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DISTRIBUTED POWER FLOW CONTROLLER FOR DAMPING OF POWER SYSTEM OSCILLATIONS
Sneha Anand Jamboti
1, Prof. A. Shravan Kumar
2, Prasad Pradeep Kulkarni
31
PG Student, Department of Electrical Engineering, Fabtech College of Engineering and Research, Sangola, (India)
2
Guide, Department of Electrical Engineering,
Fabtech College of Engineering and Research, Sangola, (India)
3
Assistant Professor, Department of Electrical Engineering, Sanjeevan Engineering Technology & Institute, (India) ABSTRACT
This project proposes a new control scheme to improve the stability of a system by optimal design of distributed power flow controller (DPFC) based stabilizer. The purpose of the work is to design an oscillation damping controller for DPFC to damp low frequency electromechanical oscillations. The optimal design problem is formulated as an optimization problem, and particle swarm optimization (PSO) is employed to search for the damping controller parameters. As the DPFC inherits all the advantages of UPFC and DFACTS, which are as follows: The total cost of the DPFC is also much lower than the UPFC, because no high-voltage isolation is required at the series-converter part and the rating of the components of is low. The shunt and series converters in the DPFC can exchange active power at the third-harmonic frequency, and the series converters are able to inject controllable active and reactive power at the fundamental frequency. The proposed system is simulated by using MATLAB/SIMULINK.
Keywords- DPFC, FACTS, PSO, UPFC
I INTRODUCTION
With increasing demand of power and the extension of transmission as well as the aging of networks leads to an increased need for power flow control in power system fast and reliability. Flexible Alternating Current Transmission Systems (FACTS) devices have been proposed to be effective for controlling power flow and regulating bus voltage in electrical power systems, resulting in an increased transfer capability, low system losses and improved stability. A FACTS incorporates power electronics and controllers to enhance power system controllability and increase transfer capability. FACTS devices improve power system operation and stability, and to
379 | P a g e better utilize the existing transmission infrastructure by controlling power flow. In this paper, a distributed power flow controller is introduced as a new FACTS (flexible alternating-current transmission system) device.
The DPFC (Distributed power flow controller) structure is derived from the UPFC (Unified power flow controller) structure that is included one shunt converter and several small independent series converters. The DPFC is obtained by eliminating the common DC link between the shunt and series converters, the DPFC employs multiple single phase converters (distributed-FACTS concept) as the series compensator, instead of one large three-phase converter, as shown in Fig.1.
Fig.1. Development of DPFC from UPFC
1.1 Concept of DPFC
1.1.1 DPFC MODULE
The DPFC consists of one shunt converter and several series connected converter. The shunt converter is similar to STATCOM where as the series converter employs the concept of D-FACTS (Distributed FACTS). DPFC same as the UPFC, is able to control all system parameters like line impedance, transmission angle and bus voltage. The DPFC eliminates the common dc link between the shunt and series converters. The active power exchange between the shunt and the series converter is through the transmission line at the third-harmonic frequency as shown in Fig.2.
380 | P a g e Fig.2 Active power exchange between DPFC converters
1.1.2. DPFC current injection model
As the installation of DPFC changes the system bus admittance matrix Ybus to an unsymmetrical matrix, the modification of Ybus is required at each stage. For this reason, a current injection model of DPFC is developed to avoid using the modification of Ybus at each stage and to study the effects of it on low frequency oscillations. By using equivalent injected currents at terminal buses to simulate a DPFC, no modification of Ybus is required at each stage.The synchronous generator in Fig.3 is delivering power to the infinite bus through a double circuit transmission line and a DPFC.
Fig.3. Power system with DPFC
Fig.4 shows the equivalent circuit of DPFC converters in the test power system. The idea of the current injection model is to use current sources, which are connected as shunt, instead of the series voltage sources. The test power system in this paper includes two parallel transmission lines, and series converters are distributed in lines at different distances. In Fig.4, the shunt converter current, Ishunt, can be written as:
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shunt = t + q (1)
Where t is in phase with i and q is in quadrature to i . The voltage sources s1 , s2, s1, s2 have been replaced in-stead of series converters. The Xs1, Xs2, X’s1, X’s2 are reactance of transmission lines. The magnitudes and phase angle of series converters are controllable. In this paper we assume that they have same value. Therefore we have: s1 = s2 = s1 = s2 = iejλ (2)
where 0 < r < rrmax and 0 < λ < 2p. The r and λ are relative magnitude and phase angle respect to Vi, respectively. The injection model is obtained by replacing the voltage sources with the current sources as shown in Fig. 5 and we have : s1= = -jbs1 iejλ (3)
s2= = -jbs2 iejλ (4)
s1= = -jb′s1 iejλ (5)
s2= = -jb′s2 iejλ (6)
Where bs1= s1 , bs2= s2, b′s1 = s1 ,b′s2= s1 The active power supplied by the shunt current source can be calculated as follows: Pshunt = Re[ i(-*shunt)] = -ViIt (7)
Fig.4 Electrical circuits in DPFC converts of case study Fig.5 Representation of series source by transformation system shunt source With the neglected DPFC losses we have: Pshunt = Pseires =Ps1+ Ps2 +P′s1 +P′s2 (8)
The apparent power supplied by the series converter Vs1 can be calculated as: Ss1 = s1 *ij = r iejλ [ ]* = r iejλ [ ]* (9)
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Ss1 =Ps1 + jQs1 (10)
From (9) and (10) the exchanged active and reactive power by converter V0s1 is distinguished as: Ps1 = (bs1 + bs2)[rViVjsin(θi – θj + λ) – rV2isin(λ)] (11)
Qs1 = (bs1 + bs2)[ rV2icos(λ) + 2r2V2i - rViVjcos(θi – θj + λ)] (12)
With attention the above equations, the exchanged active and reactive power by converters Vs2; V0s1 and V0s2 are calculated as: Ps2 = (bs1 + bs2)[rViVjsin(θi – θj + λ) – rV2isin(λ)] (13)
Qs1 = (bs1 + bs2)[ rV2icos(λ) + 2r2V2i - rViVjcos(θi – θj + λ)] (14)
P′s1 = (b′s1 + b′s2)[rViVjsin(θi – θj + λ) – rV2isin(λ)] (15)
Q′s1 = (b′s1 + b′s2)[ rV2icos(λ) + 2r2V2i - rViVjcos(θi – θj + λ)] (16)
P′s2 = (b′s1 + b′s2) [rViVjsin (θi – θj + λ) – rV2isin (λ)] (17)
Q′s2 = (b′s1 + b′s2) [rV2icos (λ) + 2r2V2i - rViVjcos (θi – θj + λ)] (18)
Substitution of (7), (11), (13), (15) and (17) into (8) gives: It = 2(bs1 + bs2) [-rVjsin (θi – θj + λ) + rVisin (λ)] + 2(b′s1 + b′s2) [-rVjsin (θi – θj + λ) + rVisin (λ)] (19)
Finally, the shunt converter current can be obtained as: shunt = t + q =( It +jIq)ejθi = (2(bs1 + bs2) [-rVjsin (θi – θj + λ) + rVisin (λ)] + 2(b′s1 + b′s2) [-rVjsin (θi – θj + λ) + rVisin (λ)] ejθi (20)
q = jBq i (21)
Bq is the equivalent susceptance used to control Iq. Thus, the current injection model of DPFC is obtained as follows: i = shunt - s1 - s1 (22)
j1 = s1 - s2 (23)
j2 = s2 (24)
j1 = s1 - s2 (25)
j2 = s2 (26)
Substituting (4), (5), (6), (7) and (21) into (22)–(26) gives the current injection model parameters as follows: i = {2(bs1 + bs2)[ -rVjsin(θi – θj + λ) + rVisin (λ)] +2(b′s1 + b′s2)( -rVjsin(θi – θj + λ) + rVisin (λ)) + jIq }ejθi + jbs1r iejλ (27)
j1 = -jbs1r iejλ + jbs2 r iejλ (28)
j2 = - jbs2 r iejλ (29)
j1 = -jb′s1r iejλ + jb′s2 r iejλ (30)
383 | P a g e j2 = - jb′s2 r iejλ (31)
II DAMPING CONTROLLER BASED ON DPFC
To design the damping torque the control parameters of DPFC (r, λ, and Bq) are modulated. In this paper r and λ are modulated in order to design of the damping controller. The speed deviation is considered as the input to the controller. The structure of DPFC based damping controller is shown in Fig.6. The parameters of the damping controller are obtained using PSO algorithm.
Fig.6. DPFC module with lead lag controller
2.1 DPFC damping controller design by PSO technique
The designed controller with proposed model is tuned to damp power system oscillations with minimum control effort following a disturbance. An Integral of Time multiplied Absolute value of the Error is considered as the fitness function, in this study. The objective function is given by:
= ωi)dt (32) (33)
In Eqs. (32) and (33), tsim is the time range of simulation, and Np is the total number of operating points for which the optimization is carried out. The design problem can be formulated as the following constrained optimization problem, where the constraints are the controller parameters bounds:
Minimize J subject to:
Kmin K Kmax
T1min T1 T1max (34) T2min T2 T2max
T3min T3 T3max T4min T4 T4max
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2.2. Nonlinear time-domain simulation
The MATLAB/Simulink is used to evaluate the proposed control scheme for DPFC. The details of simulation model are depicted in Fig.7. The parameters of machine (like nominal voltage and power, impedance and phase angle of sending and receiving ends) under test are listed, in Table 1. The simulation study is carried out for three scenarios occurred as below:
Table 1. Parameters of test power system
Sl.No. Parameters Value
1 Es (KV) 230
2 Er (KV) 230
3 F (Hz) 60
4 S (MVA) 900
5 Deg 10
6 Deg 0
7 Line Length (Km) 220
Fig. 7. MATLAB/ Simulation model with DPFC
2.2.1. Scenario 1
In this case, a 6-cycle three-phase fault is occurred at t= 1 s at the middle of one transmission line cleared by permanent tripping of the faulted line is considered. Fig.8 shows the speed deviation of generator at various loading conditions (nominal, light, and heavy) produced due to designed controller for λ and r by PSO algorithm .The generator output power, internal voltage variations, and excitation voltage deviation for nominal load condition are shown in Fig.9.
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Fig.8 (a) Fig.8 (b)
Fig.8 (c)
Fig.8 Dynamic response of speed deviation for scenario 1(a) Nominal Load (b) Light Load (c) Heavy Load
Fig.9 (a) Fig.9 (b)
386 | P a g e Fig.9 (c)
Fig.9 Dynamic responses at nominal load (a) Generator output (b) Terminal Voltage Deviation (c) Excitation Voltage Deviation
2.2.2. Scenario 2
In this case, a 6-cycle three-phase fault is occurred at t= 1s at the middle of one of the transmission line is considered. The fault is cleared without line tripping, and the original system is restored upon the clearance of the fault. Fig.10 shows the dynamic response to this disturbance. It can be seen that the proposed model based optimized DPFC damping controller has good performance in damping low frequency oscillations and stabilizes the system quickly.
Fig.10 (a) Fig.10 (b)
Fig.10 (c)
Fig.10 Dynamic response of speed deviation for scenario 2 (a) Nominal Load (b) Light Load (c) Heavy Load
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2.2.3. Scenario 3
In this case, a 6-cycle signal-phase fault is occurred at t =1 s at the middle of one of the transmission line is considered. The fault is cleared without line tripping, and the original system is restored upon the clearance of the fault. Fig.11 shows the speed deviation of generator at base nominal loading condition with control parameters λ and r for both PSO and GA damping controller. The dynamic response for PSO method is compared with GA method. it can b show that the performance of the PSO based damping controller is quite prominent than the GA based
damping controller. The proposed controller also shows that overshoots and settling time are significantly improved.
Fig.11 (a) Fig.11 (b)
Fig. 11 Dynamic response of speed deviation for scenario 3 at nominal load condition for both PSO & GA damping controller (a) For λ parameter (b) For r parameter
III CONCLUSION
In this work the mathematical analysis and current injection modeling of a new FACTS device based on distributed power flow controller are presented. PSO technique is used to design the DPFC by converting the damping controller parameters into an optimization problem. It is proved that the shunt and series converters in the DPFC can exchange active power at the third-harmonic frequency. The results have shown that the proposed model can effectively damp power system oscillations following large disturbances and has good performance in damping low frequency oscillations and stabilizes the system quickly. From the above conducted tests, it can be concluded that the λ based damping controller is superior to the r based damping controller tuned by PSO algorithm. It can be seen that the system response with the PSO based damping controller settles faster and provides superior damping. The results demonstrate that DPFC with the proposed model can more effectively improve the dynamic stability and enhance the transient stability of power system compared to the genetic algorithm based damping controllers. The r and λ are relative magnitude and phase angle of DPFC controller. Moreover, the results show that the λ based controller is superior to the r based controller.
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REFERENCES
[1] Amin Safari , Behrouz Soulat , Ali Ajami . Modeling and unified tuning of distributed power flow controller for damping of power system oscillations, Ain Shams Engineering Journal (2013)
[2] Shayeghi H, Shayanfar HA, Jalilzadeh S, Safari A. A PSO based unified power flow controller for damping of power system oscillations. Energy Convers Manage 2009;50:2583–92.
[3] Anderson PM, Fouad AA. Power system control and stability. Ames, IA: Iowa State Univ Press; 1977.
[4] Hingorani JNG, Gyugyi L. Understanding FACTS: concepts and technology of flexible AC transmission systems. New York: IEEE Press; 2000.
[5] Keri AJF, Lombard X, Edris AA. Unified power flow controller: modeling and analysis. IEEE Trans Power Deliver 1999;14(2):648–54.
[6] Yuan Z, de Haan SWH, Ferreira B. A new facts component: distributed power flow controller (DPFC). In: Eur conf power electron appl; 2007. p. 1–4.
[7] Yuan Z, de Haan SWH, Ferreira B. A FACTS device: distributed power flow controller (DPFC). IEEE Trans Power Deliver 2010;25(2):2564–72.
[8] Gyugyi L, Schauder CD, Williams SL, Rietman TR, Torgersonand DR, Edris A. The unified power flow controller: a new approach to power transmission control. IEEE Trans Power Deliver 1995;10(2):1085–97.
[9] Zhihui Y, de Haan SWH, Ferreira B. Utilizing distributed power flow controller for power oscillation damping.
In: Proc IEEE power energy soc gen meet (PES); 2009. p. 1–5.
[10] So PL, Chu YC, Yu T. Coordinated control of TCSC and SVC for system damping. Int J Control, Autom, Syst 2005;3(2):322–33 (special edition).
[11] Sadikovic R. Damping controller design for power system oscillations, Internal report, Zurich; 2004.
