Load frequency control for two-area hybrid microgrids using model predictive control optimized by grey wolf-pattern search algorithm

Amiri, Farhad; Hatami, Alireza

doi:10.1007/s00500-023-08077-0

Cited by 9 publications

(2 citation statements)

References 40 publications

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“…Wind turbines have several advantages as a stable source of electricity in power systems, such as: (1) abundant energy source: for electricity generation, wind turbines require an abundant wind energy source that is usually available day and night; (2) reduced environmental pollution: using wind turbines as a clean energy source reduces environmental pollution; (3) cost reduction in electricity production: the cost of electricity production with wind turbines is lower than that of fossil fuels. Despite these advantages, wind turbines in power systems have some drawbacks, including the complexity of load-frequency control (LFC) [4][5][6]. Wind turbines rely on wind, which is naturally fluctuating and can complicate LFC in power systems [7].…”

Section: Introductionmentioning

confidence: 99%

Improved Load Frequency Control in Power Systems Hosting Wind Turbines by an Augmented Fractional Order PID Controller Optimized by the Powerful Owl Search Algorithm

Amiri,

Eskandari,

Moradi

2023

Algorithms

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The penetration of intermittent wind turbines in power systems imposes challenges to frequency stability. In this light, a new control method is presented in this paper by proposing a modified fractional order proportional integral derivative (FOPID) controller. This method focuses on the coordinated control of the load-frequency control (LFC) and superconducting magnetic energy storage (SMES) using a cascaded FOPD–FOPID controller. To improve the performance of the FOPD–FOPID controller, the developed owl search algorithm (DOSA) is used to optimize its parameters. The proposed control method is compared with several other methods, including LFC and SMES based on the robust controller, LFC and SMES based on the Moth swarm algorithm (MSA)–PID controller, LFC based on the MSA–PID controller with SMES, and LFC based on the MSA–PID controller without SMES in four scenarios. The results demonstrate the superior performance of the proposed method compared to the other mentioned methods. The proposed method is robust against load disturbances, disturbances caused by wind turbines, and system parameter uncertainties. The method suggested is characterized by its resilience in addressing the challenges posed by load disturbances, disruptions arising from wind turbines, and uncertainties surrounding system parameters.

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Section: Introductionmentioning

confidence: 99%

Improved Load Frequency Control in Power Systems Hosting Wind Turbines by an Augmented Fractional Order PID Controller Optimized by the Powerful Owl Search Algorithm

Amiri,

Eskandari,

Moradi

2023

Algorithms

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“…However, the inverter-interfaced energy resources lack physical inertia which reduces the inertia constant of the autonomous microgrid. Therefore, the frequency dynamic of the autonomous microgrid is at risk of instability due to a drastic rate of change of frequency and large frequency nadir raised because of the limited inertia [2,3]. Battery energy storage systems (BESSs) are widely utilized and controlled to provide virtual inertia [4].…”

Section: Introductionmentioning

confidence: 99%

Virtual Inertia Control in Autonomous Microgrids via a Cascaded Controller for Battery Energy Storage Optimized by Firefly Algorithm and a Comparison Study with GA, PSO, ABC, and GWO

Amiri,

Eskandari,

Moradi

2023

Energies

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Modern (micro) grids host inverter-based generation units for utilizing renewable and sustainable energy resources. Due to the lack of physical inertia and, thus, the low inertia level of inverter-interfaced energy resources, the frequency dynamic is adversely affected, which critically impacts the stability of autonomous microgrids. The idea of virtual inertia control (VIC), assisted by battery energy storage systems (BESSs), has been presented to improve the frequency dynamic in islanded microgrids. This study presents the PD-FOPID cascaded controller for the BESS, a unique method for enhancing the performance of VIC in islanded microgrids. Using the firefly algorithm (FA), the settings of this controller are optimally tuned. This approach is robust to disruptions due to uncertainties in islanded microgrids. In several scenarios, the performance of the suggested approach is compared with those of other control techniques, such as VIC based on an MPC controller, VIC based on a robust H-infinite controller, adaptive VIC, and VIC based on an optimized PI controller. The simulation results in MATLAB show that the suggested methodology in the area of VIC is better than previous methods.

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Frequency regulation in microgrid using sliding mode control with event-triggering mechanism

Dev,

Anand,

Chauhan

et al. 2023

Electr Eng

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Load frequency control for two-area hybrid microgrids using model predictive control optimized by grey wolf-pattern search algorithm

Cited by 9 publications

References 40 publications

Improved Load Frequency Control in Power Systems Hosting Wind Turbines by an Augmented Fractional Order PID Controller Optimized by the Powerful Owl Search Algorithm

Improved Load Frequency Control in Power Systems Hosting Wind Turbines by an Augmented Fractional Order PID Controller Optimized by the Powerful Owl Search Algorithm

Virtual Inertia Control in Autonomous Microgrids via a Cascaded Controller for Battery Energy Storage Optimized by Firefly Algorithm and a Comparison Study with GA, PSO, ABC, and GWO

Frequency regulation in microgrid using sliding mode control with event-triggering mechanism

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