H-Infinity Loop-Shaping Controller for Load Frequency Control of a Deregulated Power System

Davidson, Roger A.; Ushakumari, S.

doi:10.1016/j.protcy.2016.08.172

Cited by 26 publications

(13 citation statements)

References 4 publications

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“…Various controlling methodologies and strategies of load frequency control (LFC) of single and interconnected EPSs have been extensively reported in the literature which can be classified into: (i) conventional and classical controllers, (ii) artificial intelligence controllers, (iii) meta-heuristic based-on controllers, (iv) hybridisation of these methods, and (v) recently, model predictive based on controllers. Among classical controllers, H-∞ based loop-shaping method [5,6], sliding mode based controllers [7][8][9], and fuzzy logic based control strategies [10][11][12] are employed for solving LFC problem of interconnected EPSs. It is worth mentioning that these aforesaid controllers have few shortcomings such as: designer experience is essential, longer computational time, and complex design procedures.…”

Section: Introductionmentioning

confidence: 99%

Design of robust model predictive controllers for frequency and voltage loops of interconnected power systems including wind farm and energy storage system

Othman

El‐Fergany

2018

IET Generation, Transmission & Distribution

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Section: Introductionmentioning

confidence: 99%

Design of robust model predictive controllers for frequency and voltage loops of interconnected power systems including wind farm and energy storage system

Othman

El‐Fergany

2018

IET Generation, Transmission & Distribution

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“…The value of γ represents the accuracy factor within which the loop gain approaches the desired value, as explained by Davidson and Ushakumari (2016).…”

Section: Design Of H∞ Controllermentioning

confidence: 99%

H∞ tracking control for an inverted pendulum

Kumar

Kanthalakshmi

2018

Journal of Vibration and Control

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The objective of this paper is to design an [Formula: see text] controller for an inverted pendulum system, synthesized using the [Formula: see text] loop shaping technique. In the [Formula: see text] loop shaping technique, a linear plant model is augmented with certain weight functions, such as the sensitivity weight function and complementary sensitivity weight function, so that the closed loop transfer function of the plant will have the desired performance. In this work, the [Formula: see text] controller is synthesized and the analysis on robustness and performance of the system is done by taking the singular value response and robustness indicator plots.

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“…Another LFC, based on the model predictive control for a hybrid power system taking into consideration the effect of governor and turbine parameters variation, was presented in [27,28]. Whereas a decentralized LFC was implemented in [29] based on H-infinity to control the frequency of a deregulated power system. In addition, fractional-order PID controllers were introduced by some authors to solve the LFC problem in multi-area systems [30][31][32].…”

Section: Introductionmentioning

confidence: 99%

Optimal Fuzzy PIDF Load Frequency Controller for Hybrid Microgrid System Using Marine Predator Algorithm

et al. 2021

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This paper presents a fully optimized fuzzy proportional-integral-derivative with filter (FPIDF) load frequency controller (LFC) for enhancing the performance of a hybrid microgrid system. The Marine Predator Algorithm (MPA), a recent optimization algorithm, is used to optimize the gains as well as the input scaling factors and membership functions of the proposed fuzzy PIDF controller. The controller performance is tested on a two-area hybrid microgrid system containing various renewable energy sources and energy storage devices. The effectiveness of the MPA based FPIDF controller is compared with conventional PIDF and FPIDF controllers based on other heuristic techniques presented in literatures. Moreover, different scenarios are implemented in this study to verify the robustness and sensitivity of the proposed controller to different step load perturbations, system parameters variations, wind speed fluctuation and solar irradiance variation. The dynamic response of the system is compared using different controllers in terms of settling time, maximum overshoot and undershoot values. The results are presented in the form of time domain simulations conducted via MATLAB/SIMULINK. INDEX TERMSFuzzy control, load frequency control, marine predator algorithm, microgrid system, PIDF controller, renewable energy, storage systems. NOMENCLATURE A Rotor swept area ACE Area control error B1, B2 Frequency bias coefficients BES Battery energy storage CE Change of error Predator step size control ratio Power coefficient COR Competition over resources E Error FF Fitness function FLC Fuzzy logic controller FPIDF Fuzzy proportional-integral-derivative with filter G Solar radiation ( ) Controller transfer function Solar irradiance under standard test conditions 1 , 2 Input scaling gains 12

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H-Infinity Loop-Shaping Controller for Load Frequency Control of a Deregulated Power System

Cited by 26 publications

References 4 publications

Design of robust model predictive controllers for frequency and voltage loops of interconnected power systems including wind farm and energy storage system

Design of robust model predictive controllers for frequency and voltage loops of interconnected power systems including wind farm and energy storage system

H∞ tracking control for an inverted pendulum

Optimal Fuzzy PIDF Load Frequency Controller for Hybrid Microgrid System Using Marine Predator Algorithm

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