Frequency Support of Smart Grid Using Fuzzy Logic-Based Controller for Wind Energy Systems

Simões, Marcelo Godoy; Bubshait, Abdullah

doi:10.3390/en12081550

Cited by 9 publications

(10 citation statements)

References 49 publications

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“…The membership functions are iteratively tuned by the system simulation and experiment. Similar Mamdani-type fuzzy logic controller for the primary frequency regulation of a wind farm can be found in [34].…”

Section: A Fuzzy Logic-based Controllermentioning

confidence: 99%

An Overview of Artificial Intelligence Applications for Power Electronics

Zhao

Blaabjerg

Wang

2021

IEEE Trans. Power Electron.

501

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This paper gives an overview of the Artificial Intelligence (AI) applications for power electronic systems. The three distinctive life-cycle phases, design, control, and maintenance are correlated with one or more tasks to be addressed by AI, including optimization, classification, regression, and data structure exploration. The applications of four categories of AI are discussed, which are expert system, fuzzy logic, metaheuristic method, and machine learning. More than 500 publications have been reviewed to identify the common understandings, practical implementation challenges, and research opportunities in the application of AI for power electronics. This paper is accompanied by an Excel file listing the relevant publications for statistical analytics.

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Section: A Fuzzy Logic-based Controllermentioning

confidence: 99%

An Overview of Artificial Intelligence Applications for Power Electronics

Zhao

Blaabjerg

Wang

2021

IEEE Trans. Power Electron.

501

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“…After obtaining a certain amount of primary reserve, WTs can participate in the primary frequency control. In order to enable WTs to support frequency regulation of the power grid, a dynamic droop controller based on fuzzy logic is designed in [16].…”

Section: P Mppmentioning

confidence: 99%

Adaptive Frequency Responsive Control for Wind Farm Considering Wake Interaction

Lyu

Jia

Dong

2021

Journal of Modern Power Systems and Clean Energy

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With the increasing share of wind power, it is expected that wind turbines would provide frequency regulation ancillary service. However, the complex wake effect intensifies the difficulty in controlling wind turbines and evaluating the frequency regulation potential from the wind farm. We propose a novel frequency control scheme for doubly-fed induction generator (DFIG)-based wind turbines, in which the wake effect is considered. The proposed control scheme is developed by incorporating the virtual inertia control and primary frequency control in a holistic way. To facilitate frequency regulation in timevarying operation status, the control gains are adaptively adjusted according to wind turbine operation status in the proposed controller. Besides, different kinds of power reserve control approaches are explicitly investigated. Finally, extensive case studies are conducted and simulation results verify that the frequency behavior is significantly improved via the proposed control scheme.Index Terms--Doubly-fed induction generator (DFIG) -based wind turbine, virtual inertia control, primary frequency control, power reserve control, wake interaction.

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“…For both the antecedent and consequent, the degree of fulfillment is determined by the membership functions. The type of fuzzy inference scheme is categorized as Mamdanitype [30,[32][33][34][35] and Takagi-Sugeno-Kang-type (TSK-type) [31,[36][37][38]. For the Mamdani-type fuzzy inference scheme, the membership function of the antecedent and the consequent are shape-based functions, e.g., triangular.…”

Section: B Fuzzy Logicmentioning

confidence: 99%

An overview of artificial intelligence applications for power electronics

Blaabjerg¹,

Wang²

2020

Preprint

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<div>This is a preprint version of the manuscript submitted to IEEE on June 4, 2020.</div><div><br></div><div>This paper gives an overview of the Artificial Intelligence (AI) applications for power electronic systems. The three distinctive life-cycle phases, design, control, and maintenance are correlated with one or more tasks to be addressed by AI, including optimization, classification, regression, and data structure exploration. The applications of four categories of AI are discussed, which are expert system, fuzzy logic, metaheuristic method, and machine learning. More than 500 publications have been reviewed to identify the common understandings, practical implementation challenges, and research opportunities in the application of AI for power electronics.<br></div>

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Frequency Support of Smart Grid Using Fuzzy Logic-Based Controller for Wind Energy Systems

Cited by 9 publications

References 49 publications

An Overview of Artificial Intelligence Applications for Power Electronics

An Overview of Artificial Intelligence Applications for Power Electronics

Adaptive Frequency Responsive Control for Wind Farm Considering Wake Interaction

An overview of artificial intelligence applications for power electronics

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