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346 IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 20, NO. 1, FEBRUARY 2005

Recent Philosophies of Automatic Generation ControlStrategies in Power Systems

Ibraheem, Prabhat Kumar, and Dwarka P. Kothari, Senior Member, IEEE

Abstract—An attempt is made in this paper to present critical lit-erature review and an up-to-date and exhaustive bibliography onthe AGC of power systems. Various control aspects concerning theAGC problem have been highlighted. AGC schemes based on pa-rameters, such as linear and nonlinear power system models, clas-sical and optimal control, and centralized, decentralized, and mul-tilevel control, are discussed. AGC strategies based on digital, self-tuning control, adaptive, VSS systems, and intelligent/soft com-puting control have been included. Finally, the investigations onAGC systems incorporating BES/SMES, wind turbines, FACTSdevices, and PV systems have also been discussed.

Index Terms—AC/DC transmission links, automatic generationcontrol, deregulated power systems, load frequency control, mul-tilevel control.

NOMENCLATURE

ACE Area Control ErrorAFC Automatic Frequency ControlAFRC Automatic Frequency Ratio ControlAGC Automatic Generation ControlAI Artificial IntelligenceANN Artificial Neural NetworkAVR Automatic Voltage RegulatorBES Battery Energy StorageCES Capacitive Energy StorageCPS Control Performance StandardDCS Disturbance Control StandardDPM DISCO Participation MatrixDTS Dispatcher Training SimulatorEACC Error Adaptive Control ComputerEDC Economic Dispatch ControllerFACTS Flexible Alternating Current Transmission SystemGAs Genetic AlgorithmsGENCOs Generation CompaniesGRC Generation Rate ConstraintIGBT Insulated Gate Bipolar TransistorISE Integral Square ErrorLFC Load Frequency ControlLQI Linear Quadratic IntegralLQR Linear Quadratic RegulatorMES Magnetic Energy Storage

Manuscript received July 10, 2004. Paper no. TPWRS-00272-2003.Ibraheem is with Department of Electrical Engineering, Faculty of En-

gineering and Technology, Jamia Millia Islamia, New Delhi 110025, India(e-mail: [email protected]).

P. Kumar is with Department of Electrical Engineering, Faculty of Engi-neering and Technology, Aligarh Muslim University, Aligarh 202002, India.

D. P. Kothari is with Centre for Energy Studies, Indian Institute of Tech-nology, New Delhi 110016, India.

Digital Object Identifier 10.1109/TPWRS.2004.840438

NERC North American Electric Reliability ControlNNs Neural NetworksNRPS Northern Region Power SystemOPF Optimal Power FlowPI Proportional plus IntegralPID Proportional, Integral, and DerivativePLCC Power Line Carrier CommunicationPV PhotovoltaicRF Redox FlowRTOPF Real-Time Optimal Power FlowSA Simulated AnnealingSMES Super conducting Magnetic Energy StorageSTC Self Tuning ControlSVC Static Var CompensatorUHVAC Ultra-High-Voltage Alternating CurrentVSC Variable Structure ControllerVSS Variable Structure System

I. INTRODUCTION

THE successful operation of interconnected power systemsrequires the matching of total generation with total load

demand and associated system losses. With time, the operatingpoint of a power system changes, and hence, these systems mayexperience deviations in nominal system frequency and sched-uled power exchanges to other areas, which may yield undesir-able effects [1].

There are two variables of interest, namely, frequency andtie-line power exchanges. Their variations are weighted togetherby a linear combination to a single variable called the ACE. TheAGC problem has been augmented with the valuable researchcontributions from time to time, like AGC regulator designs in-corporating parameter variations/uncertainties, load character-istics, excitation control, and parallel ac/dc transmission links.The microprocessor-based AGC regulator, self-tuning regulator,and adaptive AGC regulator designs have also been presented.The most recent advancement in this area is the application ofconcepts like neural networks, fuzzy logic, and genetic algo-rithms to tackle the difficulties associated with the design ofAGC regulators for the power systems with nonlinear modelsand/or insufficient knowledge about the system required for itsaccurate modeling. Apart from advances in control concepts,there have been many changes during the last decade or more,such as deregulation of power industry and use of SMES, windturbines, and PV cells as other sources of electrical energy tothe system. Due to these, the control philosophies associatedwith AGC have changed to accommodate their dynamics and ef-fects on overall system dynamic performance. The present studycovers the critical review of a wide range of methodologies of

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IBRAHEEM et al.: RECENT PHILOSOPHIES OF AUTOMATIC GENERATION CONTROL STRATEGIES IN POWER SYSTEMS 347

AGC regulator designs of power systems with their salient fea-tures.

II. OVERVIEW OF AGC SCHEMES

The first attempt in the area of AGC has been to control thefrequency of a power system via the flywheel governor of thesynchronous machine. This technique was subsequently foundto be insufficient, and a supplementary control was included tothe governor with the help of a signal directly proportional tothe frequency deviation plus its integral. This scheme consti-tutes the classical approach to the AGC of power systems. Veryearly works in this important area of AGC have been by Cohnet al. [2]–[6]. These works were based on tie-line bias controlstrategy. Quazza [7] illustrated noninteractive control consid-ering i) noninteraction between frequency and tie-line powerscontrols and ii) each control area taking care of its own load vari-ations. The investigations with large signal dynamics of LFCsystems were reported by Aggarwal and Bergseth [8]. The rev-olutionary optimal control concept for AGC regulator designsof interconnected power systems was initiated by Elgerd [9]. Atechnique based on coordinated system-wide correction of timeerror and inadvertent interchange was incorporated in an AGCstudy by Cohn [10]. Supplementary controllers were designedto regulate the ACEs to zero effectively. Later on, energy sourcedynamics were incorporated in AGC regulator design [11].

The standard definitions of the terms associated with the AGCof power systems were finalized in [12]. Following that, sugges-tions for dynamic modeling for LFC are discussed thoroughlyin [13]–[15]. Based on the experiences with actual implemen-tation of AGC schemes, modifications to the definition of ACEare suggested from time to time to cope with the changed powersystem environment [16]–[19]. Since many presently regulatedmarkets are likely to evolve into a hybrid scheme, and somederegulated markets are already of this type (e.g., Norway), theeffects of deregulation of the power industry on LFC have beenaddressed through [20].

A. Types of Power System Models

The AGC problem has been dealt with extensively for morethan three decades. The major part of the work reported sofar has been performed by considering linearized models oftwo/multiarea power systems [3], [4], [7], [9], [21], [22]. Lateron, the effect of GRC was included in these types of studies,considering both continuous and discrete power system models[11], [22]. Incorporating the dynamics of the energy source inAGC regulator design, Kwatny et al. [11] have proposed anoptimal tracking approach to AGC, considering load to be theoutput of the dynamic system.

The small signal analysis is justified for studying the systemresponse for small perturbations. However, the implementationof AGC strategy based on a linearized model on an essentiallynonlinear system does not necessarily ensure the stability of thesystem. Considerable attention has been paid by researchersto consider the system nonlinearities [24]–[27]. Tripathy [27]demonstrated the destabilizing effect of governor dead-bandnonlinearity on conventional the AGC system. It is shown thatgovernor dead-band nonlinearity tends to produce continuous

oscillations in the area frequency and tie-line power transientresponse.

B. Control Techniques

The pioneering work by a number of control engineers,namely Bode, Nyquist, and Black, has established links be-tween the frequency response of a control system and itsclosed-loop transient performance in the time domain. Theinvestigations carried out using classical control approachesreveal that it will result in relatively large overshoots and tran-sient frequency deviation [9], [28], [29]. Moreover, the settlingtime of the system frequency deviation is comparatively longand is of the order of 10–20 s.

The AGC regulator design techniques using modern optimalcontrol theory enable the power engineers to design an optimalcontrol system with respect to given performance criterion.Fosha and Elgerd [30] were the first to present their pioneeringwork on optimal AGC regulator design using this concept. Atwo-area interconnected power system consisting of two iden-tical power plants of nonreheat thermal turbines was consideredfor investigations. A new formulation for optimal AGC strategyhas been witnessed in [31].

The feasibility of an optimal AGC scheme requires the avail-ability of all state variables for feedback. However, these effortsseem unrealistic, since it is difficult to achieve this. Then, theproblem is to reconstruct the unavailable states from the avail-able outputs and controls using an observer. Considering statereconstruction, many significant contributions have been made[32]–[37]. Bohn and Miniesy [32] have studied the optimumLFC of a two-area interconnected power system by making theuse of i) differential approximation and ii) a Luenberger ob-server and by introducing an adaptive observer for identificationof unmeasured states and unknown deterministic demands, re-spectively. Exploiting the fact that the nonlinearity of the powersystem model, namely, the tie-line power flow, is measurable,the observer has been designed to give zero asymptotic error,even for the nonlinear model.

AGC schemes based on an optimal observer, which is astate estimator with decaying error at a desired speed, using anonlinear transformation [33] and reduced-order models with alocal observer [34] have appeared in the literature. A simplifiedgenerating unit model oriented toward LFC and the methodfor its transfer function identification based on a two-stageprocedure indirectly reducing both noise effects and transferfunction order is presented in [37].

Due to practical limitations in the implementation of regula-tors based on feedback of all state variables, suboptimal AGCregulator designs were considered [38]–[40]. A suboptimal andnear-optimal LFC concept using modern control theory is pre-sented by Moorthy and Aggarwal [38].

Apart from optimal/suboptimal control concepts, modal con-trol theory has also been used to design AGC regulators forpower systems. The design method employing modal and sin-gular perturbation techniques to affect decoupling of the in-terconnection into its subsystem components has appeared in[41]. In the method, after achieving the decoupling, local con-trollers for each subsystem are designed individually to place the


closed-loop poles of each subsystem in some prespecified loca-tions in the complex plane, and then, the resulting controllersare used to generate local control inputs, using local informa-tions only. The AGC regulator design using Lyapunov’s secondmethod and utilizing minimum settling time theory has beenproposed by Shirai [42]. The importance of the dominant timeconstant of the closed-loop systems in designing the regula-tors has been emphasized. The author has reported a bang-bangAGC policy based on this method.

C. Control Strategies

In the early days, the AGC problem of power systems wasdealt with using control strategies based on centralized con-trol strategy [7], [9], [30], [40]. Many control strategies havebeen proposed on the basis of classes of disturbances [7]. Elgerdand Fosha [9] suggested a feedback and loop gain to eliminatethe disturbance, and they also suggested a different feedbackform to develop optimal controllers [30] for an electrical energysystem. They assumed the load disturbances to be deterministic.They proposed a proportional controller, disregarding the steadystate requirements and compensation of load disturbances. Themain limitation of the works presented on AGC consideringcentralized control strategy is the need to exchange informationfrom control areas spread over distantly connected geographicalterritories along with their increased computational and storagecomplexities.

The decentralized AGC concept appeared in the powersystem control scenario to deal with such problems very ef-fectively, and consequently, many research papers using thisconcept with continuous and discrete time system models haveappeared in the literature [43]–[50]. In [46], the authors haveexamined the structural properties of observability and control-lability for a class of interconnected power system models. Theproposed scheme provides for the complete decentralizationof a global state feedback control policy in the sense that thearea control feedback loops are completely decoupled. Again, aclass of systematic distributed control design methods based oni) distributed implementations of centralized control systems,ii) model reduction of dynamical systems, and iii) modelingof the interactions between the subsystems comprising theglobal control system is presented in [77]. The beauty of thedesign is to achieve almost identical results as obtained withthe centralized one. The design of decentralized load frequencycontrollers based on structured singular values is discussed in[78].

Various AGC schemes based on two-level [81] and multi-level [82]–[84] control concepts have been reported in the lit-erature. A two-level suboptimal controller has been suggestedby Miniesy and Bohn [81]. However, this approach does not en-sure zero steady state error, and hence, a multilevel finite timeoptimal controller design ensuring zero steady-state error hasbeen reported in [82]. The advantage of hierarchical structure isreflected in the fact that even if one of the control levels fails,the system remains in operation.

A global controller, which also exploits the possible benefi-cial aspects of interconnections, has been applied for the LFCproblem [84], and favorable results have been achieved. The re-duction of control efforts required in the AGC of interconnected

power systems is sought with the help of a singular perturbationapproach. This can be achieved by decomposing the system intoslow and fast subsystems and designing controllers separatelyfor each of the subsystems, and the controllers are combined toyield a composite controller. Using this approach, the investi-gations on the AGC of large power systems are available in theliterature [87], [88]. The separate controllers were designed forslow and fast subsystems and were combined in such a way thatthe slow subsystem always interacts with only one of the fastsubsystems at a time [88]. The study also involves the effect ofparameter variation and GRC.

D. Excitation Control and Load Characteristics

In most of the AGC studies, it is assumed that there is no inter-action between the power/frequency and reactive-power/voltagecontrol loops. It may be permissible only when the speed of theexcitation systems is much faster than that of the LFC system,but in practical systems, during dynamic perturbations, theredoes exist some interaction between these two control chan-nels [27]. Some papers consider this aspect [83], [89]–[93]. Aliterature survey [90] shows that Durick [89] is probably thefirst to investigate the damping effects of voltage control in atwo-area LFC system, assuming that i) reactive-power/voltagecontrol loop has a much faster response than power/frequencycontrol loop and, thus, taking the area voltage perturbation tobe directly available as a control variable, and ii) area voltageperturbation does not have any effect on the area load. Consid-ering these assumptions unrealistic, a realistic LFC model wasdeveloped by including the excitation control in one area andvoltage-perturbation as the input in the other [90]. The changein load demand due to voltage perturbation is considered in bothareas.

Considerable research work has been carried out for the AGCof interconnected power systems incorporating the load charac-teristics [49], [94], [95], [98], [99]. A method to obtain the re-sponse of a large power system to cyclic load variations by mod-eling the power system by a set of first-order, linear differentialequations and the load variation as a Fourier series pattern wasdemonstrated by Van Ness [94]. The solution of the problem ofoptimum load frequency sampled data control with either un-known deterministic load or randomly varying system distur-bances is discussed in [49]. Introducing an adaptive observertreated the random load demands and random disturbances.

The study has also been carried out with exciter and speedgovernor control loops for voltage-dependent load character-istics on stabilizing intersystem oscillations [62]. The AGCproblem has been investigated using disturbance-accommoda-tion control. It was shown that the optimal accommodation ofload disturbances could lead to significantly better performancethan that of conventional controllers. It was further shownthat the complete cancellation of all disturbance effects in theclass of power systems considered is impossible. Nevertheless,the disturbance effects in system frequency can be cancelledcompletely.

E. Digital AGC Schemes

Since digital control is more accurate and reliable, compactin size, less sensitive to noise and drift, and more flexible, the re-


searchers have focused their attention on proposing digital AGCcontrol schemes [64]–[71]. Ross [64] was probably the first topresent a comprehensive direct digital LFC regulator for powersystems. Later, the control philosophy and design techniques ofa digital LFC incorporating dynamic control criteria for perfor-mance evaluation of digital control system based on field testresults was outlined by Ross and Green in [65]. As the ACErepresenting generation mismatch in an area can be derived indiscrete mode by sampling the tie-line power and system fre-quency deviation and then transferring over the telemeteringlinks and unlike in continuous-time system, the control vectorin the discrete mode is constrained to remain constant betweenthe sampling instants. Based on this fact, Bohn and Miniesy[32] have analyzed the effect of the sampling period on thesystem’s dynamic behavior using a discrete model of a singlearea power system. An informative work on digital AGC mod-eling, including the criterion for evaluation of system dynamicperformance with the help of indices that measure the effec-tiveness of control relative to control efforts, is discussed byDemello and Mills [66].

Kothari and coworkers [23], [70] have studied the AGC in dis-crete mode. The investigations were carried out with more real-istic modeling of AGC strategy, i.e., considering that the systemis operating in continuous mode and the controller is operatingin discrete mode [23]. In [70], discrete mode AGC of an inter-connected power system with reheat thermal plants consideringa new ACE is described. The new ACE is derived from tie-linepower deviation, frequency deviation, time error, and inadver-tent interchanges. Optimum integral and proportional integralcontrollers using the concept of stability margin and the ISEtechnique have been obtained with conventional and new ACEs,and their dynamic performance was compared for a step-loaddisturbance.

F. Sensitivity Features

An optimal AGC regulator design based on nominal systemparameter values may not really be optimal for the system withparametric variations/uncertainties due to various system oper-ating and environmental conditions, and therefore, the imple-mentation of these regulators on the system may be inadequateto provide the desired system functioning. This could result ina degraded system dynamic performance and sometimes also inthe loss of system stability. Therefore, considerable work hasalso been presented on AGC that considers sensitivities of thesystem parameter variations [72]–[84].

In the late 1960s, a sensitivity study was included in an opti-mization analysis to determine optimal parameter values of con-ventional AGC systems by Van Ness [72]. The VSS controllershave an advantage over the controllers based on the linear op-timal control theory in selecting the values of the parametersin many different ways of a VSS controller. Insensitivity to pa-rameter variation can be achieved by designing variable struc-ture AGC regulators. Erschler et al. [76] are probably the firstto investigate the AGC of hydropower systems using the VSStechnique.

It may be noted that the VSS controllers have improved tran-sient response due to load disturbances in the power system.By properly selecting the parameters of the controller, the fre-

quency deviations and tie-line powers effectively can be con-trolled. The research publications regarding the design of loadfrequency controllers for interconnected power systems incor-porating the system parametric uncertainties are reported in theliterature [80]–[85]. A control technique based on the applica-tion of linear feedback infinity robust controllers in thepower system model to control the frequency deviations wasproposed by Ismail [80]. This approach suggests that the con-troller response should be fast enough to offset the frequencyerrors due to load variations.

A robust controller based on the Riccati equation approachhas been proposed for the power system by Wang and coworkers[81], [82]. Later, based on a combination of the robust controlapproach and an adaptive control technique, a design procedureof a new robust adaptive controller was proposed for powersystem load-frequency control with system parametric uncer-tainties. The motivation of combining the robust control withan adaptive control was to use the robust control approach todeal with the small parametric uncertainties [82]. The other re-search contributions on decentralized robust LFC based on theRiccati equation approach have appeared in [84]. The designof decentralized robust LFC applying structured singular valuesis proposed by Yang et al. [85]. It has been demonstrated thatwhen the frequency response-based diagonal dominance cannotbe achieved, the structured singular values can be applied to de-sign decentralized LFC to achieve the desired system dynamicperformance [85].

G. Adaptive and Self-Tuning AGC Schemes

Apart from various AGC schemes, adaptive control has beena topic of research for more than a quarter of a century. Ba-sically, the adaptive control systems can be classified into twocategories, namely, the self-tuning regulators and the model ref-erence control systems. The task of adaptive control is to makethe process under control less sensitive to changes in processparameters and to unmodeled process dynamics. A number ofarticles have been reported on adaptive AGC schemes [86]–[91]and STC schemes [92]–[96] for AGC of power systems.

In 1966, Ross [86] described control criteria in LFC and therelated practical difficulties encountered in trying to achievethese criteria. The implementation and analysis of an adaptiveLFC system on the Hungarian power system has been done byVajk et al. [88]. An adaptive controller using a proportional in-tegral adaptation to meet the hyperstability condition require-ments to take care of the parameter changes of the system waspresented by Pan and Liaw [89]. A multiarea adaptive LFCscheme for AGC of power systems [90] and a reduced-orderadaptive LFC for interconnected hydrothermal power system[91] are reported in the literature. A multivariable self-tuningcontroller has been derived by defining a cost function with aterm representing the constraints on the control effort and thenminimizing that with respect to the control vector. Later on, aself-tuning algorithm for AGC of interconnected power systemswas presented by Lee [95].

H. Concepts of AI Techniques: NN, FL, and GA

In practice, many nonlinear processes are approximated byreduced-order models, possibly linear, that are clearly related to


the underlying process characteristics. However, these modelsmay be valid only within certain specific operating ranges, anda different model may be required in the wake of changed op-erating conditions, or the control system should adopt the newsystem model parameters. The advent of AI techniques, suchas neural networks, has solved this problem to a great extent.The neural technology offers many more benefits in the areaof nonlinear control problems, particularly when the system isoperating over the nonlinear operating range. The applicationsof neural networks in power system control are witnessed in[97]–[102].

A new AGC scheme to incorporate the nonconforming loadproblem was presented by Douglas et al. [98], in which an ef-fort had been undertaken to develop algorithms capable of dis-criminating between noncontrollable short-term excursions andcontrollable long-term excursions. Out of the two techniques de-scribed, one was developed using a neural network algorithm forpattern recognition of controllable signals, and the other tech-nique was based on the detection of the controllable signal in thepresence of a noisy random load using a random signal proba-bility model. Test results reveal that neural network-based AGCimplementation had a significant improvement over the modernAGC implementation. LFC system performance was evaluatedwith a nonlinear neural network controller using a generalizedneural structure to yield better system dynamic performancethan the individual neurons [99].

Recently, a four-area interconnected power system modelwith reheat nonlinearity effect of the steam turbine and upperand lower constraints for generation rate nonlinearity of hydroturbine was considered for the investigation in [101]. It hasbeen shown in [102] that the AGC problem can be viewed asa stochastic multistage decision-making problem or a MarkovChain control problem and have presented algorithms fordesigning AGC based on a reinforcement learning approach.

The fuzzy logic control concept departs significantly fromtraditional control theory, which is essentially based on math-ematical models of the controlled process. Instead of derivinga controller via modeling the controlled process quantitativelyand mathematically, the fuzzy control methodology tries to es-tablish the controller directly from domain experts or operatorswho are controlling the process manually and successfully. Re-cently, many studies exploiting the fuzzy logic concept in AGCregulator design dealing with various system aspects have ap-peared in the literature [103]–[105].

More recent contributions considering the problem of de-composition of multivariable systems for the purpose of dis-tributed fuzzy control was reported by Gegov [104]. The pro-posed decomposition method has reduced the number of inter-active fuzzy relations among subsystems. The concept and de-velopment of AGC using ANN and fuzzy set theory to utilizethe novel aspects of both in single hybrid AGC system designfor power systems has also been mooted [106].

These days, GA is the most popular and widely used algo-rithm of all the intelligent algorithms. GAs have been widelyapplied to solve complex nonlinear optimization problems in anumber of engineering disciplines in general and in the area ofAGC of power systems in particular [106]–[113]. In [107], op-timum adjustment of the classical AGC parameters using GAs

is investigated. An array of performance indices based on var-ious functions of error and time is considered for the study.

A reinforced GA has been proposed as an appropriate op-timization method to tune the membership functions and rulesets for fuzzy gain scheduling of load frequency controllers ofmultiarea power systems to improve the dynamic performance[108]. The proposed control scheme incorporates dead-band andgeneration-rate constraints also. Later, contrary to the trial-and-error selection of the variable structure feedback gains, a geneticalgorithm-based selection of feedback gains has been advocatedfor load frequency variable structure controller in [109]. The se-lection scheme provides an optimal feedback gains selection inthe VSC, and the test results show that not only the dynamicperformance has been improved, but also, the control effort isdramatically reduced. Karnavas et al. [106] have presented acomprehensive study on AGC of an autonomous power systemusing combined intelligent techniques.

A higher order robust dynamic performance is achievedwith LFC designs based on GA and linear matrix inequalities[112]. The desired control parameters have been obtained bycoordinating GA with linear matrix inequalitie control toolboxoptimization. In [113], a new GA/GA-SA-based fuzzy AGCscheme of a multiarea thermal generating system is developed.The scheme is capable of evaluating the fitness of GA/hybridGA-SA optimization by selecting a function like “figure ofmerit,” which directly depends on transient performance char-acteristics like settling times, undershoots, overshoots, and timederivative of frequency. The hybrid GA-SA technique yieldsmore optimal gain values than the GA method.

I. Types of Inter-Ties

The HVDC transmission has emerged on a power scenario,due to its numerous technical and economic advantages, for alarge chunk of power transfer over large distances. Besides otherapplications, the commissioning of an HVDC link in parallelwith existing ac links has shown beneficial effects from the pointof view of stabilization of the system.

Considerable attention has been paid to consider the dampingeffect of the dc system as an area interconnection between acsystems. As far as the system frequency control of power sys-tems interconnected via a dc link is concerned, very few pub-lications have appeared on this topic [114]–[116]. An AFRCsystem on an HVDC transmission utilizing the high-speed con-trol features of a dc system, cooperating with automatic fre-quency control on interconnected ac systems, is developed byYoshida et al. [114]. Later, the effects of an AFRC system onan HVDC transmission to the AFC on ac systems when AFRCis applied to a random load disturbance in a steady state. Thefrequency improving and reduction effects of the output powerof regulating power stations by AFRC are analyzed by a digitalcomputer [115]. A new dc AFC system, which applies a mul-tivariable control to the dc system-based frequency control andcapable of controlling the frequencies of the two ac systems op-timally while maintaining their stability, is developed by Sanpeiet al. [116].

Considerable research work on the LFC of interconnectedpower systems incorporating ac and dc links is contained in[117]–[121]. Investigations on decentralized robust LFC of a


multiarea interconnected power system with ac as well as fre-quency-controllable HVDC links are reported in [118]. A com-prehensive research work has been carried out by proposing op-timal AGC regulators for two-area power systems with parallelac/dc links by Kumar and Ibraheem [119]–[121]. The intercon-nected power systems were investigated with the implementa-tion of designed optimal regulators by considering the incre-mental dc link power flow as an additional state as well as con-trol variable. The investigations reveal that the system dynamicsystem performance has improved appreciably with the inclu-sion of incremental dc link power flow as an additional statevariable as compared to that obtained when system intercon-nection is through the ac link only.

J. AGC Incorporating BES, SMES, SVC, Wind Turbine, andPV Systems

Most of the solutions proposed so far for AGC have not beenimplemented practically due to system operational constraintsassociated with thermal power plants. The main reason is thenonavailability of required power other than the stored energyin the generator rotors, which can improve the performance ofthe system, in the wake of sudden increased load demands. Afast-acting BES can effectively dampen electromechanical os-cillations in a power system, because they provide storage ca-pacity in addition to the kinetic energy of the generator rotor,which can share the sudden changes in the power requirement.An attempt to use battery energy storage to improve the LFCdynamics of West Berlin Electric Supply System has appearedin the literature [122]. In [123], it has been revealed that BES ishelpful in meeting sudden requirements of real power load andis effective in reducing the peak deviations of frequency andtie-line power and also reduces the steady-state values of timeerror and inadvertent interchange accumulations.

The problems like low discharge rate, increased time requiredfor power-flow reversal, and the maintenance requirement haveled to the evolution of SMESs for their application as load fre-quency stabilizers [124]–[131]. In [126], the study of effects ofSMES on AGC has been done considering governor dead-bandnonlinearity, steam reheat constraints, and boiler dynamics. Thedigital computer model was developed, and parameter optimiza-tion of the controller was carried out by the second method ofLyapunov, which ensures the stability of the system. From thestudy, it was observed that the use of ACE for the control ofSMES units substantially reduces the tie-line power deviation,and the action of SMES is localized with diminished contribu-tion for load disturbances in the other interconnected area, ascompared to using frequency deviation as the control signal. Theperformance of the adaptive-controlled SMES is compared withthat of nonadaptive SMES, keeping the supplementary controlas the conventional one with the integral controller in [125]. Ithas been observed that when the SMES control is adaptive, theperformance is almost insensitive to controller gain parametervariation.

The effect of governor dead-band nonlinearity and generationrate constraints, along with the effect of BES system on LFC,was studied by Lu et al. [127]. Later, the feasibility of usingan IGBT converter instead of a thyristor converter as a power

conditioning system with the SMES is studied, and an improvedsystem transient response with SMES has been achieved [128].

Rechargeable batteries such as RF, which are not aged by fre-quent charging and discharging and have a quick response that isequivalent to SMES and outstanding function during overload,are gaining momentum in research and development activities[132].

Presently, small wind turbines are among the candidate sys-tems envisioned to operate in parallel with the utilities’ gen-erators. The combined effect of the customers’ load demandand the wind turbine fluctuating power output will develop anew load-diversity curve for the utility system. As a result, theregulation or LFC requirements could differ significantly frompresent ones. Therefore, studies relating to AGC of power sys-tems incorporating the dynamics of such systems are reported inthe literature [133]–[135]. A method to analyze the effects thatsmall wind turbines may have on the utility’s LFC process hasbeen developed by Curtice et al. [133]. Wind turbine output sce-narios, varying in frequency and magnitude, are combined withsystem load variations to test the effectiveness of present AGCcontrol strategies. The change in the system performance fromthe base case is assessed using ACE values, time between zerocrossings, inadvertent accumulation, and control pulses sent toregulating units.

An AGC scheme for a wind farm in the north of Spain with37 variable speed wind turbines is developed in [134]. Thecontrol scheme is based on two control levels: A supervisorysystem controls active and reactive power of the wind farmby sending out set points to all wind turbines, and a machinecontrol system ensures that set points at the wind turbine levelare reached. The advancements in wind-turbine and microhydrotechnology have made it possible to introduce decentralizedhybrid electric power systems. A variable structure LFC ofisolated wind–diesel–microhydro hybrid power systems wasdeveloped, and dynamic performance has been investigated byBhatti and Kothari [135].

The static VAR compensation systems also have been foundto aid in the damping of oscillations of power system dynamicresponse. A new technique of AGC regulator design, based onSVC, has been suggested in [136]. A feedback signal composedof frequency deviation and reactive power variation has beenused to stabilize the electrical power system. The coefficient ofthese deviations is a function of system and controller param-eters. The influence of a PV system on LFC has also been de-scribed in [137]. Besides the other observations, it has been re-vealed that an electrical power system containing a 10% contri-bution from PV stations would require a 2.5% increase in LFCcapacity over a conventional system. Besides BES, SMES, andCES units, a favorable effect of integrating a fuel cell into thepower system dynamic model on power system dynamic perfor-mance has also been evident [138].

K. AGC in a Deregulated Power System Environment

The classical LFC based on ACE is difficult to implement ina deregulated power system environment. In recent years, sev-eral control scenarios based on robust and optimal approacheshave been proposed for the AGC system in deregulated powersystems. Some research is contained in [20] and [139]–[148].


In a deregulated power system environment, the independentcontract administrator receives contracts with GENCOs to pro-vide area regulation. This is required due to unscheduled gen-eration and load changes and inconsistent frequency bias ex-isting in the system [139]. The load change in the area causesfrequency change, and all governors respond to this change in-stantaneously, whether or not they are selected for AGC. Thegovernor response is defined as area regulation contracts, andthe cost of area regulation is allocated among the players by theratio of their participation. Besides addressing the operationalstructures likely to result from deregulation, the possible ap-proaches to LFC, and associated technical issues, i.e., standardsand algorithms, were described by Christie and Bose [20], andlater, they reported a LFC scheme for hybrid electric power mar-kets in [140].

Two alternative approaches to AGC of interconnected powersystems of Norway and Sweden are introduced by Bakkenand Grande [142] in a deregulated power system environment.The approaches resulted in favorable effects in handling theincreased strain of the system operator caused by the deregu-lated environment. In most of the reported strategies, attemptshave been made to adapt well-tested classical AGC schemesto the changing environment of power system operation underderegulation [141], [146]. A comprehensive study on simula-tion and optimization in an AGC system after deregulation hasbeen carried out by Donde and Pai [145]. The concept of DPMis proposed that helps the visualization and implementation ofthe contracts.

One of the recent developments after deregulation of thepower industry is the necessity of a communication infrastruc-ture to support an increasing variety of ancillary services foreffective implementation of AGC schemes. An article focusingon the communication network requirements for a third-partyLFC service in an interconnected power system was written byBhowmik et al. [147]. Data communication models based onqueuing theory have been proposed in the study.

L. Other AGC Schemes

One of the objectives of optimal AGC is to share generationin the most economic fashion. To meet this objective with otherobjectives of an AGC system, economic load dispatch has to becarried out in conjunction with AGC, subject to some systemconstraints. However, ELD has been differentiated from AGCfunction on the basis of time span, exhibited by ELD and AGCin their implementations. A variety of research papers dealingwith the AGC problem in conjunction with ED/ELD are welldocumented in the literature [148]–[152]. Mukai and his team[149], [150] at Washington University built up an AGC projectthat is probably the most comprehensive. The control system isarea-wise decentralized. It integrates the AGC, economic dis-patch, and dynamic dispatch in a consistent manner and is dedi-cated to performing many functions with various time horizons.The system offers the improved transient responses and solvesthe AGC–ELD interface problem, as exhibited with traditionaloptimal control proposals.

A two-stage RTOPF concept in which classical ED is re-placed in AGC by a RTOPF has been envisioned [151]. Thefirst stage consists of a full OPF initialized from state estimator

and external estimator results, while in the second stage of theRTOPF concept, the constrained ED controls the generatingunits in conjunction with AGC in an optimal way. The RTOPFconcept has been tested successfully in an offline simulationusing a 685-bus network and the IEEE 118-bus network withoutany convergence problem from the algorithm. In addition, theexecution time is of the same order of magnitude as that of aclassical approach. In absorption of the load fluctuations occur-ring on power systems, both EDC and LFC systems were con-sidered separately. The simulation study has been performed fora three-area power system.

A flexible AGC algorithm for a Hellenic interconnectedsystem is given by Vournas et al. [152]. In the algorithm, LFCstability margins are calculated for the case of slow-actingflat-frequency control, and an approximate economic dispatchalgorithm is developed that makes the use of a predeterminedtable of the economic loading of units. The simulation resultshave demonstrated a satisfying operation of the AGC system.

Due to obvious reasons, when large load fluctuations arise,the effective way is to combine LFC with the very short-termload prediction. Generally, AGC periodically updates the set-point power for key “swing” generators using samples of thesystem load and electrical frequency; in typical systems, thecontrol sample rate ranges from 1 to 10 min. To improve perfor-mance, emerging AGC strategies employ a look-ahead controlalgorithm that requires real-time estimates of the system’s loadfor typically 30 to 120 min into the future at a sample rate of 1to 10 min [153]. To align with electric utility industry nomen-clature, this prediction on such a horizon is “very short-term.”

Some of the earlier attempts illustrating theoretical AGC de-signs are highlighted in [17], [154], and [155], and online imple-mentation of AGC schemes are described in [156]–[160]. Basedon online experiences with AGC, a set of procedures and algo-rithms for AGC of generating units that are jointly owned bytwo or more utilities are developed by Podmore et al. [156].

The essential hardware and software modifications requiredin AGC and the automatic voltage control program to meet newoperational and control challenges of the GURI HydroelectricPower Plant (Venezuela) are suggested in [157]. It is recom-mended that redundant signals and RTU pairs be included innew power plant computer control systems or considered as anupgrade feature in existing systems.

Apart from proposing effective and efficient AGC strategies,real-time pricing of electricity has been used as an effectivemeans to achieve improved system dynamic operation. Bergerand Schweppe [161] have demonstrated that real-time pricing inthe presence of system dynamics can aid in LFC. It was demon-strated, for a single-area power system, that prices determinedby a PI feedback control law of frequency deviations could as-sist in LFC. A report dealing with various cost aspects associ-ated with AGC, inadvertent energy, and time error is presentedin [162]. A real-time adaptive pricing for LFC in an intercon-nected power system, taking into account the system dynamicsand giving the importing area a signal in terms of increased pricefor any increment in the drawal from its scheduled value, wassuggested in this study.

Over the decades, the LFC performance of a power systemarea has been assessed by the widely adopted A1 and A2 criteria.


These criteria, based on engineering judgment, had no analyt-ical basis. A pioneering work resulted in the adoption of new andmore sophisticated criteria, namely, CPS1 and CPS2. These cri-teria were still lacking in analytic basis but have been providinggood results in [163] and [165]. An analytical framework forthe formulation and evaluation of control performance criteriain LFC, incorporating explicitly the uncertainty in the measuredvariables in LFC, was reported in [166]. The criteria reportedprovide an analytic rationale for the NERC control performancecriteria. A new AGC is designed to work under NERC’s newCPS and DCS with improved effectiveness efficiency in [164].Texas Utilities Electric Company, in a joint effort with the Uni-versity of Texas at Arlington, is in the process of its implemen-tation. The feasibility of decomposition of ACE to identify theimpact of selected loads on CPS1 and CPS2 under this newNERC’s criteria [167] and its possible practical implementation[168] are addressed in the literature. Later, the work has been ex-tended, incorporating the estimation of the area’s frequency re-sponse characteristic for adaptive frequency bias setting in LFCto ensure the reliability and the responsibility of frequency sup-port [169]. The field tests were carried out with AGC strategythat was developed with the refinements of ACE to improve theaccuracy and its use in decomposing the 1-min average of ACEof a control area to identify the regulation burden associatedwith certain widely varying loads [170].

A comparative analysis of stiff and elastic tie-line modelsused to simulate LFC of two-area as well as multiarea powersystems is demonstrated in [171]. One of the objectives thatAGC must satisfy may be the system safety requirement, re-quiring lengthy calculations, large computing system memoryspace, etc. A new approach to solve the AGC problem of hy-dropower plants stage by stage, using different methods of op-erations research, has been developed in [172].

Louis et al. [173] have developed software for the AGCsystem and investigated various aspects of power system dy-namic models. The implementation of an island AGC functionin a large-scale power system to assist in system emergencyand restoration situations is reported in [174]. It is the firsttime that the conventional AGC function was enhanced to beutilized, rather than to be suspended, under such circumstances.The island AGC function has to be implemented in both thereal-time and the DTS environments.

The uncovered subject material on AGC is available in books[175]–[178], tutorials [179], reviews [180]–[183], and state-of-the-art lectures [184].

III. CONCLUSION

The paper presents a critical review of the recent philosophiesin the area of AGC. Due attention has also been paid to recentdevelopments, such as AGC schemes based on the concepts ofneural networks and fuzzy logic and the incorporation of par-allel AC/HVDC links in the designs of AGC regulators. Em-phasis has been given to categorizing various AGC strategiesreported in the literature that highlights their salient features.

Although the authors have sincerely attempted to present themost comprehensive set of references on AGC, they would liketo apologize for exclusion of many good papers due to space

constraints and hope that additional references will be advancedas discussion to this publication. It is envisaged that this paperwill serve as a valuable resource to any future worker in thisimportant area of research.

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Ibraheem was born in Giraura of District Etah, UttarPradesh, India, on December 1, 1959. He received theB.Sc. Engg.(Hons.), M.Sc. Engg., and Ph.D. degreesin electrical engineering from Aligarh Muslim Uni-versity, Aligarh, India.

Since January 1988, he has been with the De-partment of Electrical Engineering, Faculty ofEngineering and Technology, Jamia Millia Islamia(Central University), New Delhi, India, where he iscurrently a Professor of electrical engineering. Also,he has been Head of the Department of Electrical

Engineering since 2001. He has published a number of research papers innational/international journals and has been continuously engaged in guidingresearch activities at graduate/post-graduate and Ph.D. levels.

Dr. Ibraheem received a Gold Medal from the Union Ministry of Power andEnergy (India) in 1998 for one of his research articles.

Prabhat Kumar is presently Professor of electricalengineering at Aligarh Muslim University, Aligarh,India, with over 35 years of teaching experience atundergraduate and post-graduate levels. He visitedthe USA in 1975 on a Study Exchange Tour.

Dr. Kumar received a Gold Medal and a KhoslaAward from the University of Roorkee, Roorkee,India, and a Best Paper Award and a High QualityPresentation Award from the Systems Society ofIndia. He received a Union Ministry of EnergyDepartment of Power Medal from the Institution

of Engineers (India). He had been Secretary for the System Society of India,Aligarh, and is a member and national executive of SSI and the Boards ofStudies of various universities and selection committees. He is a reviewer oftechnical papers at the Institution of Engineers (India) and has chaired andcochaired technical sessions at various conferences.

Dwarka P. Kothari (SM’03) is Professor, Centre forEnergy Studies, and Deputy Director (Admn.), In-dian Institute of Technology, New Delhi, India. Hehas guided 25 Ph.D. scholars and has contributed ex-tensively in these areas, as evidenced by the 450 re-search papers authored by him that have been pub-lished in various national and international journalsand conferences. He has also authored 18 books onpower systems. He was Principal of VisvesvaryayaRegional Engineering College, Nagpur, India, from1997 to 1998.

Prof. Kothari has received several best paper awards and gold medals for hiswork.

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