Adaptive Type-2 Fuzzy PID LFC for an Interconnected Power System Considering Input Time-Delay

Sabahi, Kamel; Hajizadeh, Amin; Tavan, Mehdi; Feliachi, A.

doi:10.1007/s40815-020-01017-2

Cited by 5 publications

(1 citation statement)

References 44 publications

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“…In [39], type-2 fuzzy controller was used to efficiently distribute electricity among various energy storages in solar power outlets. A type-2 fuzzy observer-based technique has been put up by authors in [40] for scheduling and managing the energy utilisation of hybrid storages. An adaptive type-2 fuzzy PID controller that takes input time delays into account has been presented by authors in [41] for the purpose of LFC of a connected power system.…”

Section: Review Of Literaturementioning

confidence: 99%

Type‐2 fuzzy‐based adaptively predictive controlled variable frequency transformer coordinated to SMES for improved load frequency control

Manzoor,

Mufti,

Bakhsh

et al. 2024

IET Generation Trans & Dist

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Traditionally, phase shifters powered by power electronics are used in conjunction with energy storage devices to improve the load frequency control. Conventional phase shifters provide minimal inertia and offer a significant threat to power quality due to harmonics. This study suggests the type‐2 fuzzy based adaptively predictive controlled variable frequency transformer (F2‐APC‐VFT) as a phase shifter to work in coordination with superconducting magnetic energy storage (SMES) for improved load frequency control. To assess the effectiveness of coordinated control, a two‐area, four‐machine linked power system with F2‐APC‐VFT installed in succession with the connecting line near to area one and SMES in the other area is employed. A type‐2 fuzzy controller is used to tune the cost function weights of the adaptive predictive controller (APC). A simulation study is conducted in MATLAB to show the effectiveness of the suggested strategy. Tuning the cost function weights with a type‐2 fuzzy controller considerably impacts in minimising the frequency and tie‐power deviations. The effectiveness of the F2‐APC is verified by comparing its performance with that of an adaptive neuro fuzzy inference system (ANFIS) controller and constant weight‐based adaptive predictive controller (C‐APC).

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Section: Review Of Literaturementioning

confidence: 99%

Type‐2 fuzzy‐based adaptively predictive controlled variable frequency transformer coordinated to SMES for improved load frequency control

Manzoor,

Mufti,

Bakhsh

et al. 2024

IET Generation Trans & Dist

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Predictive control of interconnected fractional‐order systems with communication delays: An application for load frequency control of power system

Mohammadikia,

Tavakoli‐Kakhki

2024

Asian Journal of Control

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This research focuses on constrained model predictive control (CMPC) problem for interconnected fractional‐order systems (IFOS). Communication delays and imposed disturbances are considered in the design procedure of the control system. The dynamic equations of the IFOS are reformulated to handle the interaction delays and to obtain a model for the overall system. Then, a constrained model predictive controller is designed for the input and output (I/O) oriented model of the IFOS. To solve this control problem, a quadratic programming algorithm is utilized to obtain the optimal solution. Since most of the power systems exhibit an interconnected structure and consist of several subsystems, this study considers the load frequency control (LFC) problem for an interconnected fractional‐order power system in the presence of communication delays to evaluate the proposed technique. Numerical simulations are provided for two different cases, and the results are reported.

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Reinforcement Fuzzy Q-Learning Incorporated with Genetic Kinematics Analysis for Self-organizing Holonomic Motion Control of Six-Link Stewart Platforms

Huang

Chen

et al. 2023

Int. J. Fuzzy Syst.

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Adaptive Type-2 Fuzzy PID LFC for an Interconnected Power System Considering Input Time-Delay

Cited by 5 publications

References 44 publications

Type‐2 fuzzy‐based adaptively predictive controlled variable frequency transformer coordinated to SMES for improved load frequency control

Type‐2 fuzzy‐based adaptively predictive controlled variable frequency transformer coordinated to SMES for improved load frequency control

Predictive control of interconnected fractional‐order systems with communication delays: An application for load frequency control of power system

Reinforcement Fuzzy Q-Learning Incorporated with Genetic Kinematics Analysis for Self-organizing Holonomic Motion Control of Six-Link Stewart Platforms

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