A Literature Survey on Load-frequency Control for Conventional and Distribution Generation Power Systems

Article history:Received 16 AuReceived in rev8 April 2013Accepted 20 Ap

Articial intelligent techniques

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5. Soft computing techniques in LFC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

5.3. Genetic algorithms (GAs) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Contents lists available at SciVerse ScienceDirect

Renewable and Sustainable Energy Reviews

Renewable and Sustainable Energy Reviews 25 (2013) [email protected] (N. Kishor).1364-0321/$ - see front matter & 2013 Elsevier Ltd. All rights reserved.http://dx.doi.org/10.1016/j.rser.2013.04.029

n Corresponding author. Tel.: +91 532 2271411.E-mail addresses: [email protected],5.1. Articial neural network (ANN) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75.2. Fuzzy logic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73.1. Classical control approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3.2. Optimal control approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3.3. Sub-optimal control approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3.4. Adaptive and self-tuning approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4. Control strategies for conventional power systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4.1. Centralized control approaches. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4.2. Decentralized control approaches. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4.3. Two-level and multi-level control strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2.2. Distributed generation power systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43. Control techniques for conventional power systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

. . . . . . . . . . . . . . 5Contents

1. Introduction . . . . . . . . . . . . . . . . .2. Type of power system models . .

2.1. Conventional power syste2.1.1. Single area therm2.1.2. Single area hydro2.1.3. Two area power2.1.4. Three area powe2.1.5. Four area power2.1.6. Power system w2.1.7. Deregulated pow. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3er systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

s . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3s. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3s. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4C-link . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4ms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4Loadfrequency controlOptimal controlKeywords:Distribution generationDeregulated power systems

& 2013 Elsevier Ltd. All rights reserved.e i n f o

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a b s t r a c t

In this paper an extensive literature review on loadfrequency control (LFC) problem in power systemhas been highlighted. The various conguration of power system models and control techniques/strategies that concerns to LFC issues have been addressed in conventional as well as distributiongeneration-based power systems. Further, investigations on LFC challenges incorporating storage devicesBESS/SMES, FACTS devices, winddiesel and PV systems etc have been discussed too.A literature survey on loadfrequency control for conventionaland distribution generation power systems

Shashi Kant Pandey, Soumya R. Mohanty, Nand Kishor n

Department of Electrical Engineering, Motilal Nehru National Institute of Technology, Allahabad-211004, India

a r t i c l

journal homepage: www.elsevier.com/locate/rser

5.4. Particle swarm optimization (PSO) algorithms. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85.5. Tabu search algorithms (TSA) and bacterial foraging optimization algorithm (BFOA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

6. Other controllers for LFC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86.1. Variable structure controller . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86.2. Robust controller . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

7. Use of SMES, BESS and facts devices in conventional power systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87.1. SMES and BESS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87.2. Flexible AC transmission systems (FACTS) devices. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

8. LFC in distributed generation power systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98.1. PV, wind farms, diesel engine and energy storage system based hybrid DG . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98.2. Other DG systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

9. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

etc. is exploited to address the optimization objective. Due to non-

The conventional power system that has been in use since

S.K. Pandey et al. / Renewable and Sustainable Energy Reviews 25 (2013) 318334 319Type of power systemmodels

Control techniques forconventional power

systems

Control strategies forconventional power

systems

LFC by soft computingapproaches: ANN, FL

Other controllers for LFC

LFC incorporating BES,SMES, PV and FACT

devicesOptimization techniques inLFC: GA, PSO,and Tabu

Search

LFC in distributiongeneration power systems

Conventional powersystems

Distribution generationpower systems

Survey on LFCThe controller parameters plays a vital role for its performance,thus it should be tuned properly with suitable optimization

centuries from the generation and transmission level to thedistribution was mainly dominated by hydro, thermal and nuclear1. Introduction

Loadfrequency control (LFC) is of importance in electric powersystem design and operation. The objective of the LFC in aninterconnected power system is to maintain the frequency of eacharea within limits and to keep tie-line power ows within somepre-specied tolerances by adjusting the MW outputs of thegenerators so as to accommodate uctuating load demands. Awell designed and operated power system must cope withchanges in the load and with system disturbances, and it shouldprovide acceptable high level of power quality while maintainingboth voltage and frequency within tolerance limits.

Subjected to any disturbance, the nominal operating point of apower system changes from its pre-specied value. As a result thedeviation occurs about the operating point such as nominalsystem frequency, scheduled power exchange to the other areaswhich is undesirable.

The LFC issues have been tackled with by the various research-ers in different time through AGC regulator, excitation controllerdesign and control performance with respect to parameter varia-tion/uncertainties and different load characteristics. As the con-guration of the modern power system is complex, the oscillationincurred subjected to any disturbance may spread to wide areasleading to system black out. In this context, advance controlmethodology such as optimal control, variable structure control,adaptive control, self-tuning control, robust and intelligent controlwere applied in LFC problem.

The further research in this area has been carried out by use ofvarious soft computing techniques such as articial neural net-work (ANN), fuzzy logic and fusion of these such as neuro-fuzzy,neuro-genetic etc. to tackle the difculties in the design due tonon-linearity in various segregated components of the controller.Fig. 1. Illustration oflinearity in the power system components and also the uncer-tainty in the system parameters, the performance differs fromactual models, so robust control design is indispensible to achieveacceptable deviation in frequency about the nominal operatingpoint. Various robust control techniques such as Riccati equation,H, m-synthesis, robust pole assignment, loop shaping, linearmatrix inequality (LMI) has been adopted to tackle the LFCproblems.

Now, there is rapid momentum in the progress of the researchto tackle the LFC in the deregulated environment, LFC withcommunication delay, and LFC with new energy systems, FACTSdevices, and HVDC links as well.

This survey paper comprehensively highlights the LFC pro-blems in conventional and distribution generation based powersystem. A comprehensive review on conventional power system assingle area, multi-area with interconnection, the power systemwith HVDC links and control problem in the deregulation envir-onment is presented. Further LFC issues in renewable energysystems and its integration with the grid is also discussed. Inaddition to this, the recent trends in LFC such as communicationdelays, wide area monitoring, phase measurement unit andpenetration of different renewable energy sources impact on theLFC is also discussed. The layout for survey carried out on LFC isshown in Fig. 1.

2. Type of power system modelstechniques. In this context, the application of genetic algorithm(GA), particle swarm optimization (PSO), simulated annealing (SA)survey on LFC.

regulator of a two-area reheat-type thermal system with GRC is

S.K. Pandey et al. / Renewable and Sustainable Energy Reviews 25 (2013) 318334320power generation which is integral component of the conventionalpower system. But in the twenty rst century due to depletion offossil fuel and threats to the environment pollution, the non-conventional energy sources plays a vital role, in form of distribu-tion generation (DG) based power system. Thus the LFC problemwhich is an important issue has to be the addressed in theconventional as well as DG.

2.1. Conventional power systems

Any power system that has the fundamental control problem ofmatching real power generation to load including losses is calledloadfrequency control. Most of the works reported so far has beencarried out by considering various linearized model of thermal/hydro of single area or multi-area power systems. The frequency isdependent upon the active power which comes from the loadgeneration mismatch. Thus primary control loop comprises ofspeed governing load followed by the secondary control withdroop control mechanism. Thus at the control centre, supplemen-tary control is also provided at the secondary control level. Theprimary control comprises of governor and turbine which consti-tutes the mechanical system with sluggish response. The second-ary control plays a vital role which comprises of droop controlmechanism, integral square error etc. in addition to that thesupplementary control and auxiliary control such as power systemstabilizer (PSS).

Decades back, the power system structure remained simpleand limited. The primary source of generation to meet the demandin the region was from hydro, thermal or both. However, increaseof electricity demand had lead to restructure it. Thus the incor-poration of exible transmission system and other auxiliarydevices came into existence. Again in the market driving powersystem, the independent player came into the role with theconcept of deregulation. Thus in this context the LFC problem inthe conventional power system is a challenging task, which hasbeen the focus of several researchers since early eighties of lastcentury.

Our survey paper is comprises of different sections. Sections2.1.1 to 2.1.7 discusses the several structure of the conventionalpower system such as single area and multi-area, the structurewith HVDC link. And the deregulation environment is discussedseparately for easier understanding in the LFC issues.

2.1.1. Single area thermal power systemsThe LFC problem for single area thermal power systems is

presented in [16]. The LFC of single-area thermal power systemincluding generation rate constraint (GRC) is presented in [2,4].The LFC scheme of one-area thermal systemwith single time delayis presented in [5]. The LFC with multi-source (thermalhydrogas) as single area is proposed in [6].

2.1.2. Single area hydro power systemsThe LFC problem for single area hydro power system is

presented in [79]. The transient speed response of a single,isolated, governed hydro-generator operating at, or near, full loadis discussed in [7]. The automatic generation control of hydro-plant is presented in [8]. The LFC of an isolated small-hydro powersystem with reduced dump load is described in [9].

2.1.3. Two area power systemsThe LFC problem for two area power systems is presented in

[1047]. Due to non-linearities in the connected load and governordead bands, the actual system response characteristic is non-linear. Therefore, a linear tie-line bias characteristic does not

match the actual system response characteristic. This mismatchpresented in [23]. The effect of reheat and governor dead-bandnonlinearity on LFC is considered in [24]. In [25], a combination ofthermal-hydro power system is considered. The application ofmagnetic energy storage unit as loadfrequency stabilizer in two-area thermal power system is presented in [29]. It has been shownthat small sized superconducting magnetic energy storage (SMES)units with suitable control can effectively reduce the frequencyand tie-line power oscillations following sudden small loadperturbations. The effect of SMES and batteries in two-areathermal power system considering dead-band and GRC is pre-sented in [32] and [33], respectively. The proposed adaptivecontrol scheme is very effective in damping out oscillations causedby load disturbances and its performance is quite insensitive tocontroller gain parameter changes of SMES [33]. The inuence ofSMES coordinated with solid-state phase shifter on LFC is dis-cussed in [35]. Again in [38], the discrete-mode automatic gen-eration control (AGC) of a two-area reheat thermal system withnew area control error (ACE) is considered. The LFC of two-areareheat thermal power system with dead zone and GRC incorpo-rated with SMES in both areas are proposed in [39]. Theinterconnected two-area reheat thermal power system withGRC and boiler dynamics including SMES units for LFC is con-sidered in [40].

The LFC of two-area hydrohydro power system with propor-tionalintegralderivative (PID) controller based on maximumpeak resonance specication that is graphically supported by theNichols chart is discussed in [41]. The automatic generation ofthree types of interconnected two-area multi-unit all-hydro powersystem, all-thermal and thermal-hydro mixed have been investi-gated in [42]. The reheat thermal power system with governordead zone is discussed in [43], while reheat thermal power systemwith GRC is presented in [44]. The LFC of two-area thermalthermal power system with time delay is considered in [45]. Thetwo-area interconnected thermal reheat power system with inter-line power ow controller (IPFC) and redox ow batteries (RFB)units for LFC is proposed in [46]. The two-area power systemconsisting of identical reheat turbines interconnected via AC linkand AC/DC links are presented for LFC in [47].

2.1.4. Three area power systemsThe LFC challenges in three area power systems are presented in

[4862]. The three area interconnected [48] consists one steam plusone hydro unit, which forms area 1, while one steam plus one hydrounit of area 2 and area 3 with one steam. The thermal power systeminterconnected as three areas is presented in [49,51,54,55]. The threeinterconnected areas that consists two thermal and one hydro unit ineach area is considered in [50]. Three thermal generating units ineach area of three-area interconnected power system are consideredin [52,56]. Two different interconnections (a) radial type and (b) ringtype with thermal unit in three area power systems have beenconsidered in [53]. The LFC problem for three-area thermal powercauses unnecessary fuel consumption and increased wear and tearon generators. Doraiswami [17] presented LFC for a two-areainterconnected system taking into account the nonlinearity andstochastic nature of the load and using an optimal linear strategyaided by stability analysis. Nanda and Kaul [15] investigated thestability and optimum settings of conventional automatic genera-tion controllers for an interconnected power system having reheatsteam plants. Oni et al. [22] investigated the nonlinear tie line biascontrol in interconnected power systems. This study was per-formed by utilizing the UMC hybrid simulator to simulate a typicalpower system including governor dead band, frequency, andvoltage sensitivity of loads. The discrete-type loadfrequencysystem with communication delays is discussed in [57]. In order to

S.K. Pandey et al. / Renewable and Sustainable Energy Reviews 25 (2013) 318334 321consider AGC, the area-1is modeled by two generators while theother two areas have single generator equivalents of four and threegenerators in area-2 and area-3, respectively. The LFC for three areapower system with time delays has been also discussed in [58,59].The load frequency controller for a three area thermal power systemis proposed in [60,61]. The LFC for three-area power system withdifferent turbine units, such as non-reheat, reheat and hydraulic isconsidered in [62].

2.1.5. Four area power systemsThe LFC problem for four area power systems is presented in

[6371]. Two types of interconnected longitudinal 4-area systemsare considered in [63]. In the rst model, all the areas consist ofnon-reheated system plant while in second type of model, eacharea has the different types of plants, i.e. steam with GRC andhydro plants without GRC. The different kinds of generating units(non-reheat, reheat and hydro-turbine type), linked together in aninterconnection and also considering GRC and governor dead-band non-linearities is presented in [64]. Studies on a 4-areapower system including GRC and governor dead-band is presentedin [65]. The combination of ring and longitudinal manner con-nected thermal units as four areas is considered in [66], whilethree thermal and one hydro unit is proposed in [67,68]. The LFCproblem for four-area power system with different turbine units,such as non-reheat in area 1 and area 2 while hydro unit in area3 and area 4 has been considered in [69]. The reheat thermal unitsfor area 1, 2 and 3 while hydro unit in area 4 for LFC has beenconsidered in [70]. The four identical thermal units for four areainterconnected power systems for LFC problem is considered in[71].

2.1.6. Power system with HVDC-linkThe HVDC transmission has emerged as an alternate link in the

power system scenario, due to its numerous technicaland economical advantages, for the need of power transfer overlarge distances [7276]. The two and three plants with AC and DCtie-lines between plants are considered in [72]. A 3-leveloptimal controller for LFC in the power system which is composedof several subsystems interconnected by asynchronoustie-lines is presented in [74]. The two area power systems inter-connected via parallel AC/DC transmission links are considered in[75,76].

2.1.7. Deregulated power systemsIn the electricity market driven, power system deregulation

plays a vital role. The deregulated power system consists ofGENCOs, TRANSCOs, and DISCOs with an open assess policy. Inthe newly emerged structure, the GENCOs may or may notparticipate in the LFC task. As a matter fact, independent systemoperator leads to make the LFC scheme more reliable. The powersystem models based on deregulated scenarios has been proposedin [7787]. Most of the study considers the control problem issueassociated with thermal power plants. The LFC study in deregu-lated structure of three-area power system is presented in[83,84,88]. The AGC in deregulated environment for four areainterconnected power system is given in [89,90].

2.2. Distributed generation power systems

As discussed in the previous section, the DG system is consideredeconomical for electrical power supply to remote and isolated areaswhere the electric power is not easily available from the grid. Thepower system model for LFC has been also proposed incorporatingwind turbine generator (WTG), photovoltaic (PV), and FACTS devices.

Jovanovic et al. [91] investigated a knowledge-based feedbackcontroller designed to enhance the quality of control of generatorspeed and power system frequency. In [92], an identication proce-dure for hydro-generator plant using an adaptive technique ispresented. The LFC problem in DG systems is presented in [93100]. The frequency support from doubly fed induction generatordriven by wind turbine is presented in [101111]. The frequencycontrol for HVDC link connected wind farms are presented in [112116]. The frequency control of standalone wind energy conversionsystem (WECS) using permanent magnet synchronous generator ispresented in [117]. Next wind-hydro hybrid system using inductiongenerators and battery storage is proposed in [118,97]. The inter-connection of energy resources like PV, fuel cell and wind system areimportant due to intermittent environmental characteristics [119121,98] to supply reliable power. A control scheme without usingcommunication signals to improve the transient response of parallel-connected inverters is suggested in [119]. The dynamic and transientanalysis of power distribution systems using fuel cell is presented in[122,123]. To enhance the performance of a grid-connected PV-fuelcell (FC) hybrid system is presented in [124]. The power uctuationcompensation in hybrid power generation system that consists ofoffshore-wind turbine and tidal turbine is proposed in [125]. The LFCin winddiesel hybrid system is discussed in [126,127,100]. Akie et al.[128] presented a frequency control problem in isolated powersystem by considering wind farm and battery through load estima-tion. Senjyu et al. [121] proposed a new stand-alone hybrid powersystem consisting of WTGs, diesel engine generators (DEGs), FC, andaqua electrolyzers (AE). The effect of these systems on the LFC isconsidered and these ensure supply of high-quality power. The effecton grid frequency control by electric water heaters as controllableloads is presented in [129].

An assessment of the impact of wind generation on systemfrequency control is discussed in [130]. The PV-diesel hybridpower system is proposed in [131133], while winddiesel forLFC in a small power system is presented in [134]. The time-domain simulation for small-signal analysis of a hybrid powergeneration/energy storage system is presented in [135]. Thesystem consists of three WTGs, DEG, FC and PV, along with batteryand ywheel as energy storage units. In [136], autonomous hybridgeneration systems consisting of WTGs, solar thermal powersystem (STPS), PV, DEGs, FCs, battery, ywheel, ultracapacitors(UCs) and AE have been considered. The LFC by consideringcontrol of FC and double-layer capacitor in an autonomous hybridrenewable energy power generation is presented in [137]. The LFCof wind energy with storage system is proposed in [138]. Theimpact of doubly fed induction generator (DIFG) type windturbines (WTs) on LFC in multi-area interconnected thermalpower system is proposed in [139], while on single thermal unitis given in [131]. The authors [140] propose the integration ofsteady-state models of several types of wind generators into apower ow algorithm with automatic LFC. The DFIG based windfarm for LFC in two-area interconnected power system consistingof multi-unit reheat type thermal and hydropower system withcoordinated control of TCPS and SMES is proposed in [141], whilein [142], identical thermal interconnected two-area power systemis considered.

The supplementary LFC method by use of a number of bothelectric vehicle (EV) and heat pump water heater as controllableloads is proposed in [143], for the power system model with largeintegration of wind and PV generation. A two-bus power systemconsisting of varying load, a diesel-synchronous generator andWTG topologies with either a DFIG or a permanent magnetsynchronous generator (PMSG) are considered in [144]. Thewind-hydro autonomous microgrid for LFC is proposed in [145].The authors [146] proposed a method for tracking a secondary LFCsignal with groups of plug-in hybrid electric vehicles (PHEVs),

controllable thermal household appliances under a duty-cycle

quency control based on optimal linear regulator theory. In [163],

S.K. Pandey et al. / Renewable and Sustainable Energy Reviews 25 (2013) 318334322the author has investigated the effect of plant response time onthe closed loops poles, designed using linear optimal controltheory. In [12], a more realistic model of the LFC system isdeveloped and studied, by including the voltage-regulator excita-tion system and optimal responses are computed under variousload conditions. Kwatny et al. [164] presented a review of recentefforts in applying optimal linear regulator theory with intent toclarify the objectives of LFC, particularly as regard to the applica-tion of modern control theory. In [25], Hsu and Chan presented asystematic approach to design an optimal variable-structure con-troller (VSC) for the LFC in the interconnected power system.

The feasibility of an optimal AGC scheme requires the avail-ability of all state variables for feedback. However, these effortsseem unrealistic, since it is difcult to achieve this. Then, thecoordination scheme, and a decentralized combined-heat-and-power generation unit.

The above paragraphs suggests a wide spread application of DGsystems for the LFC issues. However, the increased penetrationlevel of DG also affects the LFC problem tremendously. The impactof penetration of WTGs on LFC for three-area interconnectedpower system is discussed in [147]. The AGC structure for smartpower grids is presented in [148], which consists of the constantpressure steam, hydro and variable pressure steam units. Theauthors [149], proposed an autonomous distributed vehicle-to-grid (V2G) control schemes, while in [150] aggregated electricvehicle (EV)-based battery storage representing a V2G system ismodeled for the use in long-term dynamic power system.

3. Control techniques for conventional power systems

3.1. Classical control approaches

Conventionally, for issues related to automatic generationcontrol (AGC), the frequency deviation is minimized by theywheel type of governor of synchronous machine. However, thesignicant control is not achieved for the LFC objective. In thiscontext, the supplementary control is introduced to the governorvia signal directly proportional to the frequency deviation plus itsintegral action. The initial stage of research work carried out byCohn et al. is reported in [151155]. Quazza [156] proposed theapproach with non-interaction between frequency and tie-linepower control and each control area responsible for its own loadvariations. Aggarwal and Bergseth [157] investigated study onlarge signal dynamics of systems. The technique based on coordi-nated system-wide correction of time error and inadvertentinterchange is incorporated for AGC study by Cohn [158]. Anumber of classical control techniques namely, Nyquist, Bodereveal that closed loop transient response will result into relativelylarge overshoots and transient frequency deviation [159161].

3.2. Optimal control approaches

The LFC regulator design techniques using modern optimalcontrol theory enable the power engineers to design an optimalcontrol system with respect to given performance criterion. Theoptimal control theory has made a new direction to solve the largemultivariable control problems in a simplied form. The controlscheme considers the state variable representation of the modeland an objective function to be minimized. Fosha and Elgerd [162],used a state variable model and regulator problem of optimalcontrol theory to develop new feedback control law for two-areainterconnected non-reheat type thermal power system. MilonCalovic [48] presented linear regulator design for the load fre-problem is to reconstruct the unavailable states from the availableoutputs and controls by an observer design. Considering statereconstruction, many signicant contributions have been made[165170]. Bohn and Miniesy [165] have studied the optimum LFCof a two-area interconnected power system by making the use of(i) differential approximation and (ii) a Luenberger observer andby introducing an adaptive observer for identication of unmea-sured states and unknown deterministic demands, respectively.Exploiting the fact that the nonlinearity of the power systemmodel, namely, the tie-line power ow, is measurable, the obser-ver has been designed to give zero asymptotic error, even for thenonlinear model. AGC schemes based on an optimal observer,which is a state estimator with decaying error at a desired speed,using a nonlinear transformation [166] and reduced-order modelswith a local observer [167] have been discussed. In [17], anobserver for nonlinear system is presented. A simplied generat-ing unit model oriented towards LFC and the method for itstransfer function identication based on a two-stage procedureindirectly reducing both noise effects and transfer function order ispresented in [170].

3.3. Sub-optimal control approaches

The computational complexity of a multi-area system leads tosolve the optimal control problem in a modied form. Therefore,suboptimal control strategy is explored for the LFC problem.In order to remove the practical limitations in the implementationof regulators based on full order state feedback, suboptimalAGC regulator designs were considered [171173]. Moorthi andAggarwal [171] presented suboptimal and near-optimal controlusing modern control theory. The AGC schemes based on anoptimal observer, which is a state estimator with decaying errorat a desired speed, using a nonlinear transformation [174] andreduced-order models with a local observer [175] is discussed.Hain et al. [176] reported a simplied generating unit modeloriented towards LFC and the method for its transfer functionidentication based on a two-stage procedure indirectly reducingboth noise effects and transfer function order. The sub-optimalAGC regulator design of a two-area interconnected reheat thermalpower system using output vector feedback control strategy ispresented in [47]. The design method employing modal andsingular perturbation techniques to affect decoupling of theinterconnection into its subsystem components is considered in[177]. In the method, after achieving the decoupling, local con-trollers for each subsystem are designed individually to place theclosed-loop poles of each subsystem in some pre-specied loca-tions in the complex plane, and then, the resulting controllers areused to generate local control inputs, using local information only.The AGC regulator design using Lyapunov's second method andutilizing minimum settling time theory is proposed in [178]. Theimportance of the dominant time constant of the closed-loopsystems in designing the regulators has been emphasized. Theauthor has reported a bangbang AGC policy based on thismethod.

3.4. Adaptive and self-tuning approaches

As the operating point of the system gets changed, thecontroller performance in the system may not be optimal. As amatter of fact to keep the system performance near the optimalvalue, it is desirable to track the operating point of the system andaccordingly update its parameter to achieve a better controlscheme. The self-tuning control (STC) approach also includes anintegral part of the adaptive control scheme. The self-tuningregulator strategy implemented for adaptive LFC seems a viablesolution. A number of research works has been reported on

adaptive [179184] and STC [185189] schemes for LFC in the

4.2. Decentralized control approaches

S.K. Pandey et al. / Renewable and Sustainable Energy Reviews 25 (2013) 318334 323Contrary to the centralized control for a large scale powersystem, decentralized control is preferable, because it reduces thecomputational burden with pass of the communication betweendifferent systems and make the control more feasible and simple.Many research papers using this approach for continuous anddiscrete time system models are published [192199]. In order toovercome the problem arising out of the centralized control, thedecentralized control approach has been addressed. The basicobjective of later technique is to make the composite systemdivided into subsystem, each of which control separately. Thedesign of decentralized LFC is presented in [14,16,26,30,50,51,63,66,83,200203]. In [204], the design of decentralized loadfrequency regulators presented for two-area thermal power sys-tems, starting with stochastic state and output models, is pre-sented by making use of modelingerror-compensation techniquealong with bias-estimation procedure. Shirai [16], reported thedecentralized LFC for two-area thermal power system through agovernor and voltage controls by a new approach based on Siljak'stheory. Edward et al. [50] presented the decentralized loadfrequency control of a three area power system consisting of ninesynchronous machines described by a 119th order model. Hiyama[63], proposed a design of decentralized regulator for an inter-connected longitudinal 4-area system. Similarly, the analysis andsolution of the LFC problem wherein the feedback control lawpower system. Ross [179] described control criteria in LFC and therelated practical difculties encountered to achieve this criterion.Pan and Liaw [182] presented an adaptive controller for LFC usinga PI adaptation to satisfy the hyper-stability condition to take careof the system parameter changes. The effectiveness of proposedcontroller for considering the generation rate limit was alsoconrmed. In [31], a new method to design a multivariable self-tuning regulator with the inclusion of interaction of voltage onload demand is presented. Similarly in [32], self-tuning type ofadaptive controllers for main AGC loop and SMES, which isincorporated as a stabilizer to improve AGC performance isdiscussed. A multi-area adaptive LFC developed for a comprehen-sive AGC simulator is presented in [183] and a reduced-orderadaptive LFC for interconnected hydrothermal power system issuggested in [184]. Wang et al. [4], proposed a combination ofrobust control, the Riccati equation and adaptive control to designa new robust adaptive load-frequency controller for power sys-tems with parameter uncertainties. A multilevel adaptive algo-rithm based on a relatively fast implicit self-tuning regulator formulti-area power systems is investigated in [190]. Jovanovic et al.[91] presented an application of knowledge-based adaptive tur-bine governor control. In [191], a self-tuning steam turbine controlscheme designed to improve the quality of control of powersystem frequency is discussed.

4. Control strategies for conventional power systems

4.1. Centralized control approaches

The implementation of global controller requires informationabout all the states of the power system. In the beginning, the LFCproblemwas based on centralized control strategy [156,159,162,173].On the basis of classes of disturbances the control strategy has beenproposed in [156]. Elgerd and Fosha [159] suggested a feedback andloop gain to eliminate the disturbance, and new feedback control lawis developed by using a state variable model and the state regulatorproblem of optimal control theory [162].constrained to two different structures; decentralized and/oroutput feedback algorithm used to solve a non-classical linearquadratic problem based on property of the associated Riccatiequation is presented in [200].

Feliachi [26] presented a novel methodology for the design ofoptimal decentralized LFC for multi-area interconnected powersystems. Aldeen and Marsh [30] reported a simple and computa-tionally efcient decentralized control design based on reduced-order observer and a proportional-plus-integral controller in eacharea of two-area interconnected power system. This ensured zerostatic change in area-frequency and tie-line power.

A local loadfrequency controller uses only its area's statemeasurements. It does not use any feedback from other areas.The overall N-area power-system stability becomes a concern tocontrol engineers when all the local loadfrequency controllerswork together. In addition, system parametric uncertainties existin the real power plant. The controllers which are designed basedon a xed plant model may not work when some systemparameters have varied. A robust decentralized control approachis used in [51], based on the Riccati-equation for multi-area powersystems with parametric uncertainties.

Several authors applied the concept of variable-structure systemsto design the load-frequency controllers. Yang et al. [66] proposeddecentralized load-frequency controller based on structured singularvalues. The LFC problem for deregulation environment based onH2/H [83] and LMI [85] technique is presented in multi-area (3-area)interconnected power system. Taher and Hematti [201] have discusseduse of multivariable QFT method in deregulated environment for2-area power system with a wide range of parametric uncertainties.The design of multi-objective evolutionary algorithm (MOEA) baseddecentralized load frequency controllers with ACDC parallel tie-linefor (two-area) interconnected power systems is presented in [202].Additionally, GA-based decentralized controller in two-area powersystems with redox ow battery considering TCPS reported in [203].The design of loadfrequency controller based on singular structurevariable is presented in [205]. The authors [206] adopted two-degree-of-freedom (TDF) internal model control (IMC) method to tunedecentralized PID-type controller for LFC in four area power systemswith deregulated environments. The TDF-IMC-PID method has beenstudied in [207,68] for LFC in conventional situation and the perfor-mance of the control system is only related to two tuning parameters.The design of decentralized load frequency controller for three-areainterconnected power systems is described in [60]. In the design ofproposed controller, each local area network is overlapped with statesrepresenting the interconnections with the other local area networksin the global system. Then, a decentralized control scheme is devel-oped as function of local area state variables and those resulting fromthe overlapped states which represent an approximation of theinterconnection variables.

4.3. Two-level and multi-level control strategies

In decentralized control, the feedback gains associated withsome states of the neighboring area is not taken into considerationin order to reduce the cost of communication. The strong interac-tion between the areas makes the overall system unstable. Toovercome these limitations, two-level or multi-level controlscheme is addressed. Premakumaran et al. [20], proposed aperturbation approach to develop a two-level control strategy tooptimize the performance of a two-area LFC system. Next, Bengia-min et al. [49] proposed a design by use of modern optimal controland multilevel system techniques. A 3-level optimal controller forpower systems interconnected by asynchronous tie-lines is dis-cussed in [74]. Premakumaran et al. [208], proposed some aspectsof multilevel LFC of a two-area power system. Further, the studyincorporates the effects of governor controls and an excitation

system. Miniesy and Bohn [209], suggested a two-level suboptimal

band effect and reheat effect in two area interconnected power

S.K. Pandey et al. / Renewable and Sustainable Energy Reviews 25 (2013) 318334324system. Ahamed et al. [216] have viewed AGC problem as astochastic multistage decision-making problem or a Markov Chaincontrol problem and have presented algorithm for design of AGCbased on a reinforcement learning approach. Talaq et al. [217]proposed an adaptive controller which requires less trainingpatters as compared with a neural network based adaptive schemeand performance is observed better than xed gain controller.

5.2. Fuzzy logic

Fuzzy logic has been widely used in the control related problemsin power system. Contrary to the traditional control which is mostlybased on linearized mathematical model, the fuzzy logic controlapproach solves the problem based on experience and knowledgeabout the system. Indulkar et al. [218] initially designed a controllerusing fuzzy logic for AGC and responses were compared withcontroller. However, this approach does not ensure zero steadystate error, and hence, a multilevel nite time optimal controllerdesign that ensure zero steady-state error has been reported in[210]. Rubaai et al. [190] proposed a multilevel adaptive LFC basedon the self-tuning regulator (STR). A global controller, capable toexploit the possible benecial aspects of interconnections, has beenapplied in the LFC study [211], and favorable results are reported. In[180,181] control strategy based on singular perturbation approachis presented. In the study, the system is decomposed into slow andfast subsystems and controllers are designed for each subsystem,with these two combined to yield a composite controller. Ahierarchical optimal robust LFC for reheat thermal units in area-one, two and three, with hydro unit in area-four is presented in[70]. In this study, the multi-area power system is decomposed intoseveral sub-systems or areas and then two-level control strategy isused to obtain the overall optimal solution.

5. Soft computing techniques in LFC

With increased size and changes in structure of the power systemdue to integration of renewable energy sources, the traditional LFCmay not be feasible. In the robust control scheme, the structuralcomplexity and reshaping of the plant may be required. To circum-vent this problem, the intelligent control scheme with use of softcomputing techniques such as articial neural network (ANN), fuzzylogic, genetic algorithm (GA), particle swarm optimization (PSO)algorithms, etc. has been explored. In this context to address thenon-linearities, system uncertainties, the intelligent LFC scheme maybe the suitable alternative, than the traditional controls. Over theyears, number of soft computing techniques has been applied in LFCproblem for better control objective.

5.1. Articial neural network (ANN)

The ANN is a black box which correlates the non-linearrelationship between output and input without information ofsystem structure. The ANN has been applied to achieve bettercontrol strategies especially in a non-linear complex powersystem. Beaufays et al. [212] discussed the application of layeredneural networks in nonlinear power systems, while Birch et al.[213] investigated the use of neural networks to act as the controlintelligence in conjunction with a standard adaptive LFC scheme.Chaturvedi et al. [214] have developed an automatic load fre-quency controller using ANN to regulate the power output andsystem frequency by controlling the speed of the generatorthrough water or steam ow control. Demiroren et al. [215]designed the controller, taking into account the governor dead-classical integral controller. The LFC problem using fuzzy gainscheduling of PI controllers in a four area interconnected powersystem with dead-bands and GRC is addressed in [219]. Denna et al.[220] have proposed used of tabu search algorithm for the automaticdenition of the fuzzy rules. Ghoshal [221] presented a self-adjusting,fast acting fuzzy gain scheduling scheme for conventional integralgain AGCs in a radial and ring connected three equal power systemareas. The study on two area interconnected thermal power systemwith fuzzy controller is presented in [222,223]. Chia and Chun [224]proposed a GA based fuzzy gain scheduling for two-area thermalpower systemwith consideration of governor dead-band and GRC. In[54], the optimal integral and PID gains have been determined by GA.An on-line fuzzy logic controller realization with GA in a 4-areapower system including GRC and saturation as nonlinearities for AGCis presented in [67]. Juang and Lu [55] proposed fuzzy-PI controller todecide adaptively the proper proportional and integral gains accord-ing to the ACE and their changes. Saravuth et al. [225] focused theirstudy on multiple tabu search algorithm for fuzzy based PI loadfrequency controller. A multi-stage fuzzy PID controller in a restruc-tured power system is described in [84]. Sinha et al. [226] proposedGA and PSO tuned fuzzy controller for AGC in three area powersystem. The fuzzy logic controlled SMES as frequency stabilizer forinterconnected two-area thermal power system is proposed in [39].The generation of optimal fuzzy rule based on fuzzy C-meansclustering for decentralized LFC in two-area reheat thermal powersystem with GRC is proposed in [44]. The Type-2 fuzzy approach isproposed for LFC of two-area interconnected power system includingSMES and considering GRC and boiler dynamics in [40].

Nowadays the complexity issues in power system are beingsolved with the use of GAs, PSOs, bacterial foraging optimizationalgorithm (BFA). These are some of the heuristic techniques havingimmense capability of determining global optimum being dis-cussed in subsequent subsections.

5.3. Genetic algorithms (GAs)

The GA is a global search optimization technique based onoperation of natural genetics and Darwinian survival-of-the-ttestwith a randomly structured information exchange. The GAs havebeen widely applied to solve complex nonlinear optimizationproblems in a number of engineering elds in general and in thearea of AGC of power systems in particular [52,92,227233]. Theuse of basic genetic algorithm on a digital computer to identify ahydro-generator plant is discussed in [92]. Dangprasert et al. [234]proposed GA based intelligent controller for LFC problem. The GAbased fuzzy gain scheduling approach for power system LFC isdiscussed in [224,235]. Magid and Dawoud [228] proposed theirstudy on optimal adjustment of the classical AGC parameters usingGA. The use of controllers to regulate the power output and systemfrequency by controlling the speed of the generator with the helpof fuel rack position control is presented in [227]. The authors in[236] proposed GA for parameter optimization of PID sliding modeLFC for AGC in multi-area power systems with nonlinear element.Rerkpreedapong et al. [52] obtained a higher order robust dynamicperformance with LFC design based on GA and LMIs. Next, Ghoshal[233] proposed GA/GA-SA-based fuzzy AGC scheme in a multi-areathermal plant. The hybrid GA-SA technique yields more optimalgain values than GA. Du and Li [67] proposed on-line fuzzy logiccontroller realization by GA in AGC problem. In [55], the LFC byfuzzy-PI controller is proposed. The optimization of control para-meters for robust decentralized frequency stabilizer by usingmicro GA is presented in [237]. A new design of multi-objectiveevolutionary algorithm based decentralized loadfrequency con-trollers for interconnected power system with AC-DC parallel tie-lines is proposed in [202]. Comparison of articial intelligencemethods for LFC study is discussed in detailed in [238]. In [56], the

authors have discussed the design of load frequency controller in

which correspond to individuals in the GA. The PSO is a population

S.K. Pandey et al. / Renewable and Sustainable Energy Reviews 25 (2013) 318334 325based stochastic optimization technique, inspired by social beha-vior of bird ocking or sh schooling. To ease the design effort andthereby improve the performance of the controller, the design offuzzy PI controller by hybridizing GA and PSO is presented in [55].With the use of control scheme based on adaptive neuro-fuzzyinference and PSO with gains being updated in real time, a betterdynamic and steady state response is obtained in [86]. Similarlythe design of multi-objective PID controller for LFC based onadaptive weighted particle swarm optimization in two-area powersystem is described in [239,240]. Since PSO is less susceptible tolocal optima unlike GA, SA, the heuristic evolutionary searchtechnique based hybrid particle swarm optimization has beenadopted for determination of optimal PID gains for LFC in four-areapower systems having deregulation environments [89].

5.5. Tabu search algorithms (TSA) and bacterial foragingoptimization algorithm (BFOA)

The TSA is an iterative search that starts from some initialfeasible solution and attempts to determine a better solution inthe manner of a hill-climbing algorithm. The TSA has a exiblememory which maintains the information about the past step ofsearch and uses it to create and exploit the better solutions.Maurizio et al. [220] presented an approach for the automaticdenition of fuzzy rules in fuzzy controller based on TSA and theauthors describe improvement in learning of fuzzy rule by usingheuristic symbolic meta rules. Saravuth et al. [225] presented anew optimization technique of a fuzzy logic based PI-LFC by themultiple tabu search algorithm.

Another known optimization techniques; the BFOA is moti-vated by the natural selection which tends to eliminate theanimals with poor foraging strategies and favor those havingsuccessful foraging strategy. The foraging strategy is governed byfour processes namely chemotaxis, swarming, reproduction, elim-ination and dispersal. The fractional-order-PID controller tuned bybacterial foraging technique is used for LFC in three-area powersystems with deregulated environment in [88], including otherparameters such as order of integrator and differentiator of PIDcontroller also tuned by BF approach. The investigation on effect ofredox ow batteries that coordinate with intertie power owcontroller for LFC in two-area interconnected system is presentedin [46], having gain of integral controller tuned by BFA.

6. Other controllers for LFC

6.1. Variable structure controller

The variable structure controllers change the system structurein accordance to some law of structure change, in order to improvethe dynamic performance and thereby make the controller insen-sitive to the plant parameter changes. Hsu and Chan [25] proposedthe LFC problem for interconnected two-area hydro-thermalpower systems using the theory of variable-structure systemsmulti-area power system by use of multi-agent reinforcementlearning approach. The LFC problem for four-area power systemwith discrete-sliding mode control using GA for proper tuning ofthe gains is discussed in [69]. The multi-objective optimizationbased GA used to optimize the gains of PI/PID-controllers for LFCof three-area thermal power systems is presented in [61].

5.4. Particle swarm optimization (PSO) algorithms

The PSO conducts searches using a population of particlesand linear optimal control theory. A discreet version of a variable6.2. Robust controller

The conventional LFC is mostly simple classical tuned controller,having parameter adjustments heuristically. Thus, it is incapable ofproviding good dynamical performance over a wide range ofoperating conditions and various load scenarios. Thus, novel model-ing approach is strongly required to obtain a new trade off between amarket outcome and market dynamic (robustness). The robustcontroller based on Riccati-equation approach is presented in[3,12,51,200,241,242]. Goshaidas et al. [242] have presented a robustcontroller based on the Riccati-equation in single area thermal powersystem. Lim et al. [51] proposed a decentralized load frequencycontroller based on the Riccati-equation approach in three areapower systems with parametric uncertainties. Robust controller forLFC in a deregulated two area thermal power systems by using am-synthesis approach is given in [243]. Similarly the controller basedon H control design using LMI technique in order to obtainrobustness against uncertainties is presented in [52]. A decentralizedH damping control design based on the mixed-sensitivity formula-tion in the LMI framework is reported in [244].

A new decentralized robust control strategy based on the mixedH2/H control technique for LFC problem in a deregulated three areapower systems is proposed in [83,85]. Ngamroo et al. [237] proposedrobust decentralized frequency stabilizer design of static synchronousseries compensators by taking system uncertainties into considerationfor three area interconnected power system. The design of robust PIcontroller for LFC in three area interconnected power system based onH static output feedback control technique is solved by using adeveloped iterative LMI is addressed in [245]. Robust analysis anddesign of load frequency controller is described in [246].

The LMI approach based LFC including communication delays isproposed in [57], while a robust decentralized PI controller designbased on the mixed H2/H control technique using LMI approachfor three-area interconnected power systems with communicationdelays is proposed in [58]. The robust decentralized LFC for four-area interconnected power systems is proposed in [71], in which adetailed structured singular value method is proposed for local-area robustness analysis, and an eigenvalue method is derived fortie-line robustness analysis. The design of decentralized robustcontroller based on the concept of active disturbance rejectioncontrol is proposed in [62]. The authors [5] investigate the delay-dependent stability of the LFC scheme by using Lyaponuv-theorybased delay-dependent criterion and LMI techniques for one-areaand multi-area LFC schemes installed with PI-controllers. Thedelay-dependent/independent design of H controller for LFC oftwo-area interconnected power system is presented in [45].

7. Use of SMES, BESS and facts devices in conventional powersystems

7.1. SMES and BESS

In order to reduce the system frequency deviation to a mini-mum value, the storage system such as SMES or battery energystorage system (BESS) can be incorporated. The use of BESS tostructure controller for two area thermal and multi-area inter-connected power system with consideration of nonlinearities,such as GRC and governor dead band is presented in [64]. Maliket al. [65] presented a study based on the concepts of discontin-uous control, dual-mode control and variable structure systems forfour-area interconnected power systems including nonlinearities.Similarly, Yang et al. [66] proposed a decentralized controllerbased on the structured singular values.improve the LFC dynamics of West Berlin Electric Supply System

power conditioning system with the SEMS. An improved system

S.K. Pandey et al. / Renewable and Sustainable Energy Reviews 25 (2013) 318334326transient response with SMES has been achieved. Some moreapplications of SMES for improving the LFC are also mentioned in[253257].

7.2. Flexible AC transmission systems (FACTS) devices

In last one or two decade, the use of FACTS devices has becomea common practice in order to make full utilization of existingtransmission capacities instead of adding new lines. El-Emary andEl-Shibina [258] have presented a new technique of AGC regulatordesign based on static var compensators (SVC). The thyristorcontrolled phase shifter (TCPS) is expected to be an effectiveapparatus for the tie-line power ow control in an interconnectedpower system. It injects a variable series voltage to affect thepower ow by modifying the phase angle. The design of decen-tralized controller based on GA with and without redox owbatteries including TCPS is presented in [203]. The used of TCPS toprovide an active control facility of LFC problem in the deregulatedthree-area power system is presented in [259]. In [237] a robustdecentralized frequency stabilizer design through static synchro-nous compensators by taking system uncertainties in considera-tion is proposed.

The LFC of interconnected two-area system with one area asmulti-unit of all-hydro power system and second area as all-thermal/thermal-hydro mixed have been investigated in [260].The authors present a coordinated control between TCPS and SMES,with the gains of the integral controller in AGC loop and parametersof TCPS/SMES being optimized by craziness-based PSO.

8. LFC in distributed generation power systems

The above sections presented LFC issues in conventional powersystems. However, with rapid decline of the fossil fuel andadvancement in green energy, the DG such as wind, solar comesinto play to meet the scarcity of load demand. Hence the LFCproblem associated with DG is discussed in the subsequentsection.

8.1. PV, wind farms, diesel engine and energy storage system basedhybrid DG

The PV power generating systems are expected to play a keyrole in meeting future demands for electricity. The relatively highcost of PV generated electricity makes it attractive only for remotestand-alone loads or small applications. In isolated operation ofwinddieselphotovoltaic hybrid power system, the intermittencyhas been presented in [247]. Aditya and Das [248] have revealedthat use of BESS is helpful in meeting sudden requirements of realpower and is effective in reducing the peak deviations of fre-quency and tie-line power. Thus it reduces the steady-state valuesof time error and inadvertent interchange accumulations. Banerjeeet al. [29] presented the effectiveness of small sized magneticenergy storage units (both superconducting and normal losstypes) to improve the load-frequency dynamics of two-areathermal power system. Chun et al. [249] studied the effect ofgovernor dead-band and GRC, along with the effect of BESS on LFC.Tetsuo [250] presented the rechargeable batteries such as redoxow, which are not aged by frequent charging and discharging. Itis said to have a quick response equivalent to SMES and out-standing overload capability. Fuzzy gain scheduled SMES unit forimprovement of LFC in two-area thermal power system is pre-sented in [251]. Tripathi and Juengst [252] have presented feasi-bility of using an IGBT convertor instead of thyristor convertor as ain wind speed, and solar radiation causes a large uctuation insystem power and frequency. The inuence of PV power genera-tion on LFC is presented in [261]. Besides BESS, SMES units, afavorable effect of integrating a FC into the power system has alsobeen evident [262]. The authors [133] presented a coordinatedcontrol approach for output power uctuation leveling of PVsystems using fuzzy logic concept with consideration of powersystem condition and insolation condition. A coordinated controlapproach based on the minimal-order observer for the LFCproblem is presented in [132]. The LFC problem of isolatedutility-connected large PV-diesel hybrid power system based onsimple fuzzy logic approach is also proposed in [263].

The LFC problem becomes complex by integration of wind farmgrid because of the uctuating output power due to intermittentnature of wind speed. Thus in such cases, the LFC needs to beaddressed differently. The studies related to LFC incorporating thedynamics of wind farms are presented in [264267]. In [264], theauthors have presented modication in unit commitment, eco-nomic dispatch, regulation and frequency controls, when the levelof wind generation capacity is signicant. Curtice et al. [265]presented a study to analyze the effects of small wind turbinesoutput on the LFC. The effect of large number small wind turbineson LFC is presented in [94]. The LFC of WT based power system isdiscussed in [268]. In [269], a wind-turbine driven self-excitedinduction generator is considered as variable speed, constantvoltage, and constant frequency supply with isolated resistive loadconnected. The simplied model is used to develop a controlstrategy that aims to maintain the generator terminal voltage andfrequency constant in case of variations in the load and/or windspeed. The wind farms with HVDC with participation in LFC oractive power sharing during system load or generation change isdiscussed in [116].

In [128], frequency control method is presented by the WF andthe BESS using load estimation, in which the frequency deviationin low and high frequency domain are reduced by the WF usingpitch angle control and charge/discharge, respectively. The fre-quency control with controlling speed of wind turbine is pre-sented in [270285]. The frequency support from DFIG windturbines are presented in [101109,111]. The winddiesel hybridsystem is an economically viable action for large as well as smallcommunities. Bhatti et al. [100] designed a load frequency con-troller for isolated winddiesel hybrid power systems, and eval-uated its effect on the transient performance of the system.Milanovic and Soultanis [286] analyzed the operation of autono-mous winddiesel system with the load control. The study iscarried out using the PSCAD/EMTDC computer simulation package.Next, the authors in [121] analyzed the effect of stand-alonehybrid power system consisting WTGs, DEG, FC, and AE onfrequency variation. Goya et al. [126] presented H control theorybased on droop characteristics for the frequency control by usingparallel operated battery in isolated island. The PSO based designof the robust fuzzy logic-based-PID controller for LFC in isolatedwinddiesel hybrid power system is proposed in [100]. The designof robust frequency controller of SMES in a hybrid winddieselpower system by using loop shaping control technique and tuningof controller parameters using GA is discussed in [127].

The time-domain simulation for small-signal analysis of ahybrid power generation/energy storage system is presented in[135]. The authors concluded that the power generation from theWTG, PV, DEG, and FC with energy stored or released from theFESS/BESS can effectively meet the variations in load powerdemand. Also, the system frequency deviation can be properlycontrolled within a very small range. The impact of wind powergeneration on system frequency control is discussed in [130].The LFC by coordination control of WTG and the double layercapacitor in an autonomous hybrid renewable energy power

generation is presented in [137]. In the proposed method, the

[99] addressed real and reactive power management strategies of

S.K. Pandey et al. / Renewable and Sustainable Energy Reviews 25 (2013) 318334 327load variation is reduced in low and high frequency domain by FCand capacitor, respectively. The GA based PID controller for LFC ofautonomous hybrid generation systems consisting differentrenewable energy generation/storage systems such as three WTGs,a DEG, FCs and a PV, a BESS, and an FESS is proposed in [40]. Thefrequency control of wind energy storage system (BESS taken asenergy storage system) based on model predictive controlapproach, having tested on real measurement from a power gridis discussed in [138].

The authors [263] presented a stable active power control ofDFIG with wind power variations. Depending upon the rotor speedcondition, the DFIG can be controlled to trace operator's activepower command. The moving-average with K deviation method isalso introduced to preserve a certain amount of wind powerreserve for wind power frequency regulation in the study. TheLFC of two/three-area interconnected power system in the DFIGbased wind turbine using the model predictive control (MPC)technique is proposed in [139]. The robust performance is demon-strated against uncertainties due to governors and turbines para-meters variation and load disturbances. The LFC of variable speed,variable pitch wind generators are discussed in [144], in whichtwo control strategies are used. The rst one is based on over-speeding, de-loading for wind speed control to avoid over loadingof the converter of DFIG, and second one uses pitch-controlled de-loading fast LFC action. The dynamic participation of DFIG basedwind farm for LFC with coordinated control of TCPS and SMES isproposed in [141], while in [142], the identical thermal intercon-nected two-area power systemwith DFIG based WTs is consideredfor LFC including frequency linked pricing. The LFC for three-areainterconnected power system with high penetration of WTs, usingfuzzy logic approach is proposed in [147]. The authors [134]presented an integrated control approach for WF to control thefrequency deviations of winddiesel power system. In study, thefrequency control is achieved by load estimation and short-termahead wind speed prediction. The minimal-order observer asdisturbance observer is used for load estimation, while the least-squares method is used for the prediction of short-term aheadwind speed. The predicted wind speed adjusts the output powercommand of the WF as a multiplying factor with fuzzy logicconcept. The authors [140] proposed mathematical modeling ofseveral types of wind generators taking into account their depen-dence with respect to system frequency variations. These modelsare then implemented in a Newton-based power ow algorithmwith frequency control devices to estimate their electricalresponse after the action of the primary frequency regulation.

8.2. Other DG systems

Wayne et al. [287] presented transient stability analysis forSohio Prudhoe Bay emergency power system. A small-isolatedpower system of such type is susceptible to stability problems.These power systems, having two or more generator sets operat-ing in parallel with remarkably different mechanical and controlcharacteristics, require transient stability analysis. These aredened having unit ratings less than 100 kW. They are oftensituated in remote communities or area. Douglas [288] describedthe original research and development of microprocessor basedelectronic load governor that incorporates three-phase balancing.The combined study and testing of transient behavior of thegovernor indicated the need for an improved control algorithm.Doolla and Bhatti [97] presented a novel technique for LFC in anisolated small-hydro plant. In general, the frequency is controlledby using a dummy load, whose rating is equal to the rated outputpower of the plant. The scheme proposed reduces the size of thedummy load by controlling input power of the hydro power plant

using on/off control strategy. Kourosh et al. [98] discussed study of aelectronically interfaced DG units in the context of a multiple-DGmicro-grid system. Prakash et al. [290] presented LFC of isolatedautonomous hybrid system consisting of different renewableenergy resources. The GA based loadfrequency PI controllerof an autonomous hybrid generation system is presented in[291,292].

The supplementary LFC method by use of a number of bothelectric vehicle and heat pump water heater as controllable loadsis proposed in [143]. The aggregate LFC of a wind-hydro autono-mous micro-grid system is described in [145]. The LFC by PHEVs,controllable loads, and a cogeneration unit is discussed in [146].The authors [148] address the current AGC structure and itsdrawbacks, and new AGC with cyber architecture to accommodateintermittency of high penetration, non-dispatchable distributedenergy resources for smart power grids. The autonomous distrib-uted vehicle to grid control scheme providing a distributedspinning reserve for the unexpected intermittency of the renew-able energy sources is proposed in [149]. The study presents adroop control based on the frequency deviation at plug-in term-inal. The aggregated electric vehicle-based battery storage repre-senting vehicle to grid system, modeled for use in long-termdynamic power system is proposed in [150].

9. Conclusion

The techniques and strategies of LFC for conventional and DGsystems attracted much discussion in the recent past. An effort hasbeen made to present critical and comprehensive revive on thissubject. Emphasis has been given how to tackle the LFC issues inDG system. A detail survey has been done and presented. Light hasbeen thrown on categorizing various power system structure/layout reported in the literature that focusses on LFC controltechniques adopted and their shortcomings. It has been observedin this literature survey that most of the researchers have donework on LFC problems conned to conventional power system.Some of the statistical attributes in time domain are given in theAppendix. Further, it can be said that there exists a lot of researchopportunities in DG systems on issues related to LFC. This surveypaper will serve as a valuable reference for researchers to work onLFC problem in DG system.

Appendixdistribution system that has enough generation to track its loadwithout the help of a substation. Specically, it addresses thepresence of solid-oxide fuel cells in the DG mix. Two control loopsare proposed (i) to guarantee that the fuel cell is protected bymaintaining its cell utilization within its admissible range and (ii) totrack load changes and regulate the frequency. A distribution areaerror is introduced to formulate the frequency-control problem.

In [289], the authors presented a method for cooperativecontrol of DC power feeding system with power producer andsupplier owned dispersed generators under the balancing rule. Inthis work, FC, PV and ultracapacitor as dispersed generators areintroduced. Prakash et al. [112] proposed small-signal analysis ofisolated as well as interconnected autonomous hybrid DG systemfor sudden variation in load demand, wind speed and solarradiation. The hybrid systems compromise of different renewableenergy resources such as wind, PV, FC and DEG along with theenergy storage like battery and ywheel units. Further, in thestudy, ultra-capacitors as an alternative energy storage elementand interconnection of hybrid system through tie-line are incor-porated into the system for improved performance. Katiraei et al.Please see Table A1.

Table A1Short summary of time domain performance.

Comparative results of Ref. [39,42] and [40].

Ref. no. Conguration of system Control approach Operating conditions Undershoot [pu] Settling time (s)

f1 f2 Ptie f1 f2 Ptie

[39] Two-area reheat thermal power systemwith governor dead zone(GDZ), GRC, andcoordination of SMES

Fuzzy logic controlled SMES stabilizerand conventional PI SMES stabilizer

Without GDZ but withSMES Pd10.02 pu

PI SMES 0.029 0.019 0.08 4.5 4.5 5FL SMES 0.02 0.014 0.005 4.5 4.5 5

Without GDZ but withSMES Pd20.02 pu

PI SMES 0.019 0.025 +0.008 (Overshoot) 5.5 5 5FL SMES 0.012 0.02 +0.005 (Overshoot) 5 4.8 4.8

[42] Two-area with multi-units of three typeof systems with TCPS and SMES

Integral Controller and its gain andparameters of TCPS and SMESis optimized by CPSO

Hydro-Hydro 0.49 0.39 0.121 50 70 45Pd1Pd20.02 puThermalthermal 0.18 0.22 15 20 Pd1Pd20.02 puThermalhydro 0.19 0.55 50 50 Pd1Pd20.02 pu

[40] Two-area reheat thermal power systemwith boiler dynamic effect and SMES

Type-2 fuzzy logic controller Pd10.01 pu 0.015 0.012 0.003 12 12 15Pd20.01 pu 0.013 0.013 +0.0005(Overshoot) 10 11 15Pd1Pd20.01 pu 0.013 0.017 0.0001 13 10 20

Comparative results of Ref. [52] and [61].

Ref. no. Conguration of system Controller design Control structure Operating conditions ACE1 Avg [pu] ACE2 Avg [pu] ACE3 Avg [pu]

[52] Interconnected three-area thermal power systems GALMI based PI PI Pd1100 MW, Pd280 MW Pd350 MW 0.0122 0.0096 0.0056H 9th order Pd1100 MW, Pd280 MW Pd350 MW 0.0104 0.0102 0.0103

[61] GA based PI PI Pd1100 MW, Pd280 MW Pd350 MW 0.0104 0.0071 0.0063Pd1100 MW, Pd280 MW Pd350 MW 0.0103 0.0087 0.0114

Results of Ref. [57,58] and [5].

Ref. no. Conguration of system Controller design Operating conditions Undershoot [pu]

f1 f2 f3

[57] Interconnected three-area thermal powersystems with time delays

LMI based LFC Conventional AGC 0.001 0.001 0.005AGC with full state LMI control 0.001 0.0012 0.004AGC with LMI decentralized control 0.007 0.0098 0.0035LMI controller with ACE delays and telemetry delaysto the control areas of 4 s, 2 s and 4 s, respectively

0.007 0.0013 0.004

[58] Multi-area connected systems(four generating units as one control area)

Iterative LMI via H2/H based PI controller 5 s delay with 0.1 pu step load increase 0.0048 s delay with 0.1 pu step load increase 0.0056 s delay with a sequence of step load changes The frequency deviation and ACE of the control area are properly maintained

within a narrow band with smooth control efforts.[5] Interconnected three-area thermal power

systems with time delaysLMI based PI controller Integral controller (KI0.05) Delay margin is within the range of [3.1 s, 3.4 s] for Stability region.

PI controller (KP0.2, KI0.05)Results of Ref. [139,141] and [147].

Ref.no.

Conguration of system Control approach Operating conditions Undershoot [pu] Settling time (s)

f1 f2 Ptie f1 f2 Ptie

[139] Two-area and three-areathermal power system withwind turbines (WTs)

Model predictive control(MPC) technique

Conventional integratorK(s)0.3/s, PL0.02 pu,

With MPC and WT(two-area system)

0.04 0.03 0.01 12 12 15

With MPC and without WT(two-area system)

0.045 0.03 0.01 15 15 20

Governor and turbine timeconstants are increased to

With MPC and WT two-area system 0.03 0.02 0.01 7 7 80.02 0.01 +0.005 8 8 10

S.K.Pandey

etal./

Renew

ableand

SustainableEnergy

Review

s25

(2013)318

334328

31%,9

5%in

area-1

and66

%,

38%in

area-2,respectively

Three-area

system

(f 3)

(f 3)

WithMPC

andwithou

tWT

Two-area

system

0.03

80.02

50.01

88

10Th

ree-area

system

0.02

20.01

+0.005

109

12(

f 3)

(f 3)

[141]

Two-area

ofthermalthermal

(TT)

andhy

dro-hyd

ro(H

H)intercon

nectedpow

ersystem

withTC

PS,SMES

and

DFIGbasedwindfarm

inderegulated

environmen

t

Integral

gainsof

AGCloop

andparam

etersof

TCPS

and

SMES

areop

timized

byCRPSO

Withwindpen

etration

butno

pow

erfrom

DFIG.W

indpen

etration

levelan

dwindspeedarea

considered

tobe

20%an

d7.5m/s,respectively

inarea-2.

TT-H

H0.65

1.8

+0.08

3525

(TT-TT

)(0.45)

(0.5)

(+0.08

)(35)

(25)

(55)

TT-H

H(TT-TT

)0.6

1.5

+0.07

3023

withTC

PS-SMES

(0.4)

(0.43)

(+0.005

)(30)

(23)

(53)

TT-H

HW

0.42

1.0

+0.05

215

15

(TT-TT

W)

(0.39)

(0.39)

(+0.005

)(25)

(23)

(35)

TT-H

HW

0.4

1.0

+0.05

1010

(TT-TT

W)withTC

PS-SMES

(0.37)

(0.36)

(+0.005

)(20)

(20)

(10)

[147

]Th

ree-area

ThermalTh

ermal

withwindfarm

sFuzzylogiccontroller

Startup,rated

,andcutou

twindspeed

are5m/s,14m/s,and24

.5m/s,respectively.

Thewindpow

erpen

etration

is10%.

0.15

0.16

0.16

3030

30 (f 3)

(f 3)

Sameas

aboveexcept

that

thewindpow

erpen

etration

is30

%.

0.1

0.1

0.1

1010

10 (f 3)

(f 3)

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