Fuzzy Fractional-Order PID Control for PMSG Based Wind Energy Conversion System with Sparse Matrix Converter Topology

Abdulrazaq, Waleed Khaled Abdulrazaq; Vural, Ahmet Mete

doi:10.1155/2022/3663237

Cited by 4 publications

(3 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Las técnicas de control inteligente, tales como el control por lógica difusa o redes neuronales muestran una mejor capacidad de control y adaptabilidad para sistemas de mayor complejidad [12], [13]. Sin embargo, tienen como inconvenientes un elevado tiempo de procesamiento y la necesidad de conocimiento experto para su diseño [14].…”

Section: Introductionunclassified

Fractional-Order Control for Voltage Regulation in Bidirectional Converters: An Experimental Study

Parada-Salado,

Martinez-Patiño,

Pérez-Pinal

et al. 2024

IEEE Latin Am. Trans.

View full text Add to dashboard Cite

The theoretical application of fractional equations in controller development is not a new topic. The first efforts on this topic were reported in the late 1970s. However, in the last four years, a greater number of papers related to fractional control have been published than the one accumulated in previous years. Motivated by the above, this paper reports the step-by-step development of this type of control in a bidirectional converter. Furthermore, the discrete-time equivalent of the developed fractional control is implemented on Texas Instrument's F280042C digital signal processor. The experimental results of the discrete fractional compensator are compared with the experimental results of a conventional proportional integral derivative (PID) controller. The results show a notable improvement in the response of the bidirectional converter with the fractional control; specifically, faster responses and less overshoot in most of the experiments carried out. Also, the existing challenges facing the widespread application of this control technique are notorious and are extensively addressed in this article.

show abstract

Section: Introductionunclassified

Fractional-Order Control for Voltage Regulation in Bidirectional Converters: An Experimental Study

Parada-Salado,

Martinez-Patiño,

Pérez-Pinal

et al. 2024

IEEE Latin Am. Trans.

View full text Add to dashboard Cite

show abstract

“…Against the backdrop of the existing energy structure, the wind power's proportion of the power grid will continue to increase (Abdulrazaq and Vural, 2022;Xiong et al, 2022). Unlike traditional thermal power units, wind power output is influenced by external factors such as aging of internal devices, geographical environment, and meteorological conditions (Catalao et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Wind power output prediction: a comparative study of extreme learning machine

Wang,

Niu

2023

Front. Energy Res.

View full text Add to dashboard Cite

This study aims to propose a wind power prediction method that achieves high accuracy in order to minimize the impact of wind power on the power system and reduce scheduling difficulties in systems incorporating wind power. The importance of developing renewable energy has been recognized by society due to the increasing severity of the energy crisis. Wind energy offers advantages such as efficiency, cleanliness, and ease of development. However, the random nature of wind energy poses challenges to power systems and complicates the scheduling process. Therefore, accurate wind power prediction is of utmost importance. A wind power prediction model was constructed based on an improved tunicate swarm algorithm–extreme learning machine (ITSA-ELM). The improved tunicate swarm algorithm (ITSA) optimizes the random parameters of extreme learning machine (ELM), resulting in the best prediction performance. ITSA is an enhancement of the tunicate swarm algorithm (TSA), which introduces a reverse learning mechanism, a non-linear self-learning factor, and a Cauchy mutation strategy to address the drawbacks of poor convergence and susceptibility to local optima in TSA. Two different scenarios were used to verify the effectiveness of ITSA-ELM. The results showed that ITSA-ELM has a decrease of 1.20% and 21.67% in MAPE, compared with TSA-ELM, in May and December, respectively. This study has significant implications for promoting the development of renewable energy and reducing scheduling difficulties in power systems.

show abstract

“…In [14], a novel fractional-order controller was proposed for frequency regulation and real power fuctuation control but it did not explain how this controller is efective on ofine microgrid and their cost implication if any. Furthermore, a well-structured frequency control system based on proportional, integral, and derivative (PID) controller optimized through metaheuristic techniques for microgrid system comprising wind, hydro, solar, diesel, and thermal systems was conducted to give ultimate quick control response to system disturbances [15,16]. A malfunction lenient supervision for frequency and voltage was brought forward for a diesel engine machine applied on a microgrid.…”

Section: Introductionmentioning

confidence: 99%

Frequency Stability Enhancement of Microgrid Using Optimization Techniques-Based Adaptive Virtual Inertia Control

Yegon,

Singh

2023

International Transactions on Electrical Energy Systems

View full text Add to dashboard Cite

In recent years, a sharp increase in integration of renewable energy sources (RESs) in power system network has been observed. High penetration of RES interfaced with power electronics converters-inverters with reduced or no inherent inertia compromises modern power system’s overall stability. Due to low inertia, voltage and frequency deviations far off the allowable threshold occur. To overcome this challenge, an adaptive inertia control strategy based on optimization technique is proposed. The improved particle swarm optimization (PSO) and genetic algorithm (GA) optimization techniques-based PID controller has been used to generate the appropriate virtual inertia coefficient for effective emulation of inertia in the presence of energy storage system. The conventional PSO suffers local optima stagnation, resulting in premature convergence during searching process in order to achieve global and local position. To address this issue, the velocity update equation was modified on inertia weight (w) using an additional exponential term with linear decreasing inertia weight PSO (LDIW-PSO). In this paper, exponential power is taken strategically instead of squaring it in order to reduce the number of iterations for faster convergence. Finally, a microgrid based on wind and solar energy is simulated using MATLAB/Simulink where three cases, 2% disturbance, 3% disturbance, and 4% disturbance, have been considered. Here, the evaluation of proposed system is carried out based on four main performance indices (ITAE, IAE, ISE, and ITSE). Furthermore, validation was done through hardware prototype to get experimental results in real time. The results from MATLAB simulation and experimental setup are in sync.

show abstract

Fuzzy Fractional-Order PID Control for PMSG Based Wind Energy Conversion System with Sparse Matrix Converter Topology

Cited by 4 publications

References 45 publications

Fractional-Order Control for Voltage Regulation in Bidirectional Converters: An Experimental Study

Fractional-Order Control for Voltage Regulation in Bidirectional Converters: An Experimental Study

Wind power output prediction: a comparative study of extreme learning machine

Frequency Stability Enhancement of Microgrid Using Optimization Techniques-Based Adaptive Virtual Inertia Control

Contact Info

Product

Resources

About