Intelligent PI control technique in four area Load Frequency Control of interconnected hydro-thermal power system

Prakash, Surya; Sinha, Sayantan

doi:10.1109/icceet.2012.6203749

Cited by 17 publications

(15 citation statements)

References 11 publications

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“…The model network is used to predict the effect of controller changes on plant output, which allows the updating of controller parameters. In the study, the frequency deviations, tie-line power deviation and load perturbation of the area are chosen as the neural network controller inputs [21,22]. The outputs of the neural network are the control signals, which are applied to the governors in the area.…”

Section: Narma-l2 Controlmentioning

confidence: 99%

Neuro-Fuzzy Computational Technique to Control Load Frequency in Hydro-Thermal Interconnected Power System

Prakash

Sinha

2014

J. Inst. Eng. India Ser. B

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In this research work, two areas hydro-thermal power system connected through tie-lines is considered. The perturbation of frequencies at the areas and resulting tie line power flows arise due to unpredictable load variations that cause mismatch between the generated and demanded powers. Due to rising and falling power demand, the real and reactive power balance is harmed; hence frequency and voltage get deviated from nominal value. This necessitates designing of an accurate and fast controller to maintain the system parameters at nominal value. The main purpose of system generation control is to balance the system generation against the load and losses so that the desired frequency and power interchange between neighboring systems are maintained. The intelligent controllers like fuzzy logic, artificial neural network (ANN) and hybrid fuzzy neural network approaches are used for automatic generation control for the two area interconnected power systems. Area 1 consists of thermal reheat power plant whereas area 2 consists of hydro power plant with electric governor. Performance evaluation is carried out by using intelligent (ANFIS, ANN and fuzzy) control and conventional PI and PID control approaches. To enhance the performance of controller sliding surface i.e. variable structure control is included. The model of interconnected power system has been developed with all five types of said controllers and simulated using MATLAB/ SIMULINK package. The performance of the intelligent controllers has been compared with the conventional PI and PID controllers for the interconnected power system. A comparison of ANFIS, ANN, Fuzzy and PI, PID based approaches shows the superiority of proposed ANFIS over ANN, fuzzy and PI, PID. Thus the hybrid fuzzy neural network controller has better dynamic response i.e., quick in operation, reduced error magnitude and minimized frequency transients.

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Section: Narma-l2 Controlmentioning

confidence: 99%

Neuro-Fuzzy Computational Technique to Control Load Frequency in Hydro-Thermal Interconnected Power System

Prakash

Sinha

2014

J. Inst. Eng. India Ser. B

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“…The most common controller employed for AGC is based on classical control theory. These conventional controllers can be found in the researches [6][7][8][9]. These studies observed that an integral controller is very simple to implement and can provide zero steady state deviation.…”

Section: Introductionmentioning

confidence: 99%

Automatic Generation Control of Multi-area Interconnected Power Systems Using ANN Controller

Alzaareer¹,

Al-Shetwi²,

El-bayeh³

et al. 2020

RIA

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Load as well as power flow in tie-line are continuously varying in interconnection power systems. This paper presents an efficient method based on artificial intelligence control for automatic generation control (AGC) of a three-area power network. The control method implements Artificial Neural Network (ANN) to damp the frequency deviation and the fluctuation in the tie line power caused by load disturbances. The performance of the proposed controller is compared with classical control methods (PI and PID). The results showed that ANN-based control method is more efficient than others approaches. In this paper, MATLAB/SIMULINK package is used to investigate the results.

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“…Similarly, authors in Sahu et al, Sun et al, and Bhatt et al, utilized the system developed in Elgerd and Fosha to study AGC of hydro‐thermal system. Recent research in AGC is mainly focused on multi‐area system whose control areas are 3 or more …”

Section: Introductionmentioning

confidence: 99%

Maiden application of two degree of freedom cascade controller for multi-area automatic generation control

Raju

Saikia

Sinha

2018

Int Trans Electr Energ Syst

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Summary In this article, a 2 degree of freedom cascade controller (2DOF‐CC) is presented as the supplementary controller (SC) for multi‐area hydro‐thermal system. Proposed 2DOF‐CC is the combination of 2DOF proportional‐integral‐derivative (2DOF‐PID) and 2DOF proportional‐derivative (2DOF‐PD) controllers. The gains and other parameters of various controllers like PID, 2DOF‐PID, and 2DOF‐CC are optimized with cultural algorithm when considered one at a time. Comparison of dynamic responses of the system for PID, 2DOF‐PID, and 2DOF‐CC reveals better performance of the latter in terms of settling time and magnitude of oscillations. The study is also extended by incorporating superconducting magnetic energy storage units and explored that superconducting magnetic energy storage units effectively suppress the system dynamics against both step and random perturbations in presence of 2DOF‐CC. Selection of governor speed regulation parameters (R) and frequency bias parameter (B) in the presence of 2DOF‐CCs have been done in the considered system. Investigations recommend the use of higher values of R, and B should be kept at area frequency response characteristics (β). The effect of double reheat turbines on system response is also investigated and reveals that use of double reheat turbines deteriorates the system responses. Sensitivity analysis validates the sturdiness of parameters of 2DOF‐CC obtained at nominal conditions.

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Intelligent PI control technique in four area Load Frequency Control of interconnected hydro-thermal power system

Cited by 17 publications

References 11 publications

Neuro-Fuzzy Computational Technique to Control Load Frequency in Hydro-Thermal Interconnected Power System

Neuro-Fuzzy Computational Technique to Control Load Frequency in Hydro-Thermal Interconnected Power System

Automatic Generation Control of Multi-area Interconnected Power Systems Using ANN Controller

Maiden application of two degree of freedom cascade controller for multi-area automatic generation control

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