[go: up one dir, main page]

Morsi et al., 2015 - Google Patents

Model predictive control of a wind turbine based on linear parameter-varying models

Morsi et al., 2015

View PDF
Document ID
7897283803234445672
Author
Morsi A
Abbas H
Mohamed A
Publication year
Publication venue
2015 IEEE Conference on Control Applications (CCA)

External Links

Snippet

This paper demonstrates the application of a low conservative model predictive control (MPC) scheme based on linear parameter-varying (LPV) models to control a utility scale wind turbine. The main objective of the controller is to allow the wind turbine to extract from …
Continue reading at www.researchgate.net (PDF) (other versions)

Classifications

    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GASES [GHG] EMISSION, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/70—Wind energy
    • Y02E10/72—Wind turbines with rotation axis in wind direction
    • Y02E10/723—Control of turbines
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/0205—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric not using a model or a simulator of the controlled system
    • G05B13/024—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric not using a model or a simulator of the controlled system in which a parameter or coefficient is automatically adjusted to optimise the performance
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GASES [GHG] EMISSION, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02E60/70—Systems integrating technologies related to power network operation and communication or information technologies mediating in the improvement of the carbon footprint of electrical power generation, transmission or distribution, i.e. smart grids as enabling technology in the energy generation sector not used, see subgroups
    • Y02E60/76—Computer aided design [CAD]; Simulation; Modelling
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B17/00—Systems involving the use of models or simulators of said systems
    • G05B17/02—Systems involving the use of models or simulators of said systems electric

Similar Documents

Publication Publication Date Title
Karad et al. Recent trends of control strategies for doubly fed induction generator based wind turbine systems: A comparative review
Huang et al. Maximum power point tracking strategy for large-scale wind generation systems considering wind turbine dynamics
Geng et al. Output power control for variable-speed variable-pitch wind generation systems
Mirzaei et al. Robust model predictive control of a wind turbine
Kayedpour et al. Model predictive control with a cascaded Hammerstein neural network of a wind turbine providing frequency containment reserve
Ebadollahi et al. Wind turbine torque oscillation reduction using soft switching multiple model predictive control based on the gap metric and Kalman filter estimator
Ma et al. Optimal real-time control of wind turbine during partial load operation
Jin et al. Semi-definite programming for power output control in a wind energy conversion system
Kazda et al. Model-optimized dispatch for closed-loop power control of waked wind farms
Shaltout et al. An adaptive economic model predictive control approach for wind turbines
Burkart et al. Nonlinear control of wind turbines: An approach based on switched linear systems and feedback linearization
Gionfra et al. Combined feedback linearization and MPC for wind turbine power tracking
Almaged et al. Design of an integral fuzzy logic controller for a variable-speed wind turbine model
Jalilian et al. Load Frequency Control Resilience of Hybrid Power System with Renewable Energy Sources and Superconducting Magnetic Energy Storage Using FO-Fuzzy-PID Controller
Morsi et al. Model predictive control of a wind turbine based on linear parameter-varying models
Benlahrache et al. Fault tolerant control of wind turbine using robust model predictive min-max approach
Iordanov et al. Can a Wind Turbine Learn to Operate Itself? Evaluation of the potential of a heuristic, data-driven self-optimizing control system for a 5MW offshore wind turbine
Schlipf Prospects of multivariable feedforward control of wind turbines using lidar
Goyal et al. A critical study of pitch control techniques used for horizontal axis wind turbines
Dang et al. A multi-objective optimal nonlinear control of variable speed wind turbine
AlSoud et al. Linear parameter varying robust control for wind turbine power regulation
Tang et al. Robust control of wind turbines to reduce wind power fluctuation
Shaltout et al. An economic model predictive control approach using convex optimization for wind turbines
Lasheen et al. Robust model predictive control for collective pitch in wind energy conversion systems
Rezaei et al. Robust adaptive fault tolerant pitch control of wind turbines