CPSO based LFC for a Two-area Power System with GDB and GRC Nonlinearities Interconnected through TCPS in Series with the Tie-Line

Transcription

1 CPSO baed LFC for a woarea Power Sytem with GD and GRC Nonlinearitie Interconnected through CPS in Serie with the ieline R. rivoli ociate Profeor Department of Electrical Engineering, nnamalai Univerity nnamalainagar 68. amilnadu, India Dr. I.. Chidambaram Profeor Department of Electrical Engineering, nnamalai Univerity, nnamalainagar 68. amilnadu, India SRC In thi paper the deign of Proportional Integral (PI) controller i propoed uing Crazine Particle Swarm Optimization (CPSO) baed Integral Square Error (CPSOISE), CPSO baed pex Stability erge (CPSOS) and MultiObjective baed CPSO (MOCPSO) are ued to deign the controller for a twoarea power ytem conidering Governor Dead and (GD) and Generation Rate Contraint (GRC) nonlinearitie coordinate with Super Conducting Magnetic Energy Storage (SMES) unit and interconnected through hyritor Controlled Phae Shifter (CPS). CPSO algorithm i a powerful optimum earch technique, the alient advantage i that it i highly inenitivity to large load change and diturbance in the preence of plant parameter variation and ytem nonlinearitie under load following variation. For the propoed method, two type of controller namely, Mutual id Criterion (MC) baed Integral Square Error (ISE) and pex Stability erge (S) controller are deigned firt and then the propoed MOCPSO controller i deigned. Simulation reult of the propoed MOCPSO controller i not only effective in damping out frequency ocillation, but alo capable of alleviating the tranient frequency wing caued by the diturbance. From the dynamic repone it reveal that the MOCPSO baed controller for the two area reheat power ytem with SMES, interconnected with CPS enure better tranient performance and fater ettling time than that of the CPSOISE baed controller. General erm LoadFrequency Control (LFC), PI controller, Mutual id Criterion (MC), Crazine Particle Swarm Optimization (CPSO), Integral Square Error (ISE), Super Conducting Magnetic Energy Storage (SMES), hyritor Controlled Phae Shifter (CPS), Governor Dead and (GD), Generation Rate Contraint (GRC). eyword pex Stability erge (S), Crazine Particle Swarm Optimization baed pex Stability erge (CPSOS), CPSO baed Integral Square Error (CPSOISE), MultiObjective CPSO (MOCPSO).. INRODUCION Increae in Generation, ranmiion and Utilization of modern power ytem ha led the ytem to more complex. Hence the power upply with tability and high reliability i eential. LoadFrequency Control (LFC) i a very important problem in power ytem operation and control by which a balance between electric power generation and power conumption i maintained. Exiting power ytem conit of many control area interconnected together and power i exchanged between control area through tieline by which they are connected. LFC play a ignificant role in the power ytem by maintaining cheduled ytem frequency and tieline flow during normal operating condition and alo during mall load perturbation. he tability of the interarea ocillation mode i deteriorated by the heavy load condition in tieline epecially due to the electric power exchange. he Load Frequency Control (LFC) problem i of vital importance in electrical power ytem deign/operation and attention ha been directed toward deigning efficient controller to enure reliable and quality power upply. here ha been coniderable effort devote to LFC of interconnected power ytem in the literature [, ]. o enure dynamic performance of the power ytem, a number of control trategie have been employed in the deign of load frequency controller. he application of decentralized control trategy to the LFC problem ha found wide acceptance becaue of it role in eliminating mot of the problem aociated with other centralized or multilevel control trategie [39]. hi paper focue on the analyi carried out for the GC of a twoarea interconnected thermal power ytem conidering CPS in erie with the tieline. Invetigation are alo carried out to examine the capability of the CPS damping controller in twoarea interconnected power ytem. n interconnected thermal ytem involve widely different characteritic for the thermal ytem. he characteritic of team turbine i that the relatively large inertia ued a a ource of energy caue a coniderable greater time lag in the repone of the change in the prime mover torque to a change in gate poition, and alo a nonminimum phae behaviour, that i, an initial tendency for the torque to change in a direction oppoite to that finally produced. Moreover, the maximum permiible generation rate contraint for the thermal unit. Further, the effect of different generation rate contraint on the election of optimum controller etting for the thermal two area and on the ytem dynamic performance conidering a CPS in erie with the tieline can be etablihed efficiently. In view of the above, the main objective of the preent wor are:. o deign the controller for a twoarea power ytem conidering Governor Dead and (GD) and Generation Rate Contraint (GRC) nonlinearitie coordinate with Super

2 SMES SMES S Conducting Magnetic Energy Storage (SMES) unit and interconnected through hyritor Controlled Phae Shifter (CPS).. o minimie the ocillation in the ytem frequency and tieline power conidering a CPS in erie with the tieline of a twoarea interconnected thermal power ytem. 3. o optimie the gain etting of the ProportionalIntegral controller uing CPSOISE, CPSOS and MOCPSO. 4. o compare the dynamic repone. For the pat everal decade, lot of wor pertaining to the deign of claical controller for interconnected power ytem [37] ha been carriedout and in mot of the cae, the mathematical model ha been over implified by ignoring the imultaneou preence of important ytem nonlinearitie uch a Governor Dead and (GD) and Generation Rate Contraint (GRC). ll governor in the thermal reheat power ytem have deadband lie mechanical friction, baclah, valve overlap in hydraulic relay, which are important for peed control even under mall diturbance. So, the peed governor deadband ha ignificant effect on the dynamic performance of loadfrequency control ytem. Moreover, the GD ha a detabilizing effect on the tranient repone of the ytem [6, 8]. G G G n C C C C CPS ( Load rea u d : jx In a power ytem, another mot important contraint on modern large ize thermal unit i the tringent generation rate contraint i.e. the power generation can change only at a pecified maximum rate. he GRC of the ytem i conidered by adding a limiter to the control ytem. In thi condition, the repone will be with larger overhoot and longer ettling time when compared with the ytem where GRC i not conidered. So, if the parameter of the controller are not choen properly, the ytem may become untable. In the imultaneou preence of GD and GRC, even with mall load perturbation, the ytem become highly nonlinear and hence the optimization problem become rather complex. Many control trategie have been employed in the deign of loadfrequency controller for interconnected power ytem conidering GD and GRC nonlinearitie. Firt Crazine Particle Swarm Optimization baed PI controller on the bai of the cot function uing MC i deigned. Secondly MC baed PI controller on the bai of the ettling time of the output frequency deviation repone ieline C C Load G G G n rea u Figure.wo area thermal power ytem with CPS i for % tep load diturbance in area i deigned. he firt controller i referred a CPSOISE controller and the econd i referred a CPSOS controller. he gain P, I of CPSOISE and CPSOS controller will be the lower and upper or upper and lower limit of the propoed MOCPSO controller. hi paper invetigate the performance of the MOCPSO controller in a twoarea power ytem interconnected with CPS. From the imulated reult the controller deigned baed on MOCPSO enure better tranient performance and fater ettling time than that of the controller deigned with CPSOISE.. SEMEN OF HE PROLEM he tate variable equation of the minimum realization model of the twoarea inter connected power ytem i expreed a ẊxuΓd () CE, CE,Δf,G, X { Δφ,,Δf,,, U d [ U ] [ ], U C,C [ d,d ] [, ] tie D G D G G E, Where i the ytem matrix, i the input ditribution matrix, Γ i the ditribution diturbance matrix, x i the tate vector, u i the control vector and d i the diturbance vector due to change in load. 3. POWER SYSEM MODEL FOR SIMULION NLYSIS he GC ytem invetigated comprie of an interconnection of two area, both area compriing of a nonreheat thermal unit. Fig. how the chematic of twoarea interconnected thermal power ytem with CPS. wo area are connected by a wea tieline. CPS i placed in erie with the tieline near area. CPS i a device that change the relative phae angle between the ytem voltage [4]. herefore, the real power flow can be regulated to mitigate the frequency ocillation and enhance power ytem tability. he mall perturbation tranfer function bloc diagram of Fig. i hown in Fig.. When there i udden rie in power demand in a control area, the governor control mechanim tart woring to et the power ytem to the new equilibrium condition. Similar action happen when there i a udden decreae in load demand. aically, the operation peed of governorturbine ytem i low compared with that of the excitation ytem. a reult, fluctuation in terminal voltage can be corrected by the excitation ytem very quicly, but fluctuation in generated power or frequency are corrected lowly. Since load frequency control i primarily concerned with the real power/frequency behaviour, the excitation ytem model will not be required in the approximated analyi [5]. hi important implification pave the way for contructing the imulation model hown in Fig.. he baic objective of the upplementary control in Fig. i to retore balance between each area load and generation for a load diturbance. hi i met when the control action maintain the frequency and the tieline power interchange at the cheduled value. } E,

3 β PID N.SN g.s SMES R Speed regulation GRC Governer t S rr. r. Pd(S) PS p p. f / Integrator a SMES CPS p ie line P tie a π S / Integrator PID Governer N.SN g.s t GRC S rr. r. p p. PS f β R Pd(S) L tout Cloc o Worpace Figure.Simulin diagram of the propoed hermal Reheat Sytem with SMES Conidering GD and GRC interconnected through CPS in Service with the ie line 4. SE SPCE MODEL For a twoarea thermal reheat interconnected power ytem he following equation can be written Δ PG r G r r t G r t E (8) Δ F p p Δ P G Δ PG r g G E c ( ) () t r G g R g E r t E D Δ Ptie, t G r t G tie, E p (3) (4) (5) ( ) (6) Δ P G Δ F r g E p p Δ PG E t g E c t R g G (9) () ( Δp Δp ) () r t G r G G D r t ac E dc p () Δ F p p ( a ) (7) G D tie, p Δ P G t E t G (3) 3

4 Δ X E g CE E β g c R g ac Δ Ptie, π Δ F p p Δ PG p p Δ P G Δ X g dc (4) (5) ( ) (6) ( ) (7) G D ac dc ( a a ) (8) r E c G t G g R g D E r E t r t ac G G r t dc E p p (9) () () 5. INCREMENL IELINE POWER FLOW MODEL CONSIDERING CPS the recent advance in power electronic have led to the development of the FCS device. Which are deigned to overcome the limitation of the mechanically controlled device ued in the power ytem and enhance power ytem tability uing reliable and highpeed electronic component. One of the promiing FCS device i the CPS. CPS i a device that change the relative phae angle between the ytem voltage. herefore the real power flow can be regulated to mitigate the frequency ocillation and enhance power ytem tability. In thi tudy, a twoarea thermal power ytem interconnected by a tieline i conidered. Fig. how the chematic repreentation of the twoarea interconnected thermal ytem conidering a CPS in erie with the tieline. CPS i placed near rea. Practically, in an interconnected power ytem, the reactancetoreitance ratio of a tieline i quite high (X/R ) and the effect of reitance on the dynamic performance i not that ignificant. ecaue of thi, the reitance of the tieline i neglected. wo rea interconnected thermal power ytem compriing. Without CPS, the incremental tieline power flow from rea to rea can be expreed a [5] P tie ( f f ) () Where i the ynchroniing power coefficient without CPS and f and f are the frequency deviation of rea and, repectively. When a CPS i placed in erie with the tieline, a in Fig., the current flowing from rea to rea can be written a ( ) i (3) jx From Fig., it can be written a P tie jq tie * i ( ) P tie X j jq tie in( ) ( ) jx co ( ) X Separating the real part of (5), we get (4) (5) tie in(δ δ φ) (6) x P In (6), perturbing and w from their nominal value δ, δ and φ from their nominal value δ,δ and φ, repectively, eqn. () now become P tie co( x in( ) (7) However, for a mall change in real power load, the variation of bu voltage angle and alo the variation of CPS phae angle are very mall. hu, in effect, ( i very mall and hence in( Δδ Δδ Δφ) (Δδ Δδ Δφ) (8) herefore Let x tie co(δ δ φ )(Δδ Δδ Δδ Δδ Δφ ) Δφ) (9) co(δ δ φ ) x (3) 4

5 hu (9) reduce to tie (Δδ Δδ Δφ) (3) Δ Ptie (Δδ Δδ Δφ) (3) It i nown f dt and f dt (33) From (3) and (33) P tie ( ) f dt f dt Laplace tranformation of (34) yield (34) P tie ( ) [ F ( ) F ( )] ( ) (35) per (35), tieline power flow can be controlled by controlling the phae hifter angle Δ φ. uming that the control input ignal to the CPS damping controller i ΔError () and that the tranfer function of the ignalling conditioning circuit i φ c(), where φ i the gain of the CPS controller Δφ() φ C()Δ()ΔError () (36) nd C () (37) p Hence, the phae hifter angle Δ φ() can be repreented a [3, 6] φ Δφ() ΔError () (38) p where p i the time contant of the CPS and ΔError () the control ignal which control the phae angle of the phae hifter. hu (35) can be rewritten a P tie ( ) p [ F ( ) Error ( ) F ( )] (39) 5. CPS control trategy ΔError can be any ignal uch a the thermal area frequency deviation f or the area control error of the thermal area CE (i.e. Error f or CE) to the CPS unit to control the CPS phae hifter angle which in turn control the tieline power flow. hu, with Error f φ Δφ() Δf() p (4) and the tieline power flow perturbation a given by (39) become P tie ( ) p F ( ) [ F ( ) F ( )] (4) When the area control error of area, CE Δf Δptie i choen a the control ignal (i.e. Error CE), to the CPS unit, the tieline power flow perturbation become tie π () φ p ΔCE [ () () ()] (4) However, from the practical point of view, a CPS i placed near rea, meaurement of f will be eaier rather than CE, which require meaurement of tiepower alo. Hence, in the preent wor, the frequency deviation of the thermal area f i choen a the control ignal. he parameter PS and φ of the CPS are given in ppendix. However, from the practical point of view, a CPS i placed near rea, meaurement of f will be eaier rather than CE, which require meaurement of tiepower alo. Hence, in the preent wor, the frequency deviation of the thermal area f i choen a the control ignal. he parameter PS and φ of the CPS are given in ppendix. 6. SUPER CONDUCING MGNEIC ENERGY SORGE (SMES) DEICE Superconducting Magnetic Energy Storage (SMES) unit with a elfcommutated converter i capable of controlling both the active and reactive power imultaneouly and quicly, increaing attention ha been focued recently on power ytem tabilization by SMES control []. he chematic diagram in Figure 3 how the configuration of a thyritor controlled SMES unit. he SMES unit contain DC uperconducting Coil and converter which i connected by Y D/Y Y tranformer. he inductor i initially charged to it rated current Id by applying a mall poitive voltage. Once the current reache the rated value, it i maintained contant by reducing the voltage acro the inductor to zero ince the coil i uperconducting. Neglecting the tranformer and the converter loe, the DC voltage i given by Ed d co α IdRc (43) 5

6 C SYSEM US YY RNSFORMER CE i Where Ed i DC voltage applied to the inductor (), firing angle (α), Id i current flowing through the inductor (). Rc i equivalent commutating reitance () and d i maximum circuit bridge voltage (). Charge and dicharge of SMES unit are controlled through change of commutation angle α []. In GC operation, the dc voltage Ed acro the uperconducting inductor i continuouly controlled depending on the ened error ignal of that area. Moreover, the inductor current deviation i ued a a negative feedbac ignal in the SMES control loop. So, the current variable of SMES unit i intended to be ettling to it teady tate value. If the load i ued a a negative feedbac ignal in the SMES control demand change uddenly, the feedbac provide the prompt retoration of current. he inductor current mut be retored to it nominal value quicly after a ytem diturbance, o that it can repond to the next load diturbance immediately. a reult, the energy tored at any intant i given by WL LId / MJ (44) Where L inductance of SMES, in Henry) Equation of inductor voltage deviation and current deviation for each area in Laplace domain are a follow: E ( ) di Im SMES ( dci p P m P m P m I d m I m m L m I m P * m E L d dc SUPER CONDUCUING INDUCOR Figure 3.he Schematic diagram of SMES unit. Im )[ ( ) ( )] ( ) id F P I tie di dci P m Figure 4. SMES control ytem in each area. (45) ΔE di () converter voltage deviation applied to inductor in SMES unit SMES Gain of the control loop SMES dci converter time contant in SMES unit id gain for feedbac ΔId in SMES unit. ΔI di () inductor current deviation in SMES unit he deviation in the inductor real power of SMES unit i expreed in time domain i a follow SMESi ΔE di I doi ΔI di ΔE di (47) In a twoarea interconnected thermal power ytem even due to udden mall diturbance will continuouly diturb the normal operation of power ytem. a reult the requirement of frequency control of area beyond the governor capabilitie SMES i located in the area under diturbance aborb and upply required power to compenate the load fluctuation. 7. CPSOISE CONROLLER DESIGN Crazine Particle Swarm Optimization (CPSO) i a population baed on tochatic optimization technique developed by ennedy and Eberhat in 995 []. hi method find an optimal olution by imulating ocial behaviour of bird flocing. he population of the potential olution i called warm and each individual olution within the warm i called a particle. Particle in CPSO fly in the earch domain guided by their individual experience and the experience of the warm. Each particle now it bet value o far (pbet) and it x, y poition. hi information i an analogy of the peronal experience of each particle. More over each agent now the bet value o far into group (gbet) among pbet. hi information i an analog of the nowledge of how the other particle around them have performed. Each particle trie to modify it poition uing thi information : the current poition (x, x, xd), the current velocitie (,,,d), the ditance between the current poition and pbet and the ditance between the current poition and gbet. he velocity i a component in the direction of previou motion (inertia). he movement of the particle toward the optimum olution i governed by updating it poition and velocity attribute. he velocity and poition update equation are given a []. v t t t t t t i vi cr ( pi xi ) cr ( gi xi ) (48) 7.. Crazine Particle Swarm Optimization CPSO algorithm wa alo introduced by ennedy and Eberhart to allow the CPSO algorithm to operate in problem pace []. It ue the concept of velocity a a probability that a bit (poition) tae on one or zero. In CPSO updating a velocity remain the ame a the velocity in baic CPSO; however, the updating poition i redefined by the following rule ( ) if r3 S vi i { } (49) if r < S(v ) S 3 i With r3~u (,) and S() i a igmoid function for tranforming the velocity to the probability contrained to the interval [.,.] a follow ΔI di ()(/Li)*ΔEdi() (46) Where, 6

7 ig (vi ) (5) exp ( v ) i Where S (v) (,), S ().5, and r3 i a quai random number elected from a uniform ditribution in [.,.]. For a velocity of, the igmoid function return a probability of.5, implying that there i a 5% chance for the bit to flip. he control area performance in any interconnected power ytem i analyzed with the interchange power flow, ytem frequency and other tandard []. part from the tandard deviation of rea Control Error (CE) another way of meauring the control performance tandard which i denoted a MC i being adopted in thi paper. When there i no correlation between the CE of the interconnected power ytem, the tandard deviation of CE which hould be proportional to the quare root of it capacity divided by the total capacity of the inter connected power ytem called a permitted value of the tandard deviation of CE of the Entire ytem wa found to be le than the permitted value []. o over come thi drawbac, CPSOMC criterion wa adopted to evaluate the performance of the ytem. MC i defined by the following equation. P i poitive in the direction from it own ytem to the other ytem. MC (α.δf. )dt Δf x Δ P In MC, ince the poitive/negative of judged, (5) i equivalent to the following equation. MC (Δf Δf x x ) (5) i (5) From (3), the dicrimination by MC i equivalent to f x P. judging the area of Mathematically, MC can be tranformed into the following equation from (5) uing CE and CE and it i aumed that P, P and P are contant [8] MC N N CE.(P CE P CE ) Nσ Δf N P σ σ Δf P.P (P CE P CE (P P ) CE CE ) P σ CE P σce σ Δf σ P (P P )R CE σ σ P Δf (54) σ (53) If MC i maller than, then equation (54)will be expreed by the following equation Hence MC σ P σce Pσ CE PR CE (55) P P CE σ CE RCE (56) When there i no correlation between the CE, the evaluation by MC become the ame a the evaluation by the tandard deviation of CE. However, a there i no reference value to evaluate a generation control in MC, the evaluation by MC become a relative one between control area. Decentralized optimum proportional and integral controller for the interconnected power ytem are deigned by uitably adopting the Integral Performance Index criterion. characteritic of thi criterion i that it weight large error heavily and mall error lightly [7]. o obtain the optimum decentralized controller gain i (i, N), the following quadratic performance index i conidered. t J i (x ei w i x ei ) dt i,,, N ( 57) Where x ei [ f i ] 7. Decentralized Proportional Controller Deign In the abence of the integral control one can harply increae the gain of the cloed loop ytem and thereby improve the ytem repone. If the feedbac gain of the integral controller i ufficiently high, overhoot will occur, increaing harply a a function of the gain, which i highly undeirable. hu, the integral controller gain cannot be higher becaue it lead to intability in the tranient region [6]. herefore the deign of decentralized proportional controller conidered firt. he optimum proportional controller feedbac gain P CPSOISE i obtained by plotting the cot curve for variou value of P againt the cot function of area i, J i. he cot function of area i, J i i obtained by imulating the cloed loop ytem for variou value of P and eeping I equal to zero throughout. 7.3 Decentralized Proportional Plu Integral Controller Deign Following the procedure dicued in the ection 5., the integral controller i alo deigned. he cot function of area i J i i obtained by imulating the cloed loop ytem for variou value of I and eeping P equal to P CPSOISE. Following the procedure dicued in the ection 5., the integral controller i alo deigned. he cot function of area i J i i obtained by imulating the cloed loop ytem for variou value of I and eeping P equal to P CPSOISE. 8. CPSOS CONROLLER DESIGN he cloed tability of the ytem with the decentralized controller are aeed uing the ettling time of the ytem output repone. It i oberved that the ytem whoe output repone ettle fat will have minimum ettling time and the apex tability verge. he minimum ettling time or apex tability verge can be expreed a f( P, I ) min (τ i ) (58) where τ i i the ettling time of the output repone of (f i ) frequency deviation of the i th area 8. Decentralized Proportional Controller Deign he Proportional Controller feed bac gain P(S) i obtained on the bai of the pex Stability erge criterion by plotting the maximum tability curve for variou value of P againt the ettling time of f i. he integeral feed bac gain I i treated a zero throughout thi deign. 7

8 Change in Ptie CPS (MW) Change in Pc pu MW Change in Pc pu MW Change in f (Hz) Change in f (Hz) 8. Decentralized Proportional Plu Integral Controller Deign he Proportional plu Integral Controller feed bac gain are obtained by plotting the ettling time curve for variou value of I eeping P P(S) 9. DECENRLIZED CONROLLER USING MULIOJECIE CRZINESS PRICLE SWRM OPIMIZION DESIGN he ucce of the Particle Swarm Optimization (CPSO) algorithm a a ingle objective optimizer [, ] ha motivated to extend the ue of optimization algorithm Multi Objective problem for the load frequency control problem. In problem with more than one conflicting objective, there exit no ingle optimum olution rather there exit a et of olution which are all optimal involving tradeoff between conflicting objective (pareto optimal et)[35]. If an element in archive i dominated by a new olution, the correponding element in archive i removed. If new olution i not dominated by any element in archive, new olution i added to archive. If archive i full, crowding, ditance between element in archive are computed according to [] and then one element in archive i elected to remove according to diverity. In (48) each particle need to gbet for motioning in earch pace. In MultiObjective CPSO a et of gbet that called archive there exit many different way to elect gbet. In our method, gbet i elected from archive baed on crowding ditance to maintain diverity. If an element in archive ha more diverity, it ha more chance to be elected a gbet. Roulette wheel election i ued to do it. So the particle motion to pareto optimal et and diverity i maintained with roulette wheel election for electing gbet. 9. Particle Swarm Optimization lgorithm Step : Initialie earching point and velocity are randomly generated within their limit. Step : pbet i et to each initial earching point. he betevaluated value among Pbet i et to g bet. Step 3: New velocity are calculated uing the equation. i w i v i C * rand ()*(pbet id S i ) C *rand ()*(gbet d S i ) (t Step 4: if ) id < dmin the (t) (t) id dmin and if id (t) > dmax then id dmax Step 5: New earching point are calculated uing the equation, S i Si i Step 6: Evaluate the fitne value for new earching point. if evaluated value of each agent i better than previou pbet then et to pbet, if the bet pbet i better than gbet then et to gbet. Step 7: If the optimal olution i reached top the proce, otherwie goto tep 3.. SIMULION RESULS ND OSERIONS With the conideration of Mutual id criterion (MC) the CPSO baed load frequency controller for the two area power ytem with SMES unit conidering GD and GRC nonlinearitie interconnected through CPS are deigned and implemented. Simulation i carried out to deign the Proportional plu Integral controller for. p.u MW tep load change in area and correponding repone for change in frequencie, change in tieline power flow and change in input power are obtained. From imulation reult a hown in figure 4 it i found that the controller deigned uing MOCPSO for area interconnected with CPS exhibit better tranient and teady tate performance when compared with the output repone obtained with the controller deigned uing CPSOISE for area interconnected with CPS. able. Controller Deign uing CPSOISE, CPSOS and MOCPSO criterion. Controller Deign uing CPSOISE criterion P. I.4 J.6 Settling ime (Sec) F F 3.9 P tie CPS Controller Deign uing CPSOS criterion P.6 I.96 J.734 Settling ime (Sec) F 5. F 6.5 P tie CPS 5.7 Controller Deign uing MOCPSO criterion P.4 I.3 J.63 Settling ime (Sec) F 8.7 F 6.73 P tie CPS CPSOISE MOCPSO ime () CPSOISE MOCPSO ime () CPSOISE MOCPSO ime () 8 x CPSOISE MOCPSO ime () x 3 CPSOISE MOCPSO ime () Fig 4. Frequency Deviation, Control Input Deviation and ieline Power Deviation of a wo area Power Sytem with SMES Interconnected coordinated with CPS in the tieline for % Step Load Change in rea. 8

9 . CONCLUSIONS nalyi of load frequency control model of interconnected power ytem repreentation with SMES Unit conidering GD and GRC nonlinearitie interconnected through CPS provide more detailed information about the ytem evolution of the frequency of each individual control area and the power interchanged through each tieline ha been prented. he proportional plu Integral Controller namely CPSOISE, S controller for the two area power ytem with SMES unit conidering GD and GRC nonlinearitie interconnected through CPS with are deigned and the above two controller gain are ued a the upper & lower or lower and upper limit for the propoed MOCPSO controller. he multiobjective CPSO criterion baed controller i deigned for % tep load diturbance in area. From the imulated reult it i found that the MOCPSO baed controller deigned for power ytem with SMES unit conidering GD and GRC nonlinearitie interconnected through CPS how better improved ytem performance than that of the controller deigned uing CPSOISE criterion.. CNOWLEDGEMEN he author wih to than the authoritie of nnamalai Univerity, nnamalainagar, amilnadu, India for the facilitie provided to prepare thi paper. 3. REFERENCES []. Shayeghi, H.. Shayanfar,. Jalili, Load frequency Control Strategie: tateoftheart urvey for the reearcher, Energy Conervation and Management, ol. 5(), pp , 9. [] I. Ibraheem, P. umar, DP. othari, Recent Philoophie of utomatic Generation Control Strategie in Power Sytem IEEE ranaction on Power Sytem, pp , 5. [3] L. aanez, J. Riera, J. yza, Modeling and imulation of Multi area Power Sytem Load frequency Control Mathematic and computer in Simulation, PP. 546, 984. 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10 [] M. Clere, J.ennady, he particle warm exploion, tability and convergence in multi dimenional complex pace, IEEE ranaction Evolutionary Computation, vol. 6, pp. 5873,. [] etuo Saai, azuhiroenomoto, Statitical and Dynamic nalyi of Generation control performance tandard, IEEE ranaction on Power Sytem, ol. xx PP 5,. [3] Davoud Sedighizadeh and Ellip Maehian, Particle Swarm Optimization Method, axonomy and pplication, International Journal of Computer heory and Engineering, ol., No. 5, pp.7938, 9. [4] Margarita ReyeSierra and Carlo. CoelloCoello, MultiObjective Particle Swarm Optimizer: Survey of the Stateofthert, International Journal of Computational Intelligence Reearch, ol., No. 3, pp , 6. [5] SL.Ho, S. Yang, G. Ni,E.Wc.Lo, H.C. Wong. Particle Swarm Optimization baed method for multiobjective deign optimization baed method for multi objective deign optimization, IEEE ranaction on magnetic, vol. 4 (5), pp , 5. [6] atuhio Ogata, Modern Control Engineering, Prentice Hall of India Private Limited, New Delhi, India, July 986. PPENDIX (i) Data for hermal Power Sytem with Reheat urbine conidering GD and GRC nonlinearitie [6]. Rating of each area MW, ae power M, f o 6 Hz, R R 6. Hz / pu MW, g g. ec, r r ec, t t.3 ec, p p Hz / pu MW, r r.5, p p ec,.675 pu MW / Hz,.5 pu MW / Hz, a, P D. pu MW, N.8, N., P gmax. pu MW / min, ec (normal ampling rate) (ii) Data for SMES[] I d 5. 5/unit CE. id./. L H. (iii) Data for CPS[8] PS..5 rad/hz max min NOMENCLURE a Pr / Pr CE rea control error of area GC utomatic Generation Control i Frequency bia contant i (D i /R i ) area frequency repone characteritic CPSOS Crazine Particle Swarm Optimization baed pex Stability erge f Rated Frequency H i Inertia Contant I Integral gain p Proportional gain LFC Load Frequency Control MC Mutual id Criterion MOCPSO Multi Objective Crazine Particle Swarm Optimization. CPSOISE Crazine Particle Swarm Optimization baed Integral Square Error Criterion. P Di Incremental load conumption in area i P tiei Power deviation of the interchange between area i Synchronizing power coefficient UHOR IOGRPHICS R. rivoli (959) received achelor of Electrical and Electronic Engineering (99) Mater of Engineering in Power Sytem Engineering (999) from nnamalai Univerity, nnamalainagar. During 99 7 he wa woring a Lecturer in the Department of Electrical Engineering, nnamalai Univerity and now he i woring a ociate Profeor, Department of Electrical Engineering, nnamalai Univerity nnamalainagar. He i currently puruing Ph.D degree in Electrical Engineering at nnamalai Univerity. nnamalainagar. Hi reearch interet are in Power Sytem, Electrical Meaurement. Electrical Meaurement Laboratory, Department of Electrical Engineering, nnamalai Univerity, nnamalainagar 68, amilnadu, India, I.. Chidambaram (966) received achelor of Engineering in Electrical and Electronic Engineering (99) and Ph.D in Electrical Engineering (7) from nnamalai Univerity, nnamalainagar. During he wa woring a Lecturer in the Department of Electrical Engineering, nnamalai Univerity and from 7 he i woring a Profeor in the Department of Electrical Engineering, nnamalai Univerity, nnamalainagar. He i a member of ISE. Hi reearch interet are in power ytem, electrical meaurement and control ytem. Electrical Meaurement Laboratory, Department of Electrical Engineering, nnamalai Univerity, nnamalainagar 68, amilnadu, India,