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CHAPTER-2

REVIEW OF LITERATURE

In this chapter literature survey of different researcher has been carried out. The review of

literature is arranged first concept of area wise and the control methodology used like

conventional control and intelligent control (fuzzy, ANN and ANFIS). In each section and sub-

section, literature is arranged as per the year of publication.

2.1 SINGLE AREAS POWER SYSTEM

2.1.1 Based on Conventional Control theory

Pan C. T. and C. M. Liaw (1989), reported ‘An Adaptive Controller for Power System Load

Frequency Control’. This paper presents an adaptive controller for load-frequency control of

power system. The pole assignment technique is used to find the parameters of the linear

controller, and the Popov's theorem is applied to design the parameters of the adaptation

mechanism. The simulation results indicate that good control performance can be obtained by

this proposed controller, and the performance is insensitive to the plant parameter changes.

Wang Y. et al(1994), reported ‘New robust adaptive load-frequency control with system

parametric uncertainties’. In the paper, based on a combination of the robust control approach

and an adaptive control technique, a design procedure of a new robust adaptive controller is

proposed for power system load-frequency control with system parametric uncertainties. The

simulation results demonstrate that for the example system the proposed load frequency

controller can achieve good dynamic performance. Heon-Su Ryu, et al (2000) presented

‘Extended Integral Control for Load Frequency Control with the Consideration of Generation-

Rate Constraints’. This paper presents an extended integral control to LFC scheme with the

presence of Generation Rate Constraints in order to get rid of overshoot of the conventional PI

control. The conventional LFC scheme does not yield adequate control performance with

consideration of the singularities of speed governor such as rate limit on valve position and GRC.

In order to overcome this draw back, an extended integral control is developed for the PI control

of the speed governor under the presence of GRC. The key idea of this integral control is using a

decoying factor to reduce the effect of error in the past. The simulation results show that the

proposed controller based on extended integral control yields much improved control

performance, compared to the conventional PI controller.

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Yang Ming-Sheng (2000), presented ‘Load-Frequency Control Scheme for Power Systems

Using Smoothed Switching Structure Theory’. A design scheme of smoothed switching structure

theory based load-frequency control for power systems including parameter uncertainties is

presented in this paper. However, knowledge about the bounds of the parameter uncertainties is

required for controller design. The basic concept and design scheme of switching structure

control are briefly discussed.

George Gross and Jeong Woo Lee (2001) presented ‘Analysis of Load Frequency Control

Performance Assessment Criteria’. This paper presents the development and application of an

analytic framework for the formulation and evaluation of control performance criteria in load

frequency control (LFC). The framework is constructed so as to explicitly represent the

uncertainty in the measured variables in LFC and to use metrics that are meaningful for the

structure of the problem.

Young-Hyun Moon, et al (2001), presented ‘Power System Load Frequency Control Using

Noise-Tolerable PID Feedback’. This paper presents a new PID (Proportiona1, Integral and

Differential) control scheme based on the feedback of averaged derivatives to realize a noise-

tolerable differential control with its application to the load frequency control in the power

system. It is well known that the LFC (Load Frequency Control) is exposed to the quite noisy

environment. The test results show that the proposed controller yields the outputs much closer to

the output of the original PID control neglecting noise effects. This demonstrates that the purpose

of noise-tolerable control is achieved by the proposed PID control using a delay element.

Dulpichet Rerkpreedapong et al (2003) presented ‘Robust Load Frequency Control Using

Genetic Algorithms and Linear Matrix Inequalities’. In this paper, two robust decentralized

control design methodologies for load frequency control (LFC) are proposed. The first one is

based on H∞ control design using linear matrix in-equalities (LMI) technique in order to obtain

robustness against uncertainties. The second controller has a simpler structure, which is more

appealing from an implementation point of view, and it is tuned by a proposed novel robust

control design algorithm to achieve the same robust performance as the first one. The simulation

results show that the responses of GALMI tuned PI load frequency controllers are almost the

same as those of the robust H∞ controllers, which have effective control performance and

robustness against possible disturbances

Khodabakhshian A. and N. Golbon (2004) presented ‘Unified PID Design for Load Frequency

Control’. This paper presents a new PID controller for power system load-frequency control. A

systematic tuning method is developed. The method is mainly based on a maximum peak-

resonance specification that is graphically supported by the Nichols chart. The proposed

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controller is simple, effective and can ensure that the overall system performance is desirable.

Comparative results of this new load-frequency controller and a conventional PI one show the

improvement in system damping remarkably.

Giuseppe Dell Olio et al (2005) presented ‘A pluralistic LFC scheme for online resolution of

power congestions between market zones’. This paper introduces the theoretical aspects and

functional design of such an advanced LFC scheme, capable of controlling at the same time the

cross border ex-changes of the pluralistic block and the power flows between net-work subareas

defined as market zones. Simulations on the Italian power system show the performance, main

advantages, and limits of the proposed control method.

Guangwei Meng et al (2009) presented ‘power system load-frequency controller design based

on discrete variable structure control theory’. This paper proposes a discrete-time variable

structure reaching law with attenuating quasi-sliding mode band, and gives the variable condition

of quasi-sliding mode band. The proposed reaching law is applied to design a load-frequency

controller for a power system. The simulation results show that the controller can not only

eliminate system chattering, but also improve dynamic performance of the system effectively and

make the system possess a strong robustness property.

Wen Tan, Zhan Xu (2009), presented ‘Robust analysis and design of load frequency controller

for power systems’. Robust load frequency control for power systems is discussed. A detailed

robustness analysis of the existing control laws shows that parameter variation is not a critical

issue but more attention should be paid to the un modeled dynamics in robust load frequency

controller design. A new robust load frequency control method is then proposed considering the

un-modeled dynamics of power systems. Finally, a new configuration is proposed to overcome

the effects of generation rate constraints (GRC).

Muwaffaq Irsheid Alomoush (2010) presented ‘Load frequency control and automatic

generation control using fractional order controllers’. Recently, fractional calculus has received

extensive attention and research. Accordingly, there is an increasing interest in fractional-order

(FO) dynamic systems and controllers. The widely used classical integer-order proportional

integral controller and proportional-integral-derivative controller are usually adopted in the load

frequency control (LFC) and automatic generation control (AGC) to improve the dynamic

response and to eliminate or reduce steady-state errors. The simulation results show that the

proposed FO controllers are robust and competitive to IA-based optimal controllers.

Kresimir Vrdoljak et al (2010) presented ‘Applying Optimal Sliding Mode Based Load-

Frequency Control in Power Systems with Controllable Hydro Power Plants’. In this paper an

optimal load-frequency controller for a nonlinear power system is proposed. Due to a non-

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minimum phase behavior of hydro power plants, full-state feedback sliding mode controller must

be used. Therefore, an estimation method based on fast output sampling is proposed for

estimating the unmeasured system states and disturbances. Finally, the controller parameters are

optimized using a genetic algorithm. Simulation results show that the proposed control algorithm

with the proposed estimation technique can be used for LFC in a nonlinear power system.

Khodabakhshian A. and R. Hooshmand (2010) presented ‘A new PID controller design for

automatic generation control of hydro power system’. This paper presents a new robust PID

controller for automatic generation control (AGC) of hydro turbine power systems. The method

is mainly based on a maximum peak resonance specification that is graphically supported by the

Nichols chart. The open-loop frequency response curve is tangent to a specified ellipse and this

makes the method to be efficient for controlling the overshoot, the stability and the dynamics of

the system. Comparative results of this new load frequency controller with a conventional PI one

and also with another PID controller design tested on a multi machine power system show the

improvement in system damping remarkably. The region of acceptable performance of the new

PID controller covers a wide range of operating and system conditions.

2.1.2 Based on Fuzzy Control Technique

Shih Chun Hsu et al (1995) presented ‘Automatic Generation of Fuzzy Control Rules by

Machine Learning Methods’. This paper presents a multi-strategy learning technique for

automatic generation of fuzzy control rules. The resulting decision tree can be easily converted

into IF-THEN rules, which are then fuzzified. The fuzzy rules are further improved by tuning the

parameters that define their membership functions using the gradient-descent approach.

Experimental results of applying the proposed technique to nonlinear system identification have

shown improvements over previous work in the area.

Chown G.A. and RC. Hartman (1997), presented ‘Design and Experience with a Fuzzy Logic

Controller for Automatic Generation Control (AGC)’. This paper describes the design,

implementation and operational performance of a fuzzy controller as part of the Automatic

Generation Control (AGC) system in Eskom’s National Control Centre. The fuzzy controller was

implemented to the control ACE calculation, which determines the shortfall or surplus generation

that has to be corrected. The controller was also very simple to implement and configure and

could be incorporated as an option on the vendor’s product.

Ha Q. P. (1998) presented ‘A Fuzzy Sliding Mode Controller for Power System Load-Frequency

Control’. The application of a robust sliding mode control method to the load frequency control

problem of a single area power system is considered in this paper. The control signal consists of

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an equivalent control, a switching control, and a fuzzy control. The influence of not only load

changes but also parameter variations and governor S backlash is considered with and without

generation-rate constraints. Simulation results demonstrate that the system responses are strongly

robust to load disturbances and parameter variations even in the presence of governor’s backlash

dead band and imposed generation physical constraints.

Jawad Talaq and Fadel Al-Basri (1999), presented ‘Adaptive Fuzzy Gain Scheduling for Load

Frequency Control’. An adaptive fuzzy gain scheduling scheme for conventional PI and optimal

load frequency controllers has been proposed. A Sugeno type fuzzy inference system is used in

the proposed controller. The Sugeno type fuzzy inference system is extremely well suited to the

task of smoothly interpolating linear gains across the input space when a very non-linear system

moves around in its operating space. The proposed adaptive controller requires much less

training patterns than a neural net based adaptive scheme does and hence avoiding excessive

training time. Results of simulation show that the proposed adaptive fuzzy controller offers better

performance than fixed gain controllers at different operating conditions.

Kazuto Yukita et al (2000) presented ‘Study of Load Frequency Control using Fuzzy Theory by

Combined Cycle Power Plant’. This paper proposes a new control method using the combined

cycle power plant that consists of multi-power generation units, to improve the load frequency

control (LFC) characteristics and to secure the regulation capacity in power system.

Dulpichet Rerkpreedapong and Ali Feliachi (2002), presented ‘Fuzzy Rule Based Load

Frequency Control in Compliance with NERC’s Standards’. In this paper, a set of fuzzy logic

rules is designed to manipulate load frequency controllers of generating units providing

regulation and load following services. The fuzzy based load frequency controllers take smart

actions that (1) assure compliance with NERC’s control performance standards, CPS1 and CPS2,

and (2) also reduce wear and tear of generating units’ equipments.

Musiala M. et al (2004), presented ‘An Adaptive Fuzzy Controller Gain Scheduling for Power

System Load-Frequency Control’. In this paper, an adaptive fuzzy controller gain scheduling

scheme for power system load-frequency control is designed to damp the frequency oscillations

and to track its error to zero at steady state, A Sugeno type inference system is used in the

proposed controller to adapt the scaling gains of a single fuzzy controller through a classical on-

line monitoring of the most sensitive parameters of the system. The proposed controller avoids

excessive patterns and training time compared to neural network based adaptive schemes. A

typical single-area non reheat power system is considered. Simulation results indicate that the

proposed controller is insensitive to parameter changes in a wide range of operating condition,

and to the generation rate constraints. Furthermore, it is simple to implement.

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Soundarrajan A. et al (2009), presented ‘Particle Swarm Optimization Based LFC and AVR of

Autonomous Power Generating System’. In this paper, an evolutionary computing approach for

determining the optimal values for the proportional-integral derivative (PID) controller

parameters of load frequency control (LFC) and Automatic Voltage Regulator (AVR) system of

single area power system using the particle swarm optimization technique is presented.. The

results are compared with conventional PID, Fuzzy and GA based controllers.

2.1.3 Based on ANN Control Technique

Murat Luy et al (2008) presented ‘Load Frequency Control in a single area power system by

artificial neural network (ANN)’. In this study, an artificial neural network (ANN) application of

load frequency control (LFC) of a single area power system by using a neural network controller

is presented. The study has been designed for a single area interconnected power system. The

comparison between a conventional Proportional and Integral (PI) controller and the proposed

artificial neural networks controller is showed that the proposed controller can generate the best

dynamic response for a step load change. The proposed ANN controller is recommended to

generate good quality and reliable electric energy.

2.1.4 Based on Hybrid ANN- Fuzzy Control Technique

Vinod Kumar D. M. (1998), presented ‘Intelligent Controllers For Automatic Generation

Control’. This paper presents a novel approach of Artificial Intelligence (AI) techniques viz.,

Fuzzy logic, Artificial Neural Network (ANN) and Hybrid Fuzzy Neural Network (HFNN) for

the Automatic Generation Control (AGC). The limitations of the conventional controllers

Proportional, Integral and Derivative (PID) are slow and lack of efficiency in handling system

non-linearities. The intelligent controllers, Fuzzy logic, ANN and Hybrid Fuzzy Neural Network

approaches are used for Automatic Generation Control for the single area system and two area

interconnected power systems. The performance of the intelligent controllers has been compared

with the conventional PI and PID controllers for the single area system as well as two-area

interconnected power system. The result shows that Hybrid Fuzzy Neural Network (HFNN)

controller has better dynamic response i.e., quick in operation, reduced error magnitude and

minimized frequency transients.

Mathur H.D. and S. Ghosh (2006), presented ‘A Comprehensive Analysis of Intelligent

Controllers for Load Frequency Control’. This paper presents summaries of novel approaches of

artificial intelligence (AI) techniques, like fuzzy logic, artificial neural network (ANN), hybrid

fuzzy neural network (HFNN), genetic algorithm (GA) for the load frequency control of

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electrical power system. The intelligent controllers are used for load frequency control for the

single area system. The performance of intelligent controllers with the conventional controllers

has been thoroughly compared and analyzed. It is observed that intelligent controllers are found

more suitable in present day power system where complexity is gradually increasing day by day.

2.2 TWO AREA INTERCONNECTED POWER SYSTEM

2.2.1 Based on Conventional Control Technique

Elgerd Olle I. and Charles E. Fosha, (1970), presented ‘Optimum Megawatt-Frequency

Control of Multiarea Electric Energy Systems. The North American Power Systems

Interconnection Committee recommends that each control area set its frequency bias equal to the

so-called area frequency response characteristic (AFRC).The authors question seriously the basis

for this practice and prove by the methods of optimum control that better response and wider

stability margins can be obtained by lower bias settings.

Fosha Charles E. and Olle I. Elgerd (1970), presented ‘The Megawatt-Frequency Control

Problem: A New Approach via Optimal Control Theory’. This paper records the development of

a state variable model of the megawatt-frequency control problem of multi area electric energy

systems. The model is in a mathematical form necessary for application of theorems of modem

optimal control theory. An optimal feedback controller whose structure is radically different from

that considered before is developed. The results of this study allow the authors to suggest feasible

ways of greatly improving dynamic response and stability margins of the megawatt-frequency

control system.

Ashok Kumar, O.P. Malik (1985), presented ‘Variable structure system control applied to AGC

of an interconnected power system’. A control scheme based on a variable-structure-system

concept is applied to the problem of automatic generation control of interconnected power

systems. The proposed algorithm is simple and easy to implement. The effect of generation-rate-

constraint nonlinearity on the dynamic performance of the system for reheat-and non reheat-type

steam turbines is also studied. A comparison of the conventional and the proposed variable-

structure control strategies shows that, with the application of the proposed algorithm, the system

performance is improved significantly.

Song Jiahua and Zheng Xinguang (1985) presented ‘Adaptive control with multistep predictor

for power system load frequency’. The regulation of electric power is of controlled process with

time delay. The time delay is existed because measuring, processing, telecommunication, unit

mechanical delay and using simplified model which should have a equivalent time delay to

describe a complex system performance exactly. The interest of the paper is put on treating such

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problem. A method of design of adaptive controller for load frequency has been prescribed

considering the time-delay.

Kothari M.L. & J. Nanda (1988) presented ‘Application of optimal control strategy to

automatic generation control of a hydrothermal system’. The paper highlights the design of

automatic generation controllers through optimal control strategy, for an interconnected

hydrothermal system using a new performance index that circumvents the need for a load

demand estimator. The dynamic performances of these controllers are analyzed and compared

with those obtained through the usual performance index as that used by Fosha and Elgerd

(1971), considering a step-load perturbation in either of the areas. Attempt is made to suitably

design the new optimal controller that can provide safe generation rate and reasonably good

response.

Kothari N.L. et al (1989), presented ‘Discrete Mode Automatic Generation Control of Two

Areas Reheat Thermal System with New Area Control Error’. This paper deals with discrete

mode Automatic Generation control of an interconnected reheat thermal system considering a

new area control error (ACEN) based on tie-per deviation, frequency deviation, time error and

inadvertent interchange. Optimum integral and proportima1 integral controllers using the

concept of stability margin and ISE technique have been obtained with conventional ACE and

new ACE, and their dynamic performances compared for a step load perturbation. The result

reveals that regulator based on the new ACE concept always guarantees zero steady state time

error and inadvertent interchange unlike in the case of a controller based on conventional ACE.

The settling time for tie-power and frequency deviations is however, somewhat more with the

controller based on new ACE.

Katsumi Yamashita and Hayao Miyagi (1991) presented ‘Multivariable self tuning regulator

for load frequency control system with interaction of voltage on load demand’. This paper

presents a new method of designing a multivariable self tuning regulator for a load frequency

control system with the inclusion of interaction of voltage on load demand. The self tuning

controller through speed governor control and excitation control is derived by defining a cost

function with a term for presenting the constraints on the control effort, and then by minimizing

it with respect to the control vector. The proposed method is applied to a two-area power system

provided with non reheat turbines in which the interaction of voltage deviation on load demand

is considered, and the control effects of this regulator are examined using digital simulation.

Das D. et al (1991) presented ‘Variable structure control strategy to automatic generation control

of interconnected reheat thermal system’. The paper deals with the analysis of automatic

generation control (AGC) of a two-area reheat thermal system considering a variable structure

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controller (VSC) based on the sliding mode concept. Investigation reveals that there is a

significant improvement in system dynamic performance with a VSC over that with an integral

controller. More over, the variable structure controller is found to be quite insensitive to wide

variations of system parameters. A systematic method has been suggested for the designs of

variable structure controllers operating in sliding mode for a two equal area reheat thermal

system.

Khatibi M. H. and O.A. Mohammed (1994) reported ‘An Automatic Two-Area Interconnected

System Load-Frequency Control Design’. The design, implementation and evaluation of a

programmable automatic load-frequency controller for a two- area interconnected system is

described. Implementation aspects along with speed requirements of the generators have been

fully investigated, taking into consideration the feedback of the output of these generators for

comparison with model reference. The described work has been implemented in the power

system laboratory at Florida International University.

Kourosh Sedghisigarchi et al (2002) presented ‘Decentralized Load Frequency Control in a

Deregulated Environment using Disturbance Accommodation Control Theory’. In this paper, a

decentralized controller is proposed for the load frequency control problem in a deregulated

environment. The deregulation scenario considered here assumes that generating units in each

area supply regulated power according to their energy contracts. Disturbance Accommodating

Controllers (DAC) are designed which are decentralized controllers using frequency and tie-line

power measurements only.

Hassan Bevrani et al (2003) presented ‘A scenario on Load-Frequency Controller Design in a

Deregulated Power System’. An approach based on µ synthesis and analysis theory is proposed

for the design of load frequency controller in response to the new technical control demand for

power system m a deregulated environment. In this approach the power system is considered as a

collection of separate control areas and each control area can buy electric power from some

generation companies to supply the area-load. The proposed technical scenario is illustrated with

application to the design of load-frequency controller for a typical control area the resulting

controller is shown to minimize the effect of disturbances and achieve acceptable frequency

regulation in presence of uncertainties and load variation.

Muthana T. Alrifai and Mohamed Zribi (2005) presented ‘Decentralized Controllers for

Power System Load Frequency Control’. This paper presents two decentralized control schemes

for load frequency control (LFC) of interconnected power systems. The first controller is a state

feedback linear controller. The second controller is a nonlinear controller. The two control

schemes are designed using Lyapunov theory. For simplicity and without loss of generality, the

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analysis and simulation studies are carried out for a two area interconnected power system. The

simulation results indicate that the proposed control schemes work well even in the presence of

generation-rate constraints. Moreover, the simulation results show that the proposed controllers

are robust to changes in the parameters of the power system.

Tyagi Barjeev and S.C. Srivastava (2005) presented ‘A LQG Based Load Frequency Controller

in a Competitive Electricity Environment’. This paper presents the design of a Linear Quadratic

Gaussian (LQG) regulator for the frequency control of a multi-area power system in a

restructured competitive electricity market environment. A general model of the LQG regulator

has been developed for multi-area system (with hydro and thermal generators) having Poolco and

bilateral transactions.

Tyagi Barjeev and S. C. Srivastava (2006) presented ‘A Decentralized Automatic Generation

Control Scheme for Competitive Electricity Markets’. This paper presents the design of a

decentralized automatic generation control (AGC) scheme for interconnected multi area power

system. The proposed controller incorporates various types of transactions taking place in a

competitive electricity market. The controller has been designed by appropriately assigning the

Eigen structure of each isolated subsystem via state feedback, satisfying the sufficient conditions

for stability. The functioning of the proposed decentralized controller has been demonstrated on a

39-bus New England system and a 75-bus Indian power system, and the results have been

compared with those obtained by using a centralized control scheme. Compliance with the North

American Electric Reliability Council standards for AGC has also been established.

Abolfazl Salami et al (2006) resented ‘The Effect of Load Frequency Controller on Load Pickup

during Restoration’. This paper proposes a method to improve the frequency response of a power

system during restoration. A Load Frequency Control (LFC) scheme with a PID controller is

used. In the initial phase of restoration; the proposed control scheme helps to increase the amount

of load pick- up. Presented method is capable of achieving better frequency response for a

determined load step. The aim is to assess desired frequency response for different power plant.

The proposed controller has been tested for different power plants, and simulation results show

that the frequency controller can improve load pick-up.

Ahmed Bensenouci and A. M. Abdel Ghany (2007) presented ‘Mixed H∞/H2 with Pole-

Placement Design of Robust LMI-Based Output Feedback Controllers for Multi-Area Load

Frequency Control’. In this paper, mixed H∞/H2 control theory with pole-placement is applied to

design centralized and decentralized robust output feedback controllers for Load Frequency

Control (LFC) of interconnected power systems. The system performance is analyzed through

simulating severe disturbances and wide parameters variation in the presence on the system

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inherent nonlinearity. In both centralized and decentralized cases, the system with the designed

robust controllers incorporated is found to fulfill the main LFC requirements.

Prasanth B. Venkata and S. V. Jayaram Kumar (2008), presented ‘Load Frequency Control

for a Two Area Interconnected Power System Using Robust Genetic Algorithm Controller’. In

this paper a new robust load frequency controller for two area interconnected power system is

presented to quench the deviations in frequency and tie line power due to different load

disturbances. The dynamic model of the interconnected power system is developed without the

integral control. The area control error is also not included. The frequency and derivatives are

zero under normal operation and after the disturbance effects are died.

Aswin N. Venkat et al (2008) presented ‘Distributed MPC Strategies with Application to Power

System Automatic Generation Control’. A distributed model predictive control (MPC)

framework, suitable for controlling large-scale networked systems such as power systems, is

presented. The overall system is decomposed into subsystems, each with its own MPC controller.

These subsystem-based MPCs work iteratively and cooperatively towards satisfying system wide

control objectives.

Sinha S.K. et al (2008), presented ‘Design of Optimal and Integral Controllers for AGC of Two

Area Interconnected Power System’. In this work Automatic Generation Control (AGC) of two-

area interconnected power system has been studied. As a consequence of continually load

variation the frequency and tie line power deviate over time and these transients are to be

minimized using different controllers. An optimal controller has been designed to ascertain zero

steady state frequency deviation and tie-line power flow deviation under all operating conditions.

For the same two-area system an integral controller has also been designed and the performance

of the two types of controllers has been compared. The simulation results indicate that better

control performance in terms of overshoot and settling time can be obtained by optimal controller

as compared to conventional integral controller.

Tyagi Barjeev and S. C. Srivastava (2008), presented ‘Automatic Generation Control Scheme

based on Dynamic Participation of Generators in Competitive Electricity Markets’. In this paper

a general model for multi-area AGC, suitable for deregulated electricity market has been

proposed. A dynamic participation factor for Gencos and Discos based on their bid has also been

proposed. To develop the model, control areas of different ratings and each area having number

of Discos and Gencos with different response rate has been considered. Different types of

transactions, possible in the deregulated markets, have also been considered to develop the model.

The developed model has been tested on a 75-bus Indian power system, with PID and the fuzzy

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logic based controller. Frequency deviations in all the areas settle down to zero more quickly

with the fuzzy logic based controller as compared to the conventional PID controller.

Sheikh M.R.I. et al (2009), presented ‘Application of Self-Tuning FPIC to AGC for Load

Frequency Control in Multi-Area Power System’. In this study, a self-tuning control scheme for

SMES is proposed and applied to automatic generation control (AGC) in power system. The

system is assumed to be consisting of two areas. The proposed self-tuning control scheme is used

to implement the automatic generation control for load frequency control application adding to

conventional control configuration. The effects of the self tuning configuration with fuzzy

proportional integral controller (FPIC) in AGC on SMES control for the improvement of load

frequency control (LFC) is compared with that of PI controlled AGC.

Ghazanfar Shahgholian et al (2009), presented ‘Dynamic Analysis and Stability of the Load

Frequency Control in Two Area Power System with Steam Turbine’. The aim of this paper is to

model, analysis and simulation of load frequency control in two area power system and

parameters variation effects. State equations of a LFC in two area power system for a steam

turbine are proposed. Then by examining some factors such as tie-line stiffness, turbine time

constant, inertia constant and damping factor, the frequency control methods and influence of a

small load variation are discussed. Finally, the steady state change in frequency in different cases

using Matlab is calculate and compared. The response of the system is studied for load each area

and parameters changes.

Mariano S.J.P.S. et al (2009), presented ‘Optimal Output Control: Load Frequency Control of a

Large Power System’. This paper addresses the stabilization and performance of the load

frequency regulator. The problem is solved by using the theory of the optimal control. An

algorithm, based on the new technique, proposed by the authors, to overcome the difficulties of

specifying the weighting matrices Q and R, is presented. The algorithm here proposed considers

the multi-area electric energy system. The results indicate that the obtained controller exhibits

better performance then those based on classic control.

Chamnan Koisap and Somyot Kaitwanidvilai (2009) presented ‘A Novel Robust Load

Frequency Controller for a Two Area Interconnected Power System using LMI and Compact

Genetic Algorithms’. This paper proposes a new technique for designing a fixed-structure robust

load frequency controller for a two area interconnected power system. The proposed technique

uses Linear Matrix Inequality (LMI) method to form an initial solution, and then the global

search algorithm, Compact Genetic Algorithm (CGA), is adopted for evaluating the final solution.

Bevrani H. et al (2010) presented ‘Reinforcement Learning Based Multi-agent LFC Design

Concerning the Integration of Wind Farms’. Frequency regulation in interconnected networks is

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one of the main challenges posed by wind turbines in modern power systems. The wind power

fluctuation negatively contributes to the power imbalance and frequency deviation. This paper

presents an intelligent agent based load frequency control (LFC) for a multi-area power system in

the presence of a high penetration of wind farms, using multi-agent reinforcement learning

(MARL). Nonlinear time domain simulations on a 39-bus test power system are used to

demonstrate the capability of the proposed control scheme.

Chatterjee Kalyan (2010) presented ‘Design of Dual Mode PI Controller for Load Frequency

Control’. The paper presents a new technique for the automatic generation control of

interconnected power systems. The proposed technique is developed for designing the controller

using the concept of dual-mode control in the PI controller such that the proportional mode is

made active when the rate of change of the error is sufficiently larger than a specified limit

otherwise switched to the integral mode. A digital simulation is used in conjunction with the

Hooke-Jeeve’s optimization technique to determine the optimum parameters (individual gain of

proportional and integral controller) of the PI controller. The Integrated Square of the Error (ISE)

performance index is considered to measure the appropriateness of the designed controller. Case

studies justify that dual mode with optimized values of the gains improved the control

performance than the commonly used Variable Structure System.

Liu Xiangjie et al (2010) presented ‘Load Frequency Control considering Generation Rate

Constraints’. Constrained generalized predictive algorithm is employed to load frequency control

in this paper. Generation rate constraint (GRC) has been considered. Using the linearization

modeling technique, this paper deals with load frequency control by multivariable generalized

predictive control method to build Controlled Auto-Regressive Integrated Moving Average

model (CARIMA) and obtain generalized predictive control algorithm for load frequency control

of the two-area reheat power system. Results demonstrate the effectiveness of the proposed

generalized predictive control algorithm.

Siraj S. F. et al (2010), presented ‘A Robust Adaptive Predictive Load Frequency Controller to

compensate for Model Mismatch’. The paper describes the design and implementation of a self-

tuning Load Frequency Controller (LFC) of a power system based on the Adaptive Generalized

Predictive (AGP) controller. The application of predictive control in power system control is

considered due to its ability to handle disturbances and un-modeled dynamics often encountered

in interconnected power system environments. Simulation results show that the controller

exhibits robustness in handling both problems with proper tuning of its parameters, especially

when compared to the normal adaptive control methods of minimum variance and pole

assignment. It has been observed that for the LFC system studied, the system with AGP

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controller is always stable even in the presence of randomly varying or step disturbances as well

as un modeled dynamics.

Angel Molina-Garcia et al (2010) presented ‘Decentralized Demand-Side Contribution to

Primary Frequency Control’. Frequency in large power systems is usually con-trolled by

adjusting the production of generating units in response to changes in the load. As the amount of

intermittent renewable generation increases and the proportion of flexible conventional

generating unit decreases, a contribution from the demand side to primary frequency control

becomes technically and economically desirable. One of the reasons why this has not been done

was the perceived difficulties in dealing with many small loads rather than a limited number of

generating units. Simulation results show that, using this approach, the demand side can make a

significant and reliable contribution to primary frequency response while preserving the benefits

that consumers derive from their supply of electric energy.

Aidin Sakhavati et al (2011), presented ‘Decentralized robust load-frequency control of power

system based on quantitative feedback theory’. This paper aims at investigating the problem of

Load Frequency Control (LFC) in interconnected power systems in order to obtain robustness

against uncertainties. A design method for a robust controller, based on Quantitative Feedback

Theory (QFT), has been presented in this paper. For a two-area power system, the simulation

results show that the system response with the proposed QFT controller exhibits transient

response beyond PI controllers. It is also shown that the transient response of the tie line power

can also be improved.

Khodabakhshian A. et al (2012) presented ‘Design of a robust load frequency control using

sequential quadratic programming technique’. This paper presents a new methodology, named

Sequential Quadratic Programming (SQP), to design a robust PID controller for Load Frequency

Control (LFC) of nonlinear interconnected power systems. The robust performance of the

proposed controller is compared with that of a conventional PI controller, through the simulation

of two multi-machine power system examples with a variety of disturbances. Results show that

the proposed technique gives a better performance.

Dey Rajeeb et al (2012), presented ‘H∞ load frequency control of interconnected power systems

with communication delays’. This paper considers the problem of power system load frequency

control design incorporating the effect of using open communication network instead of a

dedicated one for the area control error signals. To have this appropriately considered time delays

in the ACE signals. A delay-dependent two-term H∞ controller design has then been proposed

using linear matrix inequalities. Comparison of effectiveness of the proposed two-term controller

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with that of existing one-term and two-term controller designs establishes the superiority as well

as applicability of the present design for the LFC problem.

Parmar K.P. Singh et al (2012) presented ‘Load frequency control of a realistic power system

with multi-source power generation’. In this paper, load frequency control (LFC) of a realistic

power system with multi-source power generation is presented. In practice, access to all the state

variables of a system is not possible and also their measurement is costly and difficult. Usually

only a reduced number of state variables or linear combinations thereof, are available. To resolve

this difficulty, optimal output feedback controller which uses only the output state variables is

proposed. The sensitivity analysis reveals that the proposed controller is quite robust and

optimum controller gains once set for nominal condition need not to be changed for ±25%

variations in the system parameters and operating load condition from their nominal values.

2.2.2 Based on ANN Control Technique

Bid A. P. et al (1994) presented ‘An Enhanced Neural Network Load Frequency Control

Technique’. In this work it is continued to investigate the use of neural Network (NN) to act as

the control intelligence in conjunction with a standard adaptive load frequency control scheme. In

this approach a NN is operated in parallel with a full load frequency adaptive control &e. The

NNs are able to monitor the system frequency as the controller issues control command. This

neural control approach is shown to have several advantages over the basic fixed parameter

schemes and the more advanced adaptive control technique that have been developed. The

inherent stability and rapid ability to re configure the NN control strategy, to match the operation

of the controlled system; will be more beneficial than other method.

Shayeghi H. and H. A. Shayanfar (2004) presented ‘Power System Load Frequency Control

Using RBF Neural Networks Based on µ-Synthesis Theory’. This paper describes a nonlinear

Radial Basis Function Neural Networks (RBFNN) controller based on µ-Synthesis technique to

load frequency Control (LFC) of the power systems. Power systems such as other industrial plant

& have some uncertainties and deviations due to multivariable operating conditions and load

variations that for controller design, had to take the uncertainties into account For this reason, in

design of the proposed load frequency controller the idea of µ-Synthesis theory is being used.

Shayeghi Hossein and Heidar Ali Shayanfar (2004), presented ‘Automatic Generation Control

of Interconnected Power System Using ANN Technique Based on μ Synthesis’. This paper

presents a nonlinear Artificial Neural Networks (ANN) controller based on μ–synthesis for

Automatic Generation Control (AGC) of power systems. Power systems such as other industrial

plants have some uncertainties and deviations due to multivariable operating conditions and load

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changes. The simulation results on a two-area power system show that the proposed ANN

controller is effective and gives good dynamic responses even in the presence of Generation Rate

Constraints (GRC). In addition, it is superior to the conventional PI and μ–based robust

controllers.

Shayeghi H., H.A. Shayanfar, O.P. Malik (2007), presented ‘Robust decentralized neural

networks based LFC in a deregulated power system’. In this paper, a decentralized radial basis

function neural network (RBFNN) based controller for load frequency control (LFC) in a

deregulated power system is presented using the generalized model for LFC scheme according to

the possible contracts. The results of the proposed controllers are compared with the mixed

H2/H∞ controllers for three scenarios of the possible contracts under large load demands and

disturbances.

Bhongade Sandeep et al (2011), presented ‘Performance of SMES unit on Artificial Neural

Network based Multi-area AGC scheme’. This work investigates the performance of

Superconducting Magnetic Energy Storage (SMES) unit on Artificial Neural Network (ANN)

based multi-area AGC scheme. SMES units have been used to the power systems to inject or

absorb active power. A three layer feed forward neural network (NN) is proposed for controller

design and trained with Back propagation algorithm (BPA). The result shows that the

performance of the ANN controller with SMES unit is better than the performance without

SMES unit.

Bhongade Sandeep et al(2011), presented ‘Effect of SMES unit in load following contract in a

restructured power system’. The purpose of this paper is to analyze the effect of SMES unit on

the Dynamic Neural Network (DNN) based multi area AGC scheme. The advantage of the DNN

controller is that it does not require extensive and rigorous model for optimal tuning. It requires a

set of training data. The training data can be generated from the system model. The result shows

that the performance of the DNN controller with SMES unit is better than the performance

without SMES unit.

2.2.3 Based on Fuzzy Control Technique

Hiyama Takashi et al(2000), presented ‘Fuzzy Logic Based Multi-Functional Load Frequency

Control’. This paper presents a multi-functional fuzzy logic based Tie- line Bias Control (TBC)

scheme considering the MWh constraint for the power transmission on the tie-line and the

regulation margin. In addition, the real power flow constraint on each trunk line is also taken

into account. A detailed non linear LFC simulator has been developed in the Matlab/Simulink

environment. Simulation results demonstrate the efficiency of both the proposed control scheme

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and the simulator performance. By using the proposed fuzzy logic control scheme, the MWh

constraint is satisfied to avoid the MWh contract violation. The regulation capacity is always

kept to a certain level by the replacement of the required generation from the LFC units to the

non-LFC units.

Tyagi Barjeev and S.C. Srivatav (2003), presented ‘A Fuzzy Logic Based Load Frequency

Controller in a Competitive Electricity Environment’. This paper presents the design of a fuzzy

logic based controller for Automatic Generation control (AGC) in a deregulated electricity

environment. A general model of the integral controller has been developed for multi-area system

having poolco, bilateral and mixed transactions employing fuzzy logic scheme for optimal tuning

of integral gain. The Area Control Error (ACE) signal and rate of change of the Area Control

Error (Che ACE) have been used as input to the fuzzy logic based controller.

Nanda J. and J. S. Sakkaram (2003), presented ‘Automatic Generation Control with Fuzzy

Logic Controller Considering Generation Rate Constraint’. This paper describes application of

Fuzzy Logic Controller (FLC) for Automatic Generation Control (AGC) of a two area reheat

thermal power system. Different types of inputs for the FLC and different number of triangular

Membership Functions (MF) are considered to examine their effect on the dynamic responses for

the Automatic Generation Control (AGC) system.

Nanda J. and A. Mangla (2004), presented ‘Automatic Generation Control of an Interconnected

Hydro-Thermal System Using Conventional Integral and Fuzzy Logic Controller’. This paper

deals with Automatic Generation Control of interconnected hydrothermal system in the

continuous- discrete mode using conventional integral and fuzzy logic controllers. Effects of

variation of sampling time period on dynamic responses have been investigated, both with

conventional integral controller and fuzzy logic controllers, considering small step perturbations.

Effects of different number of triangular membership functions and inputs for Fuzzy Logic

Controller on dynamic response have been explored. Further, dynamic responses under small

step perturbation have been compared, considering integral and fuzzy logic controllers. Presence

of FLC in both areas and small step perturbation in either area or in both areas simultaneously

provides better dynamic response than with conventional integral controller.

Altas I. H. and J. Neyens (2006), presented ‘A Fuzzy Logic Decision Maker and Controller for

Reducing Load Frequency Oscillations in Multi-Area Power Systems’. This paper deals with the

application of a fuzzy logic based decision maker and controller in order to damp load-frequency

oscillations in multi area power systems. A linearised dynamic model of a two area power system

is derived from that of a well known single area system and combined with the proposed fuzzy

controller for simulation purposes. The fuzzy logic based controller with a decision making unit

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is designed to replace the classical integral type controllers. The proposed approach is compared

with classical ones for performance and validity.

Rao C. Srinivasa et al (2007), presented ‘Automatic Generation Control of TCPS Based

Hydrothermal System under Open Market Scenario: A Fuzzy Logic Approach’. This paper

presents the analysis of Automatic generation control (AGC) of a two-area interconnected

thyristor controlled phase shifter (TCPS) based hydrothermal system in the continuous mode

using fuzzy logic controller (FLC) under open market scenario. The effects of nonlinearities like

dead band and generation rate constraint on the system have also been investigated. Simulation

results show that the limitations of integral controller can be overcome by including Fuzzy

concept and thereby the response of frequency and tie line power can be improved substantially

following a load change in any area.

Haider A.F. Mohamed et al (2008), presented ‘Load frequency controller design for Iraqi

National Super Grid System using Fuzzy logic controller’. This paper presents a Fuzzy Gains

Scheduled Proportional and Integral (FGPI) controller for Load Frequency Control (LFC) of the

Iraqi National Super Grid system (INSGS). A linear-time-invariant mathematical model is

derived for the system that consists of six generating stations with various types of turbines.

Maintaining frequency of each area and the net tie-line power at scheduled value due to the load

perturbations are considered in this study. Simulation of the proposed control scheme show better

results and transient performance improvements when compared to the conventional method

which is also simulated in this paper.

El-Metwally K.A. (2008), presented ‘An Adaptive Fuzzy Logic Controller for a Two Area Load

Frequency Control Problem’. This paper presents an adaptive fizzy logic control approach for

designing a decentralized controller for load frequency control of interconnected power areas.

The proposed adaptive fuzzy logic load frequency controller (AFLFC) has been designed to

improve the dynamic performance of the frequency and the tie line power flow under a sudden

load change in the power areas. The AFLFC replaces the original conventional integral controller

and utilizes the same area criteria error input. The effect of generation rate constraint (GRC) for

both areas has been considered in the controller design. Time domain simulations using

MATALB/SIMULINK program has been performed to demonstrate the effectiveness of the

proposed AFLFC.

Aravindan P. and M.Y. Sanavullah (2009), presented ‘Fuzzy Logic Based Automatic Load

Frequency Control of Two Area Power System with GRC’. This paper describes the Automatic

Generation Control (AGC) of interconnected reheat thermal system using Proportional - Integral

(PI) and extended Proportional-Integral (extended PI) and Fuzzy Logic Controller (FLC). The

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extended PI controller is used to reduce the peak over shoot and settling time error in the past.

System performance is examined considering 1% step load perturbation in either area of the

system. The system performance is observed on the basis of dynamic parameter (i.e.) settling

time. The simulation result shows that the FLC yields much improved control performance when

compared to both extended PI and conventional PI controller.

Hassan Lokman H. et al (2009), presented ‘Load Frequency Control of Power Systems with

Sugeno Fuzzy Gain Scheduling PID Controller’. This paper proposes a new Fuzzy Gain

Scheduled Proportional, Integral and Derivative (FGPID) controller by using Takagi-Sugeno

(TS) fuzzy system to the load frequency control problem in multi-area power systems. The TS

fuzzy inference engine is chosen and the range of the controller is selected suitably to enhance

the output performance of the system. Nonlinear simulation results show that the proposed

controller provides better performance than the other two models.

Anand B. and A. Ebenezer Jeyakumar (2009), presented ‘Load Frequency Control with Fuzzy

Logic Controller Considering Non-Linearities and Boiler Dynamics’. This paper describes the

Load Frequency Control (LFC) of two area interconnected reheat thermal system using

conventional Proportional – Integral (PI) controller and Fuzzy Logic Controller (FLC). The

system is incorporated with governor dead band, generation rate constraint non-linearities and

boiler dynamics. The conventional PI controller does not yield adequate control performance

with the consideration of nonlinearities and boiler dynamics. To overcome this drawback Fuzzy

Logic Controller has been employed in the system. The simulation results conclude that FLC

yields fast settling time with less number of oscillations which advocates the smooth settlement

of the quality power supply.

Mazinan A. H. and M. F. Kazemi (2010), presented ‘An Efficient Solution to Load-Frequency

Control Using Fuzzy-Based Predictive Scheme in a Two-Area Interconnected Power System’.

This work deals with a novel load-frequency control (LFC) using the fuzzy-based predictive

scheme in a two-area interconnected power system. At first, the power system needs to be

modeled and subsequently the Takagi-Sugeno-Kang (TSK) fuzzy-based approach using the

linear generalized predictive control (LGPC) scheme is realized to implement on the system

presented.

Sayed Mojtaba Shirvani Boroujeni et al (2011), presented ‘Load frequency control in multi

area electric power system using genetic scaled fuzzy logic’. In this paper, a new Fuzzy type

controller is considered for Load Frequency Control problem. In this new Fuzzy technique,

the upper and lower bounds of the Fuzzy membership functions are obtained using

genetic algorithms optimization method and so this Fuzzy method is called “scaled-Fuzzy.

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The simulation results visibly show the validity of scaled Fuzzy method, in comparison with the

traditional PI type method.

Sudha K.R. and R. Vijaya Santhi (2011) presented ‘Robust decentralized load frequency

control of interconnected power system with Generation Rate Constraint using Type-2 fuzzy

approach’. Literature shows that fuzzy logic controller, one of the most useful approaches, for

utilizing expert knowledge, is adaptive in nature and is applied successfully for power system

stabilization control. This paper proposes a Type-2 (T2) fuzzy approach for load frequency

control of two-area interconnected reheat thermal power system with the consideration of

Generation Rate Constraint (GRC). The performance of the Type-2 (T2) controller is com-pared

with conventional controller and Type-1 (T1) fuzzy controller with regard to Generation Rate

Constraint (GRC). The system parametric uncertainties are verified by changing parameters by

40% simultaneously from their typical values.

2.2.4 Based on GA Control Technique

Pinang Li et al (2002) presented ‘Genetic Algorithm Optimization for AGC of Multi-Area

Power Systems’. A Genetic Algorithm (GA) for parameter optimization of PID sliding mode

load frequency control used in Automatic Generating Control (AGC) of multi area power

systems with nonlinear elements has been proposed. The method has the advantages of both PID

and sliding mode control. Instead of using traditional analysis algorithm to obtain the controller

parameters, GA optimization technology is introduced. PID parameter optimization for the

interconnection of the AGC loops using MATLAB Simulink model is developed. A Real Coded

Genetic Algorithm is adopted and integrated into MATLAB Simulink. The simulation of a two-

area power systems with PI and PIU controllers are reported and the results are reasonable.

Juang C.F. and C.F. Lu (2006), presented ‘Load frequency control by hybrid evolutionary

fuzzy PI controller’. Power-system load-frequency control by fuzzy-PI (FPI) controller is

proposed. During control, a fuzzy system is used to decide adaptively the proper proportional and

integral gains of a PI controller according the area-control error and its change. To ease the

design effort and improve the performance of the controller, design of the FPI controller by

hybridizing a genetic algorithm and particle-swarm optimization, called FPI–HGAPSO, is

proposed. FPI–HGAPSO is based on the hybrid of the genetic algorithm and particle-swarm

optimization. In FPI–HGAPSO, elites in the population of GAs are enhanced by particle-swarm

optimization and these enhanced elites are selected as parents for crossover and mutation

operations. Simulations of the proposed evolutionary FPI-control approach on a multi area

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interconnected power system with different kinds of perturbations are performed. The

performance of the proposed approach is verified from simulations and comparisons.

Roy Ranjit and S. P. Ghoshal (2006), presented ‘Evolutionary Computation Based

Optimization in Fuzzy Automatic Generation Control’. This paper presents a comparative

optimization performance and transient performance studies among three evolutionary

computational techniques as Genetic Algorithm (GA), Hybrid Particle Swarm with Constriction

factor Approach (HPSOCFA) and Hybrid Taguchi Particle Swarm optimization (HTPSO)

methods in automatic generation control. For comparative study of performances, the above-

mentioned techniques are firstly used to determine nominal optimal Proportional-Integral-

Derivative gains of PID controller and nominal transient responses of frequency deviations in

each area for nominal area input parameters. HTPSO based optimal gains result in true optimal

transient responses of frequency deviations and tie line power flow changes.

Mehdi Nikzad et al (2010), presented ‘Comparison of Artificial Intelligence Methods for Load

Frequency Control Problem’. Practice LFC systems use simple proportional-integral (PI) or

integral (I) controllers. But the PI control parameters are usually tuned based on the classical or

trial-and-error approaches and they are incapable to obtain good dynamic performance under

various load conditions. For this problem, in this paper the artificial intelligence methods such as

Genetic Algorithms (GA) and Fuzzy logic are proposed to tune the controllers for LFC problem

in power system. A two-area power system example is considered as case study to illustrate the

proposed methods. To show effectiveness of proposed methods and also comparing the

performance of GA and Fuzzy controllers, several time domain simulations for various load

changes scenarios are presented. Simulation results emphasis on the better performance of Fuzzy

controllers than GA controllers in LFC problem.

Ramakrishna K. S. S. et al (2010), presented ‘Automatic generation control of interconnected

power system with diverse sources of power generation’. In this paper, automatic generation

control (AGC) of two area interconnected power system having diverse sources of power

generation is studied. The two area power system is simulated for different nominal loading

conditions. Genetic algorithm (GA) is used to obtain the optimal PID gains for various cases

using integral squared error plus integral time absolute error (ISE+ITAE) performance index for

fitness evaluation. Some of the transient responses are shown for different nominal loading

conditions due to step load disturbances in the system.

Bhongade Sandeep et al (2010) presented ‘Genetic Algorithm based PID controller for

Frequency Regulation Ancillary services’. In this paper, the parameters of Proportional, Integral

and Derivative (PID) controller for automatic Generation Control (AGC) suitable in restructured

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power system is tuned according to Generic Algorithms (GAs) based performance indices. The

key idea of the proposed method is to use the fitness function based on Area Control Error (ACE).

Bhongade Sandeep et al (2011), presented ‘Genetic algorithm based PID controller design for a

multi-area AGC scheme in a restructured power system’. In this paper, a multi-area Automatic

Generation Control (AGC) scheme suitable in a restructured interconnected power system has

been proposed. The results of GAPID controller have been compared with those obtained by

using the Least Square Minimization method. Compliance with North American Electric

Reliability Council (NERC) standards for AGC has also been established in this work. Effort has

been made in this paper to reduce the cost incurred by earlier proposed systems by having SMES

unit located in one area in case of two area system and only two areas out of four areas in case of

four area system to regulate multi-area frequency.

Boroujeni et al (2012) presented ‘Multi Area Load Frequency Control Using Simulated

Annealing’. In this paper a PI type controller is considered for LFC problem. The parameters of

the proposed PI controller are tuned using Simulated Annealing (SA) optimization method. A

multi area electric power system with a wide range of parametric uncertainties is given to

illustrate proposed method. To show effectiveness of the proposed method, a PI type controller

optimized by Genetic Algorithms (GA) is designed in order to comparison with the proposed PI

controller. The simulation results visibly show the validity of SA-PI controller in comparison

with the GA-PI controller.

2.2.5 Based on hybrid Intelligent Control Technique

Hosseini S.H and A.H. Etemadi (2008) presented ‘Adaptive neuro-fuzzy inference system

based automatic generation control’. Fixed gain controllers for automatic generation control are

designed at nominal operating conditions and fail to provide best control performance over a

wide range of operating conditions. So, to keep system performance near its optimum, it is

desirable to track the operating conditions and use updated parameters to compute control gains.

A control scheme based on artificial neuro-fuzzy inference system (ANFIS), which is trained by

the results of off-line studies obtained using particle swarm optimization, is proposed in this

paper to optimize and update control gains in real-time according to load variations. Also,

frequency relaxation is implemented using ANFIS. The efficiency of the proposed method is

demonstrated via simulations.

Taher Seyed Abbas et al (2008) presented ‘Optimal Decentralized Load Frequency Control

Using HPSO Algorithms in Deregulated Power Systems’. LFC systems use simple Proportional-

Integral (PI) or Integral (I) controllers. However, since the PI or I control parameters are usually

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tuned based on classical or trial-and-error approaches, they are incapable of obtaining good

dynamic performance for various load changes scenarios in multi-area power system. For this

reason, in this study the PI and I control parameters are tuned based on Hybrid Particle Swarm

Optimization (HPSO) algorithm method for LFC control in two-area power system. Because

HPSO is an optimization method, therefore, in the uncertainty area of controller parameters, finds

the best parameters for controller and obtained controller is an optimal controller.

Panda Gayadhar et al (2009), presented ‘Hybrid Neuro Fuzzy Approach for Automatic

Generation Control of Two Area Interconnected Power System’. This paper deals with a novel

approach of artificial intelligence (AI) technique called Hybrid Neuro-Fuzzy (HNF) approach for

an (AGC). The advantage of this controller is that it can handle the non linearities at the same

time it is faster than other conventional controllers. The result shows that intelligent controller is

having improved dynamic response and at the same time faster than conventional controller. The

effectiveness of the proposed controller in increasing the damping of local and inter area modes

of oscillation is demonstrated in a two area interconnected power system.

Panda Gayadhar et al (2009) presented ‘Automatic Generation Control of Interconnected

Power System by Hybrid Neuro Fuzzy Approach’. The design of Automatic Generation Control

(AGC) system plays a vital role in automation of power system. This paper proposes Hybrid

Neuro Fuzzy (HNF) approach for AGC of two-area interconnected reheat thermal power system

with the consideration of Generation Rate Constraint (GRC). System performance is examined

considering disturbance in each area of interconnected power system. Also the simulation results

are compared with a conventional PI controller. The result shows that the proposed intelligent

controller is having improved dynamic response and at the same time faster than conventional PI

controller.

Nanda Janardan et al (2009), presents ‘Maiden Application of Bacterial Foraging-Based

Optimization Technique in Multi area Automatic Generation Control’. A maiden attempt is made

to examine and highlight the effective application of bacterial foraging (BF) to optimize several

important parameters in automatic generation control (AGC) of interconnected three unequal

area thermal systems, such as integral controller gains for the secondary control, governor speed

regulation parameters for the primary control and frequency bias parameters, and compare its

performance to establish its superiority over genetic algorithm (GA) and classical methods.

Shayeghi H. and H.A. Shayanfar (2010), presented ‘PSO Based Neuro-Fuzzy Controller For

LFC Design Including Communication Time Delays’. The Proportional Integral Derivative (PID)

controller is the most adopted controllers for industrial plants, due to its simplicity and

satisfactory performances for a wide range of processes. The problem of robustly off-line tuning

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of PID based LFC design is formulated as an optimization problem according to the time

domain-based objective function which is solved by Particle Swarm Optimization (PSO)

technique that has a strong ability to find the most optimistic results. To demonstrate the

effectiveness of the proposed control strategy a two-area restructured power system is considered

as a test system under different operating conditions and system nonlinearities. The simulation

results show that the tuned gains of the PID based load frequency controller using the ANFIS can

provide better damping of frequency oscillations.

Rao C. Srinivasa (2010), presented ‘Adaptive Neuro-Fuzzy Based Inference System For Load

Frequency Control of Hydrothermal System Under Deregulated Environment’. This paper

presents the analysis of Load Frequency Control (LFC) of a two-area hydrothermal system under

deregulated environment by considering Adaptive Neuro-Fuzzy Inference System (ANFIS).

Fixed gain controllers for LFC are designed at nominal operating conditions and fail to provide

best control performance over a wide range of operating conditions. So, in order to keep system

performance near its optimum, it is desirable to track the operating conditions and use updated

parameters to compute control gains. A control scheme based on ANFIS, which is trained by the

results of off-line studies obtained using genetic algorithm, is proposed in this paper to optimize

and update control gains in real-time according to load variations. The efficiency of the proposed

method is demonstrated through computer simulations.

Farhangi Reza et al (2012), presented ‘Load frequency control of interconnected power system

using emotional learning based intelligent controller’. In this paper a novel approach based on the

emotional learning is proposed for improving the load frequency control (LFC) system of a two-

area interconnected power system with the consideration of generation rate constraint (GRC).

The controller includes a neuro-fuzzy system with power error and its derivative as inputs. A

fuzzy critic evaluates the present situation, and provides the emotional signal (stress). The

controller modifies its characteristics so that the critic’s stress is reduced. The convergence and

performance of the proposed controller, both in presence and absence of GRC, are compared

with those of proportional integral (PI), fuzzy logic (FL), and hybrid neuro-fuzzy (HNF)

controllers. By applying the stress signal to the neuro-fuzzy controller, the controller parameters

are tuned in order to optimize system performance.

2.2.6 Based on Combining AC-DC Link

Ibrahim et al (2005) presented ‘Recent Philosophies of Automatic Generation Control Strategies

in Power Systems’. An attempt is made in this paper to present critical literature review and an

up-to-date and exhaustive bibliography on the AGC of power systems. Various control aspects

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concerning the AGC problem have been highlighted. AGC schemes based on parameters, such as

linear and nonlinear power system models, classical and optimal controls, and centralized,

decentralized, and multilevel control, are discussed. AGC strategies based on digital, self-tuning

control, adaptive, VSS systems, and intelligent/soft computing control have been included.

Finally, the investigations on AGC systems incorporating BES/SMES, wind turbines, FACTS

devices, and PV systems have also been discussed. The paper presents a critical review of the

recent philosophies in the area of AGC. Due attention has also been paid to recent developments,

such as AGC schemes based on the concepts of neural networks and fuzzy logic and the

incorporation of parallel AC/HVDC links in the designs of AGC regulators. Emphasis has been

given to categorizing various AGC strategies reported in the literature that highlights their salient

features.

Rao C. Srinivasa et al (2009), presented ‘Improvement of dynamic performance of

hydrothermal system under open market scenario using asynchronous tie-lines’. This paper

presents an analysis on dynamic performance of a two-area hydrothermal system interconnected

via parallel ac/dc transmission links when subjected to parametric uncertainties. In this paper

area-1 consists of thermal power plant whereas area-2 consists of hydro power plant. The

degradation in system dynamic performance can be compensated effectively using dc link in

parallel with ac tie-line and the same have been presented using MATLAB/SIMULINK.

Nakayama K. et al(2009), presented ‘Load Frequency Control for Utility Interaction of Wide-

Area Power System Interconnection’. This paper discusses LFC (load frequency control) with

HVDC (High Voltage DC transmission system). So far, AGC (Automatic generation control) has

focused on economic dispatch control and load frequency control; especially the latter is mainly

on frequency stabilization for ac-link network systems. However, the upcoming power-

electronics based HVDC transmission system offers new aspects for the improvement of

frequency control. Whole DC-interconnected system now acts as a single system and the

disturbance to even the weaker system is easily suppressed since it is treated as a tiny disturbance

to the whole system.

Ramesh S. and A. Krishnan (2010) presented ‘Fuzzy Rule Based Load Frequency Control in a

Parallel AC-DC Interconnected Power Systems through HVDC Link’. In this paper, a fuzzy

logic controller is proposed for an application of HVDC link to stabilize the frequency oscillation

in parallel AC-DC interconnected power systems. By simulation study, the fuzzy logic controller

is very effective in suppressing the frequency oscillations caused by rapid load disturbances. For

further study, the proposed control design of HVDC link will be extended to stabilize the

frequency oscillations in a multi area interconnected power system.

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Naimul Hasana et al (2012) presented ‘Sub-optimal automatic generation control of

interconnected power system using constrained feedback control strategy’. This paper presents

sub-optimal AGC regulator designs for a 2-area interconnected power system using constrained

feedback control strategy. The power system with identical thermal plants consisting of non-

reheat thermal turbines interconnected via parallel AC/DC links is considered for the

investigations. The implementation of optimal AGC regulator requires monitoring of all the state

variables of the system or state reconstruction, which may be undesirable from cost and

complexity considerations. Due to these limitations of optimal AGC regulators, sub-optimal

AGC regulators are designed based on the constrained feedback control strategy using the

feedback of system states which are accessible and available for measurement.

2.3 THREE AREAS POWER SYSTEM

2.3.1 Based on Conventional Control Theory

Alan R Oneal (1995), presented ‘A Simple Method for Improving Control Area Performance:

Area Control Error (ACE) Diversity Interchange’. Control Areas within three major (and

essentially separate) areas of North America are interconnected electrically, thus enjoying vastly

improved reliability and economy of operation compared to operating in isolation. Each must

continually balance load, interchange and generation to minimize adverse influence on

neighboring control areas and interconnection frequency. This requires investment in control

systems and the sacrifice of some fuel conversion efficiencies to achieve the objective of

complying with minimum control performance standards set by the North American Electric

Reliability Council (NERC).

Wake Koichi et al (2001) presented ‘A Study on Automatic Generation Control Method

Decreasing Regulating Capacity’. This paper presents a method of automatic generation control

(AGC) decreasing the regulating capacity of load frequency control (LFC). The regulating

capacity is reduced economic load dispatching control (EDC) and LFC using the regulating

decreased level (Dei). In this paper, it is examined that this technique is effective on random

disturbance using a three-area longitudinal system model. The proposed LFC can decrease the

regulating capacity than the conventional LFC by using the regulating decreased level.

Delfino F. Fornari and S. Massucco (2002), presented ‘load frequency control and inadvertent

interchange evaluation in restructured power systems’. The subject of load-frequency control

(LFC) from the point of view of the restructuring process of the electrical industry is addressed.

LFC is treated as an ancillary service essential for maintaining the electrical system reliability at

an adequate level. Reference is made to the guidelines suggested by the Union for the Co-

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ordination of Transmission of Electricity. The results of simulations performed on a power

system based on an IEEE Reliability Test System arranged into a three-control-area configuration

are reported for the different LFC schemes. Evaluation of inadvertent interchanges is performed

and suggestions on their accounting are proposed.

Bevrani H. et al (2004), presented ‘Robust decentralized load-frequency control using an

iterative linear matrix inequalities algorithm’. In practice LFC systems use simple proportional-

integral (PI) controllers. However, since the PI controller parameters are usually tuned based on

classical or trial-and-error approaches, they are incapable of obtaining good dynamical

performance for a wide range of operating conditions and various load changes scenarios in a

multi-area power system. For this problem, the decentralized LFC synthesis is formulated as an

HN-control problem and is solved using an iterative linear matrix inequalities algorithm to design

of robust PI controllers in the multi-area power systems. A three-area power system example

with a wide range of load changes is given to illustrate the proposed approach. The resulting

controllers are shown to minimize the effect of disturbances and maintain the robust performance.

Shayeghi H. and H. A. Shayanfar (2005), presented ‘Mixed H2/H∞ Based LFC of a

Deregulated Power System’. In this paper, a decentralized robust controller for the Load

Frequency Control (LFC) of a power system in the deregulated environment is proposed. A

generalized model for the LFC scheme is developed based on the possible contracts in the new

environment. The proposed method is tested on a three-area power system with the possible

contracted scenarios under large load demands. The results are shown to maintain robust

performance in the presence of specified uncertainties and system nonlinearities for a wide range

of area load demands and disturbances in comparison with the PI controller.

Shayeghi Hossein and Heidar Ali Shayanfar (2005), presented ‘Design of Decentralized

Robust LFC in a Competitive Electricity Environment’. A new decentralized robust controller for

Load Frequency Control (LFC) in a deregulated electricity environment is presented in this paper.

This newly developed design strategy combines the advantage of the H2 and H1 control

synthesizes and gives a powerful multi-objectives design addressed by the Linear Matrix

Inequality (LMI) techniques. The effectiveness of the proposed method is demonstrated on a

three-area power system with possible contracted scenarios under large load demands. The

results of the proposed controller are compared with the conventional PI controller and are shown

to maintain robust performance in the presence of specified uncertainties and system

nonlinearities.

Koji Abe et al (2006), presented ‘New Load Frequency Control Method suitable for Large

Penetration of Wind Power Generations’. In this paper, it propose a designing method of a load

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frequency control using disturbance observer when a large amount of wind power generations are

introduced in the power system. The disturbance cancellation problem in the disturbance

observer is considered. The disturbance observer estimates disturbances from observable

quantities of states, and cancels the effect of the disturbance. By this method, the instantaneous

power variations of the wind power generations can be suppressed. As an example, it has been

run simulations for a three-area longitudinal system to compare the proposed method with a

conventional method (PI type controller).

Liu Le et al (2008) presented ‘Object-controllable and Predictive Frequency Bias Coefficient

Setting Method’. In order to implement object-controllability and pre-control of AGC, a method

of estimating frequency bias coefficient by using multi-objective optimization technology and

very short-term load prediction is presented. For practical implementation, the method is

designed based on discrete-time system. The method is examined by digital simulation with a

three-area system model. The results showed that the method is accurate and effectual for

estimating B coefficient, and the performance of interconnected power systems is improved by

using the object-controllable and predictive frequency bias coefficient

Kresimir Vrdoljak and Muharem Mehmedovic (2008), presented ‘Optimal Parameters for

Sliding Mode Based Load-Frequency Control in Power Systems’. One of main obstacles in the

usage of sliding mode based load-frequency control in a power system is the difficulty in

choosing optimal controller parameters. Those parameters define the sliding surface and also

dynamics of the reaching law. Constraints upon the choice of those parameters come out from the

requirements of system’s stability and no steady state error. In this paper the parameters are

computed using a genetic algorithm. Obtained optimal parameters are tested on simulations,

which are conducted on a power system model consisting of three interconnected control areas.

Zhang Yao et al (2009), presented ‘Load Frequency Control for Multiple-Area Power Systems’.

This paper presents the development and application of an Active Disturbance Rejection

Controller (ADRC) to regulate the frequency error for a three-area interconnected power system.

The effectives of the controller are validated by both simulation results and a frequency-domain

analysis of the control system.

Prabhat Kumar and Ram Naresh Mishra (2008), presented ‘Optimal Control of 3-Area

Interconnected Hydro-Thermal Power Systems with EHVAC/HVDC Links’. In this paper, an

attempt is made for optimal control of 3-area interconnected Hydro-Thermal power systems with

EHVAC/HVDC links when subjected to small step load perturbations. The system responses

have been simulated in Matlab. Responses of deviation in frequencies, deviation in tie line power

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and integral of area control errors have been plotted for three areas. Thus, on the basis of these

responses, the dynamic performance of the system has been studied.

Wen Tan (2010) presented ‘Unified Tuning of PID Load Frequency Controller for Power

Systems via IMC’. A unified PID tuning method for load frequency control (LFC) of power

systems is discussed in this paper. The tuning method is based on the two-degree-of-freedom

(TDF) internal model control (IMC) design method and a PID approximation procedure. The

time-domain performance and robustness of the resulting PID controller is related to two tuning

parameters, and robust tuning of the two parameters is discussed. The method is applicable to

power systems with non-reheated, reheated, and hydro turbines. Simulation results show that it

can indeed improve the damping of the power systems. It is shown that the method can also be

used in decentralized PID tuning for multi-area power systems.

2.3.2 Based on ANN Control Technique

Demiroren A. et al (2001) presented ‘The Application of ANN Technique to Load-frequency

Control for Three-area Power System’. This paper includes an application of layered artificial

neural network controller to study load frequency control problem in power system. The

proposed control has been designed for a three-area interconnected power system that two areas

include steam turbines and the other area includes a hydro turbine. Only one artificial neural

network (ANN) controller, which controls the inputs of each area in the power system together,

is considered. In the study, back propagation-through- time algorithm is used as neural network

learning rule. The performance of the power system is simulated by using conventional integral

controller and ANN controller, separately. By comparing the results for both cases, the

performance of ANN controller is better than conventional controllers.

Bevrani H et al (2006) presented ‘Load-frequency regulation under a bilateral LFC scheme

using flexible neural networks’. A new approach based on artificial Flexible Neural Networks

(FNNs) is proposed to design of load frequency controller for a large scale power system in a

deregulated environment. In this approach, the power system is considered as a collection of

separate control areas under the bilateral Load Frequency Control (LFC) scheme. The proposed

control methodology was applied to a 3-control area power system under a bilateral LFC scheme.

Simulation results demonstrated the effectiveness of methodology. It has been shown that the

suggested FNN load frequency controllers give better ACE minimization and a quick

convergence to the desired trajectory in comparison with one based on the traditional ANNs.

Sundaram V. Shanmuga and T. Jayabarathi (2011) presented ‘An Investigation of ANN

based PID Controllers using Three- Area Load Frequency Control in Interconnected Power

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System’. The objective of LFC is to minimize the transient deviations and to provide zero steady

state errors of these variables in a very short time. This paper deals with various controllers like

proportional integral (PI), Proportional Integral Derivative (PID) and ANN (Artificial neural

network) tuned PID controller for three area load frequency control. The performance of the PID

type controller with fixed gain, Conventional integral controller (PI) and ANN based PID (ANN-

PID) controller have been compared through MATLAB Simulation results.

2.3.3 Based on Fuzzy Control Technique

Mathur H.D. and H.V. Manjunath (2006) presented ‘Extended Fuzzy Logic Based Integral

Controller for Three Area Power System with Generation Rate Constraint’. In this paper, a fuzzy

logic controller is proposed for load frequency control problem of electrical power system. The

fuzzy controller is constructed as a set of control rules, and the control signal is directly deduced

from the knowledge base and the fuzzy inference. The study has been designed for a three area

interconnected power system with generation rate constraint. Simulation results of the proposed

fuzzy controller are presented and it has been shown that proposed controller can generate the

best dynamic response following a step load change. Robustness of proposed controller is

achieved by analyzing the system response with varying system parameters.

Shayeghi Hossein et al (2007) presented ‘Multi Stage Fuzzy PID Load Frequency Controller In

A Restructured Power System’. In this paper, a multi stage fuzzy Proportional-Integral-

Derivative (PID) type controller is proposed to solve the Load Frequency Control (LFC) problem

in a restructured power system that operates under deregulation based on the bilateral policy

scheme. The proposed method is tested on a three-area power system with different contracted

scenarios under various operating conditions. Simulation results show that the proposed strategy

is very effective and guarantees good robust performance against parametric uncertainties, load

changes and disturbances even in the presence of GRC.

Soundarrajan and S. Sumathi (2009) presented ‘Effect of Non-linearities in Fuzzy Based Load

Frequency Control’. This paper resents an approach for designing fuzzy logic based load

frequency controller with the presence of non-linearity and obtaining better dynamic response as

compared to conventional controllers. This paper also develops an extended control to LFC

scheme with the presence of generation rate constraint (GRC) non-linearity to a typical three area

power system model proposed by Hadi Sadaat. The simulation has been conducted in MATLAB

Simulink package for the three area interconnected power system with various load changes. The

simulation result shows that the proposed method of fuzzy logic controller for load frequency

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control is giving 40% reduction in settling time and 20% reduction in peak overshoot when

compared to conventional controller.

Soundarrajan, and S. Sumathi (2009), presented ‘Effect of Non-linearities in Fuzzy Based

Load Frequency Control’. This paper presents an approach for designing fuzzy logic based load

frequency controller with the presence of non-linearity and obtaining better dynamic response as

compared to conventional controllers. This paper also develops an extended control to LFC

scheme with the presence of generation rate constraint (GRC) non-linearity to a typical three area

power system model proposed by Hadi Sadaat. The simulation has been conducted in MATLAB

Simulink package for the three area interconnected power system with various load changes. The

result shows that the proposed method of fuzzy logic controller for load frequency control is

giving 40% reduction in settling time and 20% reduction in peak overshoot when compared to

conventional controller.

Sudha K.R. et al (2012) presented ‘Fuzzy C-Means clustering for robust decentralized load

frequency control of interconnected power system with Generation Rate Constraint’. The present

paper proposes the generation of optimal Fuzzy rule base by Fuzzy C-Means clustering technique

(FCM) for load frequency control. The phase-plane plot of the inputs of the Fuzzy controller is

utilized to obtain the rule-base in the linguistic form. The system parametric uncertainties are

obtained by changing parameters by 40% simultaneously from their typical values. The

performance of the proposed FCM controller is compared with conventional controller and

original Fuzzy controller in the presence of Generation Rate Constraint (GRC) in case of two

areas and three areas inter connected power systems.

2.3.4 Based on ANFIS Technique

Khuntia Swasti R. and Siddhartha Panda(2012), presented ‘Simulation study for

automatic generation control of a multi-area power system by ANFIS approach’. This paper

deals with the application of artificial neural network (ANN) based ANFIS approach to

automatic generation control (AGC) of a three unequal area hydrothermal system. The

design objective is to improve the frequency and tie-line power deviations of the

interconnected system. 1% step load perturbation has been considered occurring either in

any individual area or occurring simultaneously in all the areas. It is a maiden application

of ANFIS approach to a three unequal area hydrothermal system with GRC considering

perturbation in a single area as well as in all areas. The performance of the ANFIS

controller is compared with the results of integral squared error (ISE) criterion based

integral controller published previously.

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2.4 FOUR AREAS POWER SYSTEM

2.4.1 Based on ANN Control Technique

Zeynelgil H.L. et al (2004) presented ‘The application of ANN technique to automatic

generation control for multi area power system’. This paper presents an application of layered

artificial neural network controller (ANN) to study automatic generation control (AGC) problem

in a four-area interconnected power system that three areas include steam turbines and the other

area includes a hydro turbine. Each area of steam turbine in the system contains the reheat effect

non-linearity of the steam turbine and the area of hydro turbine contains upper and lower

constraints for generation rate. Only one ANN controller, which controls the inputs of each area

in the power system together, is considered. In the study, back propagation-through-time

algorithm is used as ANN learning rule. By comparing the results for both cases, the performance

of ANN controller is better than conventional controllers.

2.4.2 Based on Fuzzy Control Technique

Emre Ozkop et al (2010) presented ‘Load Frequency Control in Four Area Power Systems

Using Fuzzy Logic PI Controller’. This paper present a load frequency control in four area power

systems using fuzzy gain scheduling of PI controller is realized. The system simulation is

realized by using Matlab/ Simulink software. System dynamic performance is observed for

conventional PI, fuzzy PI and fuzzy logic controllers. The system dynamic performances are

observed via using different controllers.

Summary

The literature survey shows that much more work has been presented on power system load

frequency control problems for single area, two area and three areas interconnected power system.

Lesser attention has been given for multi (four or more) areas inter connected conventional

power system. Emre et al 2010, presented four area load frequency control of thermal-thermal

power plants by using fuzzy-PID control technique. But four area hydro thermal reheat power

plant with hybrid intelligent control by using ANN, Fuzzy and ANFIS controllers are not been

yet tested so for.

Therefore in this thesis work, Hybrid Load frequency intelligent controllers are tested on four

area hydro thermal reheat power system and results are compared with already published results

which reveals the proposed hybrid neuro-fuzzy approach in four area interconnected power

system is quite satisfactory.