Hybrid MPC-Based Automatic Generation Control for Dominant Wind Energy Penetrated Multisource Power System

Hasan, Naimul; Alsaidan, Ibrahim; Sajid, Mohammad; Khatoon, Shahida; Farooq, Shuaib

doi:10.1155/2022/5526827

Cited by 7 publications

(5 citation statements)

References 33 publications

(34 reference statements)

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“…These data are then used to learn the type-2 fuzzy system (based on a neural network or using evolutionary algorithms). For more information on the type-2 fuzzy system and its equations, see [35,36].…”

Section: Predictive Controller Designmentioning

confidence: 99%

“…Some researchers have also used secondary frequency control over the converter of renewable energy production sources to control the frequency [34]. One of the control methods that has been successful in all engineering fields is model predictive control (MPC) [35,36]. This control method is based on predicting the system behavior (from the mathematical model of the system) and generating a control signal to minimize the error.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive Intelligent Model Predictive Control for Microgrid Load Frequency

et al. 2022

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In this paper, self-tuning model predictive control (MPC) based on a type-2 fuzzy system for microgrid frequency is presented. The type-2 fuzzy system calculates the parameters and coefficients of the control system online. In the microgrid examined, there are sources of photovoltaic power generation, wind, diesel, fuel cells (with a hydrogen electrolyzer), batteries and flywheels. In simulating the load changes, changes in the production capacity of solar and wind resources as well as changes (uncertainty) in all parameters of the microgrid are considered. The performances of three control systems including traditional MPC, self-tuning MPC based on a type-1 fuzzy system and self-tuning MPC based on a type-2 fuzzy system are compared. The results show that type-2 fuzzy MPC has the best performance, followed by type-1 fuzzy MPC, with a slight difference between the two results.

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Section: Predictive Controller Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Adaptive Intelligent Model Predictive Control for Microgrid Load Frequency

et al. 2022

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“…In [11],a cascade-fractional order secondary controller is suggested to reach the goals of the AGC when the system integrated with renewables. A hybrid MPC is suggested in [12] to reach the goals of the AGC when the system integrated with renewables.…”

Section: Introductionmentioning

confidence: 99%

Frequency Control of Interconnected Power System via SBO assisted Simultaneous Tuning Strategy in Presence of DFIG

A. Ravi Shankar

2024

jes

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To achieve the objectives of the automatic generation control (AGC) of wind integrated interconnected power system (WIIPS), better tuning and control strategies are required. This paper suggests simultaneous tuning strategy for the AGC and wind system controllers to improve the stability of the WIIPS. The bulk amount of wind is integrated into the grid using the doubly fed induction generator (DFIG) and its simplified model is used to simulate the WIIPS. Initially, classical controllers are opted in AGC mechanism to reduce the frequency disturbances caused by the load and wind generation uncertainties. Further, classical controllers of WIIPS are replaced with cascade controllers to enhance the system frequency profile during the disturbances. The optimal set of solutions of the classical and cascade controllers are examined by the satin bowerbird optimizer (SBO) with the help of integral square error as fitness function of the optimization problem. Comparisons are provided to show the merits of the WIIPS over normal interconnected power system, cascade controller over classical controller and simultaneous tuning strategy over regular tuning mechanism.

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“…With a typical controller set to a single functional form, it isn't easy to establish stability across the system's whole working range due to its nonlinearity. To solve this problem and efficiently run the power generating units, frequency, and tie-line power flow, intelligent control technology such as the FLC is advised over the traditional one [15]. The Fuzzy logic controller increases the traditional controller's closed-loop effectiveness and can manage every variation in operational points by modifying controller parameters live.…”

Section: Introductionmentioning

confidence: 99%

“…The researchers' primary focus in the combined AGC experiments has been designing the ALFC loop controller. The auxiliary controller of the ALFC loop, like traditional PID, fuzzy-PID, and Neuro-fuzzy-PID, with HVDC, has been done in the integrated LFC and automatic voltage regulator (AVR) inner loops in the work done in [15,16]. Abazari et al [17] demonstrated load frequency control Power Systems using a classical PID & Fuzzy PID controller.…”

Section: Introductionmentioning

confidence: 99%

A Novel Adaptive Neuro-Fuzzy Based Cascaded PIDF-PIDF Controller for Automatic Generation Control Analysis of Multi-Area Multi-Source Hydrothermal System

Ramshanker¹,

Ravi²,

Edward³

et al. 2022

Preprint

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This article investigated the Automatic Generation Control(AGC) of multi-area multi-source interconnected systems with hydropower plants, thermal power plants, and wind energy. Adaptive Neuro-fuzzy controller integrated with the cascaded proportional-integral-derivative with filter (PIDF-PIDF) is a new cascaded controller (ANF-PIDF-PIDF) that has been presented as a secondary controller for applied hybrid power systems. The recent Skill Optimization Algorithm (SOA) is employed to optimize PIDF- PIDF controller parameter gains and the Adaptive Neuro-Fuzzy controller's inputs and output scaling factors. SOA is used to update the controller parameters with integral square error (ISE) employed as the objective function. A 1% step load disturbance was considered simultaneously in all three areas. The controller's performance is evaluated and compared with and without considering the effects of wind energy sources and non-linearity for ANF-PIDF-PIDF, PIDF-PIDF, and PIDF and it was determined that the ANF-PIDF-PIDF was the most efficient. The dynamic system performance is also compared with parallel high voltage direct current (HVDC) tie-lines. The investigation clearly shows that incorporating HVDC tie-line with multi-area, multi-source provides better dynamic performance in maximum amplitude, oscillation, and settling time. Additionally, sensitivity analysis is done and the optimum controller gains does not need to be reset to uncertain values in system loading conditions. All simulation results were evaluated using MATLAB 2016b.

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Hybrid MPC-Based Automatic Generation Control for Dominant Wind Energy Penetrated Multisource Power System

Cited by 7 publications

References 33 publications

Adaptive Intelligent Model Predictive Control for Microgrid Load Frequency

Adaptive Intelligent Model Predictive Control for Microgrid Load Frequency

Frequency Control of Interconnected Power System via SBO assisted Simultaneous Tuning Strategy in Presence of DFIG

A Novel Adaptive Neuro-Fuzzy Based Cascaded PIDF-PIDF Controller for Automatic Generation Control Analysis of Multi-Area Multi-Source Hydrothermal System

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