of obtaining accurate measurements for pressure on the buoy surface and for buoy position, compared to wave elevation measurements.

Optimal control of wave energy converters

A Hamiltonian surface shaping power flow control (HSSPFC) method is used to analyze the meta-stability and adjust pulsed power loads on a DC electric power distribution network. Pulsed power loads are nonlinear, time-variant systems that cause nonlinear limit-cycles. During the on periods of a pulsed load, the system can be in an unstable state and is damped back to stability during the off state of the load. Therefore, over the entire period of the pulse the system may only be assessed as meta-stable. As shown through simulation, HIL and hardware results, the HSSPFC method is more accurate than the other small-signal approaches, such as Eigenvalues, Nyquist, and Floquet theory, and can reveal important details about the transient responses and performance.

Method to provide meta-stable operation of a DC microgrid comprising a pulsed load

A Unified Power Flow Controller described herein comprises a sensor that outputs at least one sensed condition, a processor that receives the at least one sensed condition, a memory that comprises control logic that is executable by the processor; and power electronics that comprise power storage, wherein the processor causes the power electronics to selectively cause the power storage to act as one of a power generator or a load based at least in part upon the at least one sensed condition output by the sensor and the control logic, and wherein at least one operating parameter of the power electronics is designed to facilitate maximal transmittal of electrical power generated at a variable power generation system to a grid system while meeting power constraints set forth by the electrical power grid.

Growing community of inventors

Tijeras, NM, United States of America

Rush D Robinett, Iii