Design of Fractional Order Controller for Microgrid Based on Model Analysis

Li, Peike; Zheng, Min; Zhong, Daxing; Yang, Zheng; Zhang, Guangfeng

doi:10.23919/ccc52363.2021.9550290

Cited by 1 publication

(1 citation statement)

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“…Performance criteria are used to prove this by calculating the area of the control. One such method is used is Integral Time Absolute Error (ITAE), which can be tabulated to evaluate the system with ease of understanding [16][17][18][19]. It is important that, if fluctuations occur, the system must return to its nominal value.…”

Section: Introductionmentioning

confidence: 99%

A Novel Solution for Solving the Frequency Regulation Problem of Renewable Interlinked Power System Using Fusion of AI

Kader

Akindeji

2022

Energies

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The requirement for clean energy has increased drastically over the years due to the emission of CO2 and the degrading of the environment by introducing Renewable Energy Systems (RES) into the existing power grid. While these systems are a positive change, they come at a cost, with some issues relating to the stability of the grid and feasibility. Hence, this research paper closely investigates the modeling and interlinking of photovoltaic (PV)-based solar power and Double-Fed Induction Generator (DFIG)-based wind turbines with the conventional power systems. RES has been known to contribute to a highly non-linear system and complexity. To return the power systems to their original state after a load disturbance, a novel control technique based on the fractional-order Type-2 Fuzzy logic system, well developed via particle swarm optimization (PSO), has been utilized for solving the frequency control problem of a renewable interlinked power system. The efficacy of the proposed technique is validated for various possible operating conditions and the system results are compared with some of the recent methods with and without including non-linearity, and the performance of the controllers is superimposed on frequency/time graphs for ease of understanding to show the benefits of the proposed research work.

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Section: Introductionmentioning

confidence: 99%