Grid Mode Selection Scheme based on a Novel Fractional Order Proportional Resonant Controller for Hybrid Renewable Energy Resources

Perumal, Vimala; Kannan, Saravanan Kanagasabai; Balamurugan, C. R.

doi:10.1080/15325008.2023.2202674

Cited by 3 publications

(1 citation statement)

References 40 publications

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“…To solve this problem, a hybrid green energy system that combines many energy ISSN: 2088-8694  sources is developed [7]. This article seeks to present and critically evaluate an in-depth review of hybrid renewable energy sources (HRES) [8]. Additionally, the article examines various approaches utilized in every category [9].…”

Section: Introductionmentioning

confidence: 99%

Distributed voltage unbalance mitigation in islanded microgrid using moth flame optimization and firebug swarm optimization

Gandikoti,

Jha,

Jha

et al. 2024

IJPEDS

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In recent trends, hybrid renewable energy sources (HRES) provide a better solution to meet energy demand, maximizing the productivity of electricity network. Due to the above-mentioned features, several researchers have given more attention to PV-wind-based HRES systems. A stable energy supply must be added, including batteries, diesel generator (DG), to meet demand in the event of a grid failure. To meet the voltage unbalance in islanded mode, the sizes of DG have need to be selected sensibly and HRES requires additional energy storage. To examine the voltage unbalance problems of an islanded microgrid, a hybrid optimization approach known as moth flame optimization (MFO) and firebug swarm optimization (FSO) is introduced. Due to various loads, harmonic distortion causes the voltage to unbalance, which can result in voltage collapse. To deliver a quick response in an island mode, a comprehensive algorithm called MFO-FSO control is proposed. MATLAB software is used to validate the results which demonstrate that the proposed MFO-FSO outperforms the conventional decoupling double synchronous reference frame (DDSRF) methods by reducing total harmonic distortion (THD) up to 1.21% and voltage unbalance factor (VUF) up to 1.427%.

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Section: Introductionmentioning

confidence: 99%

Distributed voltage unbalance mitigation in islanded microgrid using moth flame optimization and firebug swarm optimization

Gandikoti,

Jha,

Jha

et al. 2024

IJPEDS

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Voltage Controller Design for Offshore Wind Turbines: A Machine Learning-Based Fractional-Order Model Predictive Method

Safari,

Hassanzadeh Yaghini,

Kharrati

et al. 2024

Fractal Fract

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Integrating renewable energy sources (RESs), such as offshore wind turbines (OWTs), into the power grid demands advanced control strategies to enhance efficiency and stability. Consequently, a Deep Fractional-order Wind turbine eXpert control system (DeepFWX) model is developed, representing a hybrid proportional/integral (PI) fractional-order (FO) model predictive random forest alternating current (AC) bus voltage controller designed explicitly for OWTs. DeepFWX aims to address the challenges associated with offshore wind energy systems, focusing on achieving the smooth tracking and state estimation of the AC bus voltage. Extensive comparative analyses were performed against other state-of-the-art intelligent models to assess the effectiveness of DeepFWX. Key performance indicators (KPIs) such as MAE, MAPE, RMSE, RMSPE, and R2 were considered. Superior performance across all the evaluated metrics was demonstrated by DeepFWX, as it achieved MAE of [15.03, 0.58], MAPE of [0.09, 0.14], RMSE of [70.39, 5.64], RMSPE of [0.34, 0.85], as well as the R2 of [0.99, 0.99] for the systems states [X1, X2]. The proposed hybrid approach anticipates the capabilities of FO modeling, predictive control, and random forest intelligent algorithms to achieve the precise control of AC bus voltage, thereby enhancing the overall stability and performance of OWTs in the evolving sector of renewable energy integration.

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Direct Fractional-Order Adaptive Control Design for Cascaded Doubly-Fed Induction Generator (CDFIG) in a Wind Energy System

Djebbri,

Ladaci

2024

Wseas Transactions on Power Systems

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This paper is devoted to a fractional-order model reference adaptive control (FO-MRAC) synthesis for the independent control of the active and reactive power flows in the cascaded doubly fed induction generator (CDFIG) in wind energy systems. The proposed adaptive control law combines a second-order-like fractional reference model and a direct MIT adaptation law using a fractional order integrator. This generator configuration can be an interesting alternative to standard double-output wound rotor induction generators. It is made up of two identical wound rotor induction motors such that their rotors are mechanically and electrically coupled. Using two cascaded induction machines permits the elimination of the brushes and copper rings in the traditional doubly-fed induction generator DFIG, which makes the system more resistant and reduces maintenance costs. In the first step, we propose a classical PI controller synthesis to regulate the active and reactive power produced by CDFIG. Then, the FO-MRAC design is realized and a comparative study based on numerical simulations is performed between the classical regulators PI, MRAC, and FO- MRAC, to demonstrate the superiority of the proposed fractional-order adaptive controller relative to conventional integer order PI and MRAC controllers. These results illustrate the reliability and efficiency of the proposed adaptive control scheme.

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Grid Mode Selection Scheme based on a Novel Fractional Order Proportional Resonant Controller for Hybrid Renewable Energy Resources

Cited by 3 publications

References 40 publications

Distributed voltage unbalance mitigation in islanded microgrid using moth flame optimization and firebug swarm optimization

Distributed voltage unbalance mitigation in islanded microgrid using moth flame optimization and firebug swarm optimization

Voltage Controller Design for Offshore Wind Turbines: A Machine Learning-Based Fractional-Order Model Predictive Method

Direct Fractional-Order Adaptive Control Design for Cascaded Doubly-Fed Induction Generator (CDFIG) in a Wind Energy System

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