ACEEE Int. J. on Electrical and Power Engineering, Vol. 03, No. 02, May 2012 A CHS based PID Controller for Unified Power ...
ACEEE Int. J. on Electrical and Power Engineering, Vol. 03, No. 02, May 2012Where:PAR       pitch adjusting rate for each ...
ACEEE Int. J. on Electrical and Power Engineering, Vol. 03, No. 02, May 2012                                              ...
ACEEE Int. J. on Electrical and Power Engineering, Vol. 03, No. 02, May 2012                               T ABLE II .    ...
ACEEE Int. J. on Electrical and Power Engineering, Vol. 03, No. 02, May 2012                         CONCLUSIONS          ...
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A CHS based PID Controller for Unified Power Flow Controller

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This paper presents a method for designing of
proportional-integral-derivative (PID) controller based on
unified power flow controller (UPFC) using chaotic harmony
search algorithm (CHS) for damping of low frequency
oscillations (LFO) in a power system. The main aim of this
paper, optimization of selected gains with the time domainbased
objective function which is solved by chaotic harmony
search algorithm. The performance of the proposed singlemachine
infinite-bus system (SMIB) equipped with UPFC
controller- based PID controller is evaluated under various
disturbances and operating conditions. The effectiveness of
the proposed UPFC controller based on PID controller to damp
out of oscillations over a wide range of operating conditions
and variation of system parameters is showed in simulation
results and eigenvalue analysis.

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A CHS based PID Controller for Unified Power Flow Controller

  1. 1. ACEEE Int. J. on Electrical and Power Engineering, Vol. 03, No. 02, May 2012 A CHS based PID Controller for Unified Power Flow Controller S.Jalilzadeh, R.Noroozian, M.Bakhshi Department of Electrical Engineering, Faculty of Engineering, University of Zanjan, Zanjan, Iran jalilzadeh@znu.ac.ir, noroozian@znu.ac.ir,bakhshi.mohsen@gmail.comAbstract-This paper presents a method for designing of II. CHAOTIC HARMONY SEARCH ALGORITHMproportional-integral-derivative (PID) controller based onunified power flow controller (UPFC) using chaotic harmony This section describes the proposed chaotic harmonysearch algorithm (CHS) for damping of low frequency search (CHS) algorithm. First, a brief overview of the IHS isoscillations (LFO) in a power system. The main aim of this provided, and finally the modification procedures of thepaper, optimization of selected gains with the time domain- proposed CHS algorithm are stated.based objective function which is solved by chaotic harmonysearch algorithm. The performance of the proposed single- A. Improved Harmony Search Algorithmmachine infinite-bus system (SMIB) equipped with UPFC Fundamental of this method is based on the concept incontroller- based PID controller is evaluated under various search of a suitable state in music. In that mean’s how adisturbances and operating conditions. The effectiveness of musician with different search modes to reach its desiredthe proposed UPFC controller based on PID controller to damp state. To implement the above concepts in form of algorithmout of oscillations over a wide range of operating conditions ahead will several steps. This process generally in the formand variation of system parameters is showed in simulationresults and eigenvalue analysis. of the following five steps will be implemented [7- 9]. 1. Initialize the problem and algorithm parameters.Index terms- UPFC, Chaotic harmony search, PID controller, 2. Initialize the harmony memory.SMIB system, LFO 3. Improvise a new harmony. 4. Update the harmony memory. I. INTRODUCTION 5. Check the stopping criterion. A.1. Initialize the problem and algorithm parameters UPFC is a kind of FACTs devices that it can be used for At this stage initialize all the algorithm parameters arevoltage regulation compensation, phase shifting regulation, carried out. These parameters can be defined by the followingimpedance compensation and reactive compensation [1]. terms [7- 9]:UPFC has some great feature but first capability of it is HMS: Harmony memory size or the number of solutionindependent controlling of real and reactive power flows in vectors in the harmony memorythe transmission system [2]. Now days UPFC’s utilize move HMCR: Harmony memory considering rateforward to the secure and economic operation in new power PAR : Pitch adjusting ratesystems. Several controlling methods for FACTs devices NI : Number of improvisationshave been introduced. An assessment of the effects of power N : Number of decision variablessystem stabilizer (PSS) and static phase shifter (SPS) control A.2. Initialize the Harmony Memoryusing simulated annealing (SA) in [3] has been carried out. The harmony memory (HM) is a matrix include ofProblem of the STATCOM state feedback design based on independent variables which in this stage are selectedzero set concept coming in [4]. Particle swarm optimization randomly. Each row of this matrix indicates a solution to the(PSO) for achieved output feedback parameters of UPFC in problem.[5] is used. In this article a single machine infinite bus (SMIB) as apower system is considered. After making a linear systemaround the operating condition with a disturbance in differentloading situation that are converted to optimizing problem.For solving these kinds of problem, several algorithms are A.3. Improvise a New Harmonyrecommended in the above but in this paper chaotic harmony Producing a new harmony is called improvisation. Thesearch (IHS) technique is used. By considering available new harmony vector x’=( x1’, x2’,…, xN’) is achieved by threeparameter Äù as a input of PID controller this procedure is parameters: harmony memory consideration rate, pitchcarried out. In this paper two UPFC inputs applied adjustment rate and random selection. In the improvedindependently that connected to the output of PID controller. harmony search algorithm two parameters in each iterationFinally the effectiveness of this work by result evaluation are changed. These parameters are pitch adjustment rateand comparison of performance indices is showed. (PAR) and bandwidth (bw). The form of the changing these parameters is shown at below equations:© 2012 ACEEE 16DOI: 01.IJEPE.03.02.78
  2. 2. ACEEE Int. J. on Electrical and Power Engineering, Vol. 03, No. 02, May 2012Where:PAR pitch adjusting rate for each generationPARmin minimum pitch adjusting ratePARmax maximum pitch adjusting rateNI number of solution vector generationsgn generation numberHerebw(gn) bandwidth for each generationbwmin minimum bandwidthbwmax maximum bandwidthA.4. Update the Harmony Memory In the updating harmony memory stage, with placing newvalue ( x’ = ( x1’, x2’,…, xN’) ) on the objective function if objectivefunction value is better than the previous case it must be oldharmony out of memory and its new value will replaced.A.5. Check Stopping Criterion If the stopping criterion (maximum number ofimprovisations) is satisfied, computation is terminated.Otherwise, steps 3 and 4 are repeated. Figure 1. Flowchart of the chaotic harmony searchB. Proposed Method In numerical analysis, sampling, decision making and III. MODELING THE POWER SYSTEM UNDER STUDYespecially heuristic optimization needs random sequenceswith some features. These features consist a long period and The system in this article is a single machine infinite busgood uniformity. The nature of chaos is apparently random (SMIB) with UPFC installed as shown in Fig. 2 [5]. Forand unpredictable. Mathematically, chaos is randomness of analysis and enhancing small signal stability of power systema simple deterministic dynamical system and chaotic system through UPFC, dynamic relation of system is needed. To havemay be considered as sources of randomness [7]. There are these relations through park transformation and ignoringmany methods for generating of random numbers but here resistance of both boosting and exciting transformers can beused sinusoidal iterator for chaotic map [7]. It is represented achieve following equations [5, 6]:by: Xn+1= axn2sin (πxn) (4)When a = 2.3 and x0=0.7 it has the simplified form representedby: Xn+1= sin (πxn) (5)It generates chaotic sequence in (0, 1). Initial HM is generatedby iterating the selected chaotic maps until reaching to theHMS as shown in flowchart Fig.1 [7]: where vEt, iE, vBt, and iB are the excitation voltage, excitation current, boosting voltage, and boosting current, respectively; Cdc and vdc are the dc link capacitance and voltage [5]. The non linear model of the SMIB system introduced Fig.2 as shown following equations:© 2012 ACEEE 17DOI: 01.IJEPE.03.02.78
  3. 3. ACEEE Int. J. on Electrical and Power Engineering, Vol. 03, No. 02, May 2012 By properly choosing the PID gains (K p, K i, K d), the eigenvalues of system are moved to the left-hand side of the complex plane and the desired performance of controller can be achieved. UPFC controllers (mB, mE, δB and δE) are four parameters that can help them, reach the above goals mentioned but in this paper the two UPFC’s controller inputs (δE, mB) separately under various operating conditions is considered. In this study for solving optimization problem and reach the global optimal value of coefficients K, CHS algorithm is used. Figure 3. UPFC with PID controller Figure 2. SMIB power system equipped with UPFC in form Integral of Time Multiplied Absolute value of theA. Power System Linearized Model Error (ITAE) as the objective function for the algorithm is With applying linearization process around operating selected. The objective function is defined as follows:point on under study system, state space model of systemaccording below relation can be achieved. In the above equations, tsim is the time range of simulation.Where, the state vector x, input vector u, A and B are: The design problem can be formulated as the following constrained optimization problem, where the constraints are the controller parameters bounds: Typical ranges of the optimized parameters are [0.01–150] for Kp and [-5 – 5] for Ki and [-10 – 10] for Kd. The optimization of UPFC controller parameters is carried out by evaluating the objective cost function as given in Eq. (19). The operating conditions are considered as, Normal, light and heavy load respectively: P = 0.80 pu , Q = 0.114 pu and xL = 0.5 pu. P = 0.2 pu, Q = 0.007 pu and xL = 0.5 pu. P = 1.20 pu, Q = 0.264 pu and xL = 0.5 pu. In order to acquire better performance, the parameters of CHS algorithm are showed in table I . T ABLE I . IV. PID CONTROLLER FOR UPFC VALUE OF CHS ALGORITHM C ONSTANT PARAMETERS The eigenvalues of the state matrix A that are called thesystem modes define the stability of the system. By usingPID controller, can move the unstable mode to the left-handside of the complex plane in the area of the negative real In optimizing values of the controller parameters, algorithmparts. A PID controller has the following structure: must be repeated several times. Finally values for PID control gains are selected. Optimal values in normal load are shown in the table II:© 2012 ACEEE 18DOI: 01.IJEPE.03.02.78
  4. 4. ACEEE Int. J. on Electrical and Power Engineering, Vol. 03, No. 02, May 2012 T ABLE II . T ABLE III . T HE O PTIMAL G AIN ADJUSTING OF T HE PROPOSED C ONTROLLERS EIGENVALUES OF SYSTEM IN D IFFERENT O PERATING C ONDITIONS FOR δE BASED CONTROLLER V. T IME DOMAIN SIMULATION System performance with the values obtained for theoptimal PID by applying a disturbance at t = 1 for 6 cycles is T ABLE IV.evaluated. The speed and generator power deviation at normal, EIGENVALUES OF SYSTEM IN D IFFERENT O PERATING C ONDITIONS FOR m E BASEDlight and heavy load with the proposed controller based on CONTROLLERthe δE and mB are shown in Fig. 4 and Fig.5 respectively. Todemonstrate performance robustness of the proposedmethod, two performance indices: the ITAE and Figure ofDemerit (FD) based on the system performance characteristicsare defined as [8]:Where ( ω) is the speed deviation, ( Pe) is the generatorpower deviation, Overshoot (OS), Undershoot (US) and Ts isthe settling time of speed deviation for the machine isconsidered for evaluation of the ITAE and FD indices. It isworth mentioning that the lower the value of these indices is,the better the system response in terms of time-domaincharacteristics. It can be seen that the values of these systemperformance characteristics with the PID δE based controllerare much smaller compared to PID mB based controller. Figure 5. Dynamic responses for generator power deviation with normal (a), heavy (b) and light load (c): solid (δ E based controller), dotted ( mB based controller), dashed (without controller) T ABLE V. VALUES OF PERFORMANCE I NDICES ITAE AND FDFigure 4. Dynamic responses for speed deviation with normal (a),heavy (b) and light load (c): solid (δ E based controller), dotted (mB based controller), dashed (without controller)© 2012 ACEEE 19DOI: 01.IJEPE.03.02.78
  5. 5. ACEEE Int. J. on Electrical and Power Engineering, Vol. 03, No. 02, May 2012 CONCLUSIONS REFERENCES The chaotic harmony search algorithm was successfully [1] L. Gyugyi, “Unified power-flow control concept for flexible acused for the modeling of UPFC based PID damping controller. characteristics are defined as: transmission systems”, IEE Proc.For each of the control signals from available state variable Gen. Transm, Distrib., vol. 139, No. 4, pp. 323-331, 1992.Δω is used. The efficient of the proposed UPFC controller for [2] N Tambey, Prof M L Kothari, Unified Power Flow Controller Based Damping Controllers for Damping Low Frequencyimproving dynamic stability performance of a power system Oscillations in a Power System. IE(I) Journal-EL, June 2003, Volare illustrated by applying disturbances under different 84operating points. Results from time domain simulation shows [3] M.A.Abido”Simulated annealing based approach to PSS andthat the oscillations of synchronous machines can be easily FACTS based stabilizer tuning”, Electrical Power and Energydamped for power systems by this method. To analyze Systems 22 (2000) 247–258performance of UPFC’s controller two indicators were used. [4] VitalySpitsa, Abraham Alexandrovitz, Ezra Zeheb, “Design ofThese indices in terms of ‘ITAE’ and ‘FD’ are introduced that a Robust State Feedback Controller for a STATCOM Using a Zerothis indices demonstrate that PID with δE based damping Set Concept “IEEE Trans on Power Delivery, Vol. 25, No. 1, JAN 2010, pp.885-897controller is superior to mB based damping controller. [5] H. Shayeghi, H.A. Shayanfar, S. Jalilzadeh, A. Safari, “A PSO based unifed power flow controller for damping of power system APPENDIX A oscillations”, journal of energy conversion and management, 50 (2009); 2583-2592. T ABLE.VI . SYSTEM PARAMETERS [6] Wang HF. A unified model for the analysis of FACTS devices in damping power system oscillations – part III: unified power flow controller. IEEE on TPD 2000;15(3):978–83. [7] Bilal Alatas, ‘Chaotic harmony search algorithms’, journal of applied mathematics and computation 216 (2010) 2687–2699 [8] S.L. Kang, Z.W. Geem, A new structural optimization method based on the harmony search algorithm, Comput. Struct. 82 (9–10) (2004) 781–798. [9] Z.W. Geem, C. Tseng, Y. Park, Harmony search for generalized orienteering problem:best touring in China, in: Springer Lecture Notes in Computer Science, vol. 3412, 2005, pp . 741-750© 2012 ACEEE 20DOI: 01.IJEPE.03.02.78

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