Optimized coordinated control of frequency and voltage for distributed generating system using Cuckoo Search Algorithm

Ain Shams Engineering Journal xxx (2017) xxx–xxx

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Optimized coordinated control of frequency and voltage for distributed generating system using Cuckoo Search Algorithm Pankita Mehta a, Praghnesh Bhatt a,⇑, Vivek Pandya b a b

Department of Electrical Engineering, C.S. Patel Institute of Technology, CHARUSAT, Changa, Gujarat, India Department of Electrical Engineering, School of Technology, PDPU, Gandhinagar, Gujarat, India

a r t i c l e

i n f o

Article history: Received 1 June 2016 Revised 29 July 2016 Accepted 25 August 2016 Available online xxxx Keywords: Automatic Voltage Regulator Cuckoo Search Algorithm Distributed Generation Load Frequency Control SVC

a b s t r a c t The distributed generating system may employ hybrid power system consists of diesel and wind power generating units based on synchronous and induction generator (IG), respectively, to supply small isolated load. Frequency and voltage controls are major problems for such system as smaller synchronous generator (SG) offers lesser inertia and IG draws reactive power for its operation. In this paper, the voltage control loop governed by automatic voltage regulator of SG has been integrated with frequency control loop to yield optimized transient responses for frequency and voltage deviations. The linearized model of hybrid system with coordinated control of voltage and frequency has been developed. The dynamic responses of frequency and voltage deviations are compared for different active and reactive load disturbances. The gains of controller of SG and Static Var Compensator (SVC) at the terminal of IG have been optimized with Cuckoo Search Algorithm to minimize frequency and terminal voltage deviations. Ó 2017 Production and hosting by Elsevier B.V. on behalf of Ain Shams University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

1. Introduction The continuous promotions of power generation from renewable energy sources have become essential as they are clean sources of energy, sustainable and eco-friendly. The solar and wind power generations have become popular in recent years [1]. The intermittent nature of power generation from these energy sources limits their penetration in the system in order to observe the reliability in system. The use of these renewable energy sources can be explored at the larger scale if they are operated in parallel with conventional power generations. The conventional diesel enginedriven synchronous generators operating in parallel with nonconventional wind turbine-driven induction generator form the hybrid wind–diesel electrical power generation system. This type of hybrid wind–diesel electrical power generation system can either be integrated with electrical grid or be operated in standalone mode [2]. The hybrid system must be capable to maintain frequency and voltage regulation in the allowable range against the disturbances caused by load variations and wind velocity changes. Generally, fixed speed squirrel cage induction generator shave been employed for wind power generation which itself a sink Peer review under responsibility of Ain Shams University. ⇑ Corresponding author. E-mail address: [email protected] (P. Bhatt).

for the reactive power, thus imposes serious issues for maintaining the nominal voltage in case of reactive power deficit. Similarly, the low inertia of the stand-alone system may create severe frequency excursion in the event of active power unbalance. The control strategies based on orthogonal filters for frequency estimation is proposed in [3] to provide coordinated frequency and voltage control for inverter fed distributed generation (DG) systems. Consideration of variable real and reactive power demand with operational constraint has been presented in [4] for optimal design procedure of hybrid wind-diesel system. The paper also presents a strategy for real and reactive power demand sharing in real time for optimally designed wind and diesel generators. The reactive power balance condition which is a prime requirement of voltage control for stand-alone system has been obtained with nonlinear constrained optimization technique for yielding maximum wind turbine power output. In [5], the sizing of micro-hydro-PV hybrid system is proposed as per the seasonal variations in both solar and hydro resources. The simulation was carried out in HOMER software and the complementary solution was found out to explore the necessity of operating diesel generator in parallel for hybrid system. However, dynamic study for voltage and frequency control of hybrid study was not carried out. The reactive power control of an isolated wind-diesel hybrid power system has been addressed in [6]. The mathematical

http://dx.doi.org/10.1016/j.asej.2016.08.019 2090-4479/Ó 2017 Production and hosting by Elsevier B.V. on behalf of Ain Shams University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Please cite this article in press as: Mehta P et al. Optimized coordinated control of frequency and voltage for distributed generating system using Cuckoo Search Algorithm. Ain Shams Eng J (2017), http://dx.doi.org/10.1016/j.asej.2016.08.019

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model for an induction generator employed in wind turbine generator integrated with voltage control loop of conventional diesel generator was developed to study the impact of different small disturbances in the system. The optimal transient responses have been obtained with Integral Square Error (ISE) criterion. The control loops for voltage and frequency is treated separately as they are weakly coupled. The integrated effect of voltage control loop and frequency control loops have been reported in [7,8]. In [8], transient performance of distributed generation system has been studied with the mixture of different energy sources such as hydro, wind turbine generators, aqua electrolyzer, fuel cells, diesel engine generator, and energy storage devices. The integration of AVR along with PSS and AGC loop enhances the transient performance of the distributed generation system. Linear Quadratic Gaussian (LQG) controller was employed in [9] for voltage and frequency regulation of an isolated hybrid wind– diesel scheme where self-excited induction generator is connected to grid through AC–DC–AC converter and a synchronous generator driven by a diesel engine is operating in parallel. The state space model for dynamic study of wind-diesel system has been developed in [10,11] where STATCOM is used to cater the mismatched reactive power demand. The mathematical models for synchronous generator, PMIG and VSC connected PMSG have been developed and the gains of STACOM and VSC controller are optimized with ISE criterion. Evolutionary optimization techniques belong to a rich class of multi-agent stochastic global search methods which is based on unifying principle of modern biological thought called evolution. It is rapidly and widely accepted by the research communities as general purpose optimizing tools. It is an evolutionary computational model, a stochastic search technique based on swarm intelligence [12–14]. With some modifications in the basic PSO algorithm, better quality solution in terms of accelerated speed of convergence, lesser computational memory requirement and lesser time of execution may be attributed [14]. Recently, Cuckoo Search Algorithm (CSA) which simulates the intelligent breeding behavior of cuckoos has been reported in [15]. CSA needs less number of parameters to be tuned as compared to GA and PSO and widely used as an optimization tool for solving complex, nonlinear and non-convex optimization problems [16]. CSA has been applied to locate and sizing distributed generators [17], to solve non-convex economic dispatch problem [18] and to capacitor

placement on distribution problem [19]. Allocation of static shunt capacitors in radial distribution networks with the objective of minimization of operating cost and improvement in voltage profile is adopted in [20]. In [17–20], the CSA has been used to solve the static power flow problem. But more recently, CSA is reported in time domain to robustly tune the gains of PI controller LFC controller for interconnected three-area power system considering system non-linearity [21]. The literature survey in the area of voltage and frequency control issues with hybrid wind-diesel system shows that transient performance has been improved by tuning the gain of SVC or STATCOM controller with ISE criteria. So far no Evolutionary Optimization Algorithms has been applied to enhance the dynamic performance of hybrid system under different wind speed changes or varying active/reactive power demand. Also, coordinated control of voltage and frequency control loop has not been addressed yet for isolated hybrid power system. Hence, an attempt is made to develop a mathematical model of isolated hybrid wind-diesel system with the coordinated control of voltage and frequency loop and optimized its transient performance by tuning the gains of controller with the help of Cuckoo Search Algorithm.

2. Coordinated control of frequency and voltage for wind-diesel isolated test system Fig. 1 shows the schematic of isolated hybrid power system where the active and reactive power loads are supplied locally by hybrid power generating system. The hybrid power generating system consists of conventional diesel generators and renewable wind power generators. The diesel generating system employs synchronous generator whereas wind power generation has fixed speed squirrel cage induction generator (SQIG). In normal conditions, voltage and frequency are controlled with the precise control of active and reactive power generation, respectively. In isolated power system with wind and diesel power generating units, the frequency control becomes very sensitive as the system has low inertia. Also, the wind power generating units cannot participate to compensate the increased load demand as its active power output depends on the available wind velocity. Similarly, the voltage control is also very difficult as the fixed speed SQIG acts as sink for the reactive power in addition to the reactive power demand

V ∠δ

Pig

Wind Gear Box

Induction Generator Qig

Turbine Blades

PL LOAD SVC QSVC

QL

Psg Fuel

Synchronous Generator Qsg

Fig. 1. Schematic of isolated hybrid power system.

Please cite this article in press as: Mehta P et al. Optimized coordinated control of frequency and voltage for distributed generating system using Cuckoo Search Algorithm. Ain Shams Eng J (2017), http://dx.doi.org/10.1016/j.asej.2016.08.019

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of the system. Hence, the sole contribution of reactive power from the synchronous generator will not be sufficient to cater the increasing reactive power demand of load as well as SQIG both and under such circumstances the voltage may have severe voltage fluctuations. In order to prevent larger voltage fluctuations, static var compensators (SVC) has been considered at the point of common coupling as shown in Fig. 1 to compensate the unbalanced reactive power demand in the system. It is well known that small unbalance between active power generation and load causes frequency deviations whereas small unbalance between reactive power generation and load causes voltage deviations. The excitation system on synchronous generator with smaller time constant acts much faster as compared to the slower governor and prime

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mover control. Hence, the effect of excitation control loop for voltage control is generally neglected over the load frequency control (LFC) dynamic [6,22]. In [8], the beneficial effect of excitation loop has been revealed for the effective control of frequency. However, the study was carried out for SMIB system with the consideration of four large synchronous generators supplying power to the infinite bus through the long transmission line. In this work, the effect of frequency control loop and voltage control loop over each other has been comprehensively studied for isolated wind-diesel system. Fig. 2 shows the block diagram representations of isolated wind-diesel power system where the frequency control loop and voltage control loop are integrated together. The constants in the voltage control loop are taken from [6] and are also given in

Fig. 2. Block diagram representation of isolated wind-diesel power system.

Please cite this article in press as: Mehta P et al. Optimized coordinated control of frequency and voltage for distributed generating system using Cuckoo Search Algorithm. Ain Shams Eng J (2017), http://dx.doi.org/10.1016/j.asej.2016.08.019

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P. Mehta et al. / Ain Shams Engineering Journal xxx (2017) xxx–xxx

Fig. 3. SVC Type 1, Type 2 and Type 3 for small signal analysis.

Appendix A. The impact of frequency change has been considered in the flux linkage and the reactive power equations of synchronous generator and they are modified as follow. Under transient condition, QSG is given by [6].

Eq ¼ ðX d =X 0d ÞE0q  ðX d  X 0d Þ=X 0d V cos d

Q SG ¼ ðE0q V cos d  V 2 Þ=X 0d

where DEq = change in internal armature emf proportional to change in direct axis field flux under steady state condition. For round rotor synchronous machine, flux linkage equation of the for small perturbation is given as

ð1Þ

For small perturbation, (1) can be written as

DQ SG ¼

! !
 E0q cos d  2V E0q V sin d V cos d 0 D E þ D V  Dd q X 0d X 0d X 0d

ð2Þ

where DE0q = deviation in the internal armature emf proportional to the change in the direct axis field flux under transient condition, DV = deviation in terminal voltage and Dd = deviation in power angle of synchronous generator. Laplace transform of both sides for (1) results in

DQ SG ðsÞ ¼ K 1 DE0q ðsÞ þ K 2 DVðsÞ  K d Dd where

K 1 ¼ V cos d=X 0d ,

K 2 ¼ ðE0q cos d  2VÞ=X 0d

ð3Þ and

K d ¼ E0q V sin d=X 0d The internal armature emf for round rotor synchronous machine is given by (4) and its change with small perturbation is given in (5). Table 1 Steps for CSA. Step 1: Step 2: Step 3: Step 4:

Generate the initial solutions (nests) randomly Evaluate the fitness of nest among initially generated nest and find the best of them Start the iteration Generate new solutions (nest) by Levy flights  1=b b=2Þ Lev y ðbÞ ¼ Cð1þbÞ sinðpðb1Þ=2 C½ð1þbÞ=2b 2

Step size of walks/flights needs to be controlled, otherwise, Levy flights may become too aggressive /efficient, which makes new solutions jump out side of the design domain. The step size is

DEq ¼

ð4Þ


     Xd X d  X 0d X d  X 0d 0 cos d DV þ V sin dDd 0 DE q  0 0 Xd Xd Xd

d=dtðDE0q Þ ¼ ðDEfd  DEq Þ=T 0do T 0do

ð5Þ

ð6Þ

= direct axis open circuit transient time constant

DE0q ðsÞ ¼

1 ½K 1 DEfd ðsÞ þ K 2 DVðsÞ  K d DdðsÞ 1 þ sT G

ð7Þ

where

T G ¼ X 0d T 0do =X d K 1 ¼ X 0d =X d K 6 ¼ ðX d  X 0d =X d Þ  cos d K d ¼ ðX d  X 0d =X d Þ  V sin d 3. State space representation of test system and formulation of objective function For the system shown in Fig. 2, the state equations in a standard form can be written as (8). The state, input and disturbance vectors for the system without and with coordinated control are given in (9) and (10), respectively.

x_ ¼ Ax þ Bu þ C C

ð8Þ

computed as follow using Mantegna’s algorithm. s ¼ u=jv j1=b , u and v are generated randomly and b = 1.5. Step 5: Step 6:

Step 7: Step 8:

Evaluate the fitness of newly generated nests using (11) and (12) and find the best nest among them. Discover a fraction of worse nests with a probability P a ; replace them and construct new solutions/nests; In real world, if a cuckoo’s egg is very similar to a host’s eggs, then this cuckoo’s egg is less likely to be discovered, thus the fitness should be related to the difference in solutions. Therefore, it is a good idea to do a random walk in a biased way with some random step sizes. Find the best nest again by evaluating the fitness using (11) and (12) and keep it for the next iteration. Go to Step 4 and Repeat the steps until the max iteration.

Table 2 Optimized parameters obtained with CSA Gains of PI controller in frequency loop

Gains of SVC in voltage control loop SVC Type I

SVC Type II

SVC Type III

K DP ¼ 275:12 K DI ¼ 15

K R ¼ 620 T R ¼ 0:05

K R ¼ 6500 T 1 ¼ T 2 ¼ 1:15 s

K Psv c ¼ 575 K Isv c ¼ 23500

K DP ¼ 200:45 K DI ¼ 15

T3 ¼ T4 ¼ 4 s K DP ¼ 195 K DI ¼ 15

K DP ¼ 194:88 K DI ¼ 15:34

Please cite this article in press as: Mehta P et al. Optimized coordinated control of frequency and voltage for distributed generating system using Cuckoo Search Algorithm. Ain Shams Eng J (2017), http://dx.doi.org/10.1016/j.asej.2016.08.019

P. Mehta et al. / Ain Shams Engineering Journal xxx (2017) xxx–xxx T x_ ¼ ½Df Dd DPI DLL DT D3 DP GD DF TS 

u ¼ ½DPref 

ð9Þ

C ¼ ½DPL DPIW T 

DEfd DV a DV f DE0q Bsv c B0sv c Da DV . . . . . . . . . . . . Df Dd DPI DLL DT D3 DP GD DF TS u ¼ ½DV ref DP ref 

T

x¼

ð10Þ

C ¼ ½DQ L DPL DPIW T In (10), the state vector x is represented for the SVC type 1 which gets modified for another two types of SVC shown in Fig. 3. The time domain responses for the system shown in Fig. 2 have been obtained with the application of different types of disturbances. The objectives are to control the frequency and voltage deviations of the system after having been subjected to any active and reactive power load demand changes. The optimized transient responses for frequency and voltage deviations are obtained by optimizing the gains of PI controller in the load frequency control loop and gains of SVC. In order to have minimum undershoot (US),

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overshoot (OS) and settling time (ts) in the transient responses of frequency and voltage deviations, the objective function defined as Figure of Demerit (FDM) in (11) and (12) are minimized with the use of recently reported Cuckoo-Search Algorithm (CSA) [18– 21]. The set of optimized parameters vary according to the type of SVC consideration and they are ½K DP K DI K R T R , ½K DP K DI K R T 1 T 2 T 3 T 4  and ½K DP K DI K Psv c K Isv c  with SVC type 1, type 2 and type 3, respectively. The objective functions to be minimized are defined in different ways in (11) and (12) for the system given in (9) and (10), respectively.

FDM ¼

N X ½Df ðnÞ2  Dt

ð11Þ

n¼0

FDM ¼

N X ½Df ðnÞ2 þ DVðnÞ2 Dt

ð12Þ

n¼0

where Df and DV are deviations in frequency and voltage, respectively. N is the total number of samples for frequency and voltage responses and Dt is the time interval between two samples.

Fig. 4. Transient responses of frequency deviations and generated powers considering only frequency control loop.

Fig. 5. Comparative transient responses of frequency deviations and generated powers considering coordinated control of frequency and voltage control loops (SVC – Type 3).

Please cite this article in press as: Mehta P et al. Optimized coordinated control of frequency and voltage for distributed generating system using Cuckoo Search Algorithm. Ain Shams Eng J (2017), http://dx.doi.org/10.1016/j.asej.2016.08.019

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active power as to compensate the increased active power demand. In this work, an attempt is made to explore the impact of voltage control obtained from the fast acting excitation control of synchronous generating unit and SVC placed at the terminal of wind power generating unit on frequency control. Following case studies have been presented in order to establish the beneficial impact of integrating voltage control for frequency control.

4. Cuckoo-Search Algorithm for minimizing FDM Cuckoo Search (CS) algorithm is an optimization algorithm introduced by Yang and Deb [15,16] which is based on obligate brood parasitism of some cuckoo species. Cuckoos lay their eggs in the nests of other host birds which may have direct conflict with the intruding cuckoos. When a host birds realize that the eggs are not their own, it will either throw these alien eggs away or simply abandon its nest and build a new nest elsewhere. Each egg in a nest represents a solution and a cuckoo egg represents a new solution. The aim is to use the new and potentially better solutions to replace a not-so-good solution in the nests. The parameters used for the CSA and procedure to follow for the solution is given in Table 1.

5.1. Case 1: The test system is considered with only frequency control loop For this case, the coordinated control of frequency and voltage control loop is ignored in Fig. 2. The active power load perturbation of 1% is applied at t = 0.0 Sec. The gains of the PI controller employed in frequency control loop are optimized with the help of recently reported Cuckoo Search Algorithm and listed in Table 2. The transient responses of frequency deviation and active power generations of wind and diesel generating units are shown in Fig. 4. It can be observed that the frequency drops down to 0.21 Hz upon application of active power load perturbation of 1%. The increments in active power generation from the two generat-

5. Simulation results and discussion The objective of the work is to obtain optimized frequency control of isolated hybrid power system shown in Fig. 1.The linearized model of diesel and wind power generating units is presented in Fig. 2 to study its frequency and voltage control problem. The diesel and wind power generating units will generate proportionate

-5

-3

x 10

6 Delta QSG (pu)

2

Delta V (pu)

SVC 1

1

SVC 2 SVC 3

0

-1

0

1

2

3

4

4

2

0

5

x 10

0

1

2

Time (s) -6

5

2 1 0 -1

4

5

-3

x 10

Delta Qsvc (pu)

Delta QIG (pu)

3

3 Time (s)

0

1

2

3

4

0 -5 -10 -15

5

x 10

0

1

2

Time (s)

3

4

5

Time (s)

Fig. 6. Comparative transient responses of terminal voltage deviation and generated reactive powers considering coordinated control of frequency and voltage control loops with three types of SVCs.

-4

-4

2

x 10

4

x 10

Only f Control

Delta Pg SG (pu)

with v and f Control

Delta f (pu)

1

0

-1

-2

2

0

-2

0

5

10 Time(s)

15

-4

0

5

10

15

Time(s)

Fig. 7. Transient responses of frequency deviations and generated powers considering coordinated control of frequency and voltage control loops against random load change (SVC – Type 3).

Please cite this article in press as: Mehta P et al. Optimized coordinated control of frequency and voltage for distributed generating system using Cuckoo Search Algorithm. Ain Shams Eng J (2017), http://dx.doi.org/10.1016/j.asej.2016.08.019

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x 10

-3

10

Delta QSG (pu)

Delta V (pu)

1

0 SVC 1

-1

SVC 2 SVC 3

-2

0

0.02

0.04

0.06

-3

5

0

-5

0.08

x 10

0

0.02

Time(s) x 10

0.08

0.06

0.08

0.06

1 0 -1 -2

0.06

-4

Delta QSVC(pu)

Delta QIG(pu)

2

0.04

Time(s)

0

0.02

0.04

0.06

0.08

Time(s)

0.04 0.02 0 -0.02

0

0.02

0.04

Time(s)

Fig. 8. Comparative transient responses of terminal voltage deviation and generated reactive powers considering coordinated control of frequency and voltage control loops with three types of SVCs – reactive load perturbation.

-8

20

SVC 1 SVC 2 SVC 3

15

Delta f (pu)

DPm;IG = Increment in generated power of wind generating unit, DPe = Increment in electromagnetic power of synchronous generating unit, DPL = Increment in active power load demand.

x 10

10 5 0 -5

0

2

4

6

8

10

12

14

16

18

20

Time (Sec) Fig. 9. Comparative transient responses of frequency deviation with reactive load perturbation.

ing units restrict the further frequency decline. The gains of PI controller in frequency control loop are optimized by minimizing the objective function given in (11). The action of PI controller eliminates the steady state error in the frequency deviation and active power generation exactly increases to 0.01 pu to compensate the 1% step load perturbation. The SQIG does not generate any active power in steady state as the wind speed is assumed to be constant. 5.2. Case 2: The test system is considered with coordinated frequency and voltage control loops For this case, the action of the voltage control loop is integrated with frequency control loop as shown in Fig. 2.The integration of voltage control loop changes the active power generation of synchronous generating unit as per (13).

DPm;SG þ DPm;IG þ DPe ¼ DPL DPe ¼ Ps Dd þ KE;V DE0q

ð13Þ

where DPm;SG = Increment in generated power of synchronous generating unit,

The comparative transient responses of frequency deviations with coordinated control of voltage and frequency loop are depicted in Fig. 5. The beneficial impact of coordinating the voltage control loop with the frequency control loop can be clearly observed. The coordinated control can successfully reduce the undershoot in frequency deviation as well as results in the faster settling time. The ramp in power generation for synchronous generator is higher in order to support active power generation faster and to restrict the frequency decline. The wind power generation transiently supports for frequency control and finally settles to original position under steady state conditions. Upon application of step load perturbation of active power load, the terminal voltage also gets deviated. The deviation in the terminal voltage has been compensated with the additional reactive power generation by synchronous generator and SVC and clearly noticed from Fig. 6. The SVC type 3 results in the minimum voltage deviation and successfully removes the steady state error in voltage deviation with the integral controller actions. Another two types of SVC left with small steady state error in voltage deviation and gives comparatively slower to suppress the voltage deviation. The test system is subjected to random load change as given in (14). The dynamic responses for frequency and generated power are shown in Fig. 7 after having been subjected to random active load disturbance which also proves the effectiveness of coordinated control of frequency and voltage loops.

DPL ¼ 0:003 sinð4:36 tÞ þ 0:005 sinð5:3 tÞ  0:01 sinð6 tÞ

ð14Þ

5.3. Case 3: The system is considered with coordinated frequency and voltage control loops: Reactive load perturbation The reactive load perturbation produces larger voltage deviation which needs immediate reactive power support. The capabil-

Please cite this article in press as: Mehta P et al. Optimized coordinated control of frequency and voltage for distributed generating system using Cuckoo Search Algorithm. Ain Shams Eng J (2017), http://dx.doi.org/10.1016/j.asej.2016.08.019

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ities of different types of SVCs to provide reactive power support are compared in Fig. 8. SVC type 2 and 3 represents better dynamic response in terms of faster settling time. SVC type 1 able to prevent undershoots in voltage deviation but takes longer time to suppress the oscillations. Compared to Fig. 6, the terminal voltage deviations and reactive power generations are higher in Fig. 8 when the system is subjected to reactive load perturbation. Moreover, reactive power generation by synchronous generator and induction generator finally attains its original position in steady state and required reactive power support is provided by SVCs only. The frequency deviation is very small with the reactive load perturbation as can be seen from Fig. 9. It indicates that the change in reactive load negligibly affect the frequency deviation. The frequency deviation takes the longest time to settle for SVC type 1 as compared to other two types. 6. Conclusion The linearized model of isolated hybrid power system consists of synchronous generator and fixed speed induction generator is presented for controlling frequency and voltage deviations after the load perturbations. The fast acting voltage control loop of excitation system of synchronous generator is integrated with slower frequency control loop and the state space model for this coordinated system is developed. The performance of the proposed coordinated system is validated for different active and reactive power load disturbances in form of step and random variations. It is seen that the coordinated control of these two loops has restricted the further frequency deviations and resulted in optimal dynamic performance under all kinds of load perturbations. Drawing of reactive power by IG from grid imposes serious concern for maintaining nominal voltage, hence, the performance of different types of SVCs have been evaluated to quickly compensate the voltage deviations. The presence of the different types of SVC is also included while developing the state space model of isolated hybrid power system. The SVC with PI controller structure gives the best responses in comparison to other two types of SVCs and it effectively suppress the oscillations in terminal voltage as well as reduce the reactive power requirement of IG in transient conditions. The gains of the controller employed in LFC loop of synchronous generator and SVC installed at the terminal of IG have been optimized with the help of CSA to yield the optimal dynamic response after the disturbance. Appendix A

Table A.1 Parameters for the test system. K1 K2 K3 K4 K5 K8 K9

¼ 0:15 ¼ 0:7932 ¼ 6:22143 ¼ 7:35 ¼ 0:126 ¼ 1:478 ¼1

T FF ¼ 0:715 T E ¼ 0:55 s K E ¼ 1:0 K A ¼ 40:0 T A ¼ 0:05 K a ¼ 0:4464 T a ¼ 0:02=4 s

T d ¼ 0:02=12 s K V ¼ 0:6667 T V ¼ 0:000106 K F ¼ 0:5 T G ¼ 0:75

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Please cite this article in press as: Mehta P et al. Optimized coordinated control of frequency and voltage for distributed generating system using Cuckoo Search Algorithm. Ain Shams Eng J (2017), http://dx.doi.org/10.1016/j.asej.2016.08.019

P. Mehta et al. / Ain Shams Engineering Journal xxx (2017) xxx–xxx Pankita Mehta did her Bachelor of Engineering in Electrical Engineering from Saurastra University, India in 2003. She completed her Master of Engineering in Electrical Engineering with specialization in Electrical Power System from Sardar Patel University, India in 2006. She is presently pursing her PhD from Charotar University of Science and Technology, Changa, India. She has more than 10 years of teaching experience at undergraduate and post graduate level and has successfully guided several UG and PG projects. Her research area of interest includes Distributed Generation, Smart Grid, Frequency Control, Voltage Stability and Electrical Machines. She is a member of IEEE, Indian Society of Technical Education (ISTE) and Society of Power.

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Dr. Vivek J. Pandya has earned his B.E. (Electrical Engineering, Sardar Patel University), 1995, M.E. (Electrical Power Systems, Sardar Patel University), 2003, Ph. D. (Power System Protection (Electrical Engineering), Maharaja Sayajirao University, Vadodara, India. His areas of interests are Electrical Machines, Electrical power system and Power system protection. He had published several papers in reputed journals and conferences. Currently he is working as Associate Professor at PDPU, School of Technology, Raysan, India.

Dr. Praghnesh Bhatt did his PhD from S V National Institute of Technology, Surat, India in 2012. He is working as Professor and Head in Department of Electrical Engineering at C S Patel Institute of Technology, Charusat, India. He has more than 15 years of teaching experience both at undergraduate and post-graduate level in Electrical Engineering. He is a member of IEEE, IEEE Power and Energy Society, Indian Society of Technical Education (ISTE) and Society of Power. He has published several research papers in reputed international journals. His main areas of interests are Power System Analysis, Power system Dynamics and Stability, Grid integration of renewable energy sources, Power System Protection, Distributed Generation and Smart Grid.

Please cite this article in press as: Mehta P et al. Optimized coordinated control of frequency and voltage for distributed generating system using Cuckoo Search Algorithm. Ain Shams Eng J (2017), http://dx.doi.org/10.1016/j.asej.2016.08.019

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P. Mehta et al. / Ain Shams Engineering Journal xxx (2017) xxx–xxx

Please cite this article in press as: Mehta P et al. Optimized coordinated control of frequency and voltage for distributed generating system using Cuckoo Search Algorithm. Ain Shams Eng J (2017), http://dx.doi.org/10.1016/j.asej.2016.08.019