Perturbation estimation based robust state feedback control for grid connected DFIG wind energy conversion system-Reference-Cited by-同舟云学术

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Perturbation estimation based robust state feedback control for grid connected DFIG wind energy conversion system

Published:2017-08 Issue:33 Volume:42 Page:20994-21005
ISSN:0360-3199
Container-title:International Journal of Hydrogen Energy
language:en
Short-container-title:International Journal of Hydrogen Energy

Author:

Yang Bo,Hu Yilin,Huang Haiyan,Shu Hongchun,Yu Tao,Jiang Lin

Funder

National Basic Research Program of China

National Natural Science Foundation of China

Yunnan Provincial Talents Training Program

Scientific Research Foundation of Yunnan Provincial Department of Education

Publisher

Elsevier BV

Subject

Energy Engineering and Power Technology,Condensed Matter Physics,Fuel Technology,Renewable Energy, Sustainability and the Environment

Reference27 articles.

1. How does hydrogen-based renewable energy change with economic development? Empirical evidence from 32 countries;Wang;Int J Hydrogen Energy,2017

2. An integrated decision support model for design and operation of a wind-based hydrogen supply system;Kim;Int J Hydrogen Energy,2017

3. The implications of energy systems for ecosystem services: a detailed case study of offshore wind;Hooper;Renew Sustain Energy Rev,2017

4. Performances analysis of WT-DFIG with PV and fuel cell hybrid power sources system associated with hydrogen storage hybrid energy system;Tamalouzt;Int J Hydrogen Energy,2016

5. Advanced control for wind energy conversion systems with flywheel storage dedicated to improving the quality of energy;Hamzaoui;Int J Hydrogen Energy,2016

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1. Optimal Adaptive Fractional Order Integral Sliding Mode Controller-Energy Management Strategy for Electric Vehicles Based on Bald Eagle Search Algorithm;International Journal of Energy Research;2024-02-20

2. Single-Loop Robust Decoupling Control Base on Perturbation Estimation for DC-Based DFIG;IEEE Access;2024

3. Stabilization of DFIG-based wind turbine with active and reactive power: A coupling memory state-feedback control scheme;Information Sciences;2023-11

4. Adaptive reinforcement learning interval type II fuzzy fractional nonlinear observer and controller for a fuzzy model of a wind turbine;Engineering Applications of Artificial Intelligence;2023-08

5. D-decomposition-based multi-objective robust resilient control for blade pitch of wind energy conversion system;International Journal of Electrical Power & Energy Systems;2023-03

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