2003 Febrero PS Matlab Simulink

42 IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 18, NO. 1, FEBRUARY 2003

PAT: A Power Analysis Toolbox forMATLAB/Simulink

Karl Schoder, Amer Hasanovic, Ali Feliachi, Senior Member, IEEE, and Azra Hasanovic

AbstractA power system simulation environment inMATLAB/Simulink is presented in this paper. The developedpower analysis toolbox (PAT) is a very flexible and modular toolfor load flow, transient, and small-signal analysis of electric powersystems. Standard power system component models and a widerange of flexible ac transmission systems (FACTS) devices areincluded. Its data structure and block library have been tested toconfirm its applicability to small-to-medium-sized power systems.Its advantages over an existing commercial package are given.

Index TermsMATLAB, PAT, simulation, Simulink, transientstability.

I. INTRODUCTION

WITH THE RECENT deregulation and increase in thedemand, maintaining the power system stability is be-coming evermore difficult. In order to operate power systemseffectively, without reduction in the system security and qualityof supply, even in the case of contingency conditions such asloss of transmission lines and/or generating units, which willmost probably occur at a higher frequency under deregulationand/or restructuring, new control strategies need to be imple-mented. New equipment and control devices, such as flexibleac transmission systems (FACTS) [1], are sought to enhancestability and reliability of the system. Also, neural networks,fuzzy logic, and other soft computing technologies are increas-ingly used to answer control challenges. Before implementingany novel technology, it is essential to validate these new con-trol schema through simulation within an environment that al-lows accurate modeling of all power systems components. Thisenvironment also has to be modular enough to allow frequentadditions of new components without compromising the overallspeed of simulation or its accuracy.

Traditional tools for power system simulation such as PSS/E[2], Eurostag [3], and PSAPAC [4], require coding in conven-tional programming languages and are optimized for speed andefficiency. However, implementation of new components, espe-cially soft computing ones, within these packages can be verydifficult and error prone.

In the last decade, MATLAB [5] became, de facto, thestandard tool for flexible technical computing. MATLAB

Manuscript received September 26, 2001; revised April 18, 2002. This workwas supported by the National Science Foundation under Grant ECS-9870041and a DOE/EPSCoR WV state Implementation Award.

K. Schoder, Am. Hasanovic, and A. Feliachi are with the Lane Departmentof Computer Science and Electrical Engineering, West Virginia University,Morgantown, 26506-6109 USA.

A. Hasanovic is with American Electric Power, Columbus, OH, 43230 USA.Digital Object Identifier 10.1109/TPWRS.2002.807117

incorporates a large number of domain specific toolboxes suchas fuzzy logic toolbox, neural network toolbox, control toolbox,real-time workshop, etc., and Simulink [6], an interactive toolfor modeling, simulating, and analyzing dynamic systems.Simulink offers a set of tools that can be used to build systemsfrom the library of built-in blocks. It also allows creationof custom blocks that can incorporate C/C++, Fortran, orMATLAB code. These features make MATLAB/Simulink anattractive choice for power systems-related research.

A number of papers addressed the issue of power system sim-ulation in MATLAB/Simulink. Using the real-time workshop,the authors in [7] have demonstrated real-time simulation of afour-machine power system in the Simulink environment. Mah-seredjian and Alvarado have developed MatEMTP [8], a setof m-files that can perform Electromagnetic Transient Program(EMTP)-type simulations in the MATLAB environment. In [9],Allen et al. described an object-oriented approach. The problemwith this approach is that Simulink was not designed to handlenoncausal modeling (i.e., model ports in Simulink must have ei-ther output or input role specified). If these ports are connectedin an object-oriented fashion, algebraic loops are created withinthe model. The current Simulink solvers resolve algebraic loopsiteratively, decreasing the speed of simulation while having anegative impact on simulation stability. These limitations makethis approach impractical for larger systems.

There exist two commercial toolboxes that allow powersystem simulation in MATLAB, namely the power systemtoolbox [10] (PST) and power system blockset [11]. The lattertargets the three-phase power system simulation and, therefore,is not appropriate for large-scale transient stability analysis. ThePST is a set of MATLAB m-files that can be used to performpower flow and stability studies. PST does not offer graphicaluser interface (GUI) and cannot be used within the Simulinkenvironment; addition of new components is time consumingand requires a good understanding of the toolboxs internalstructure. PST provides a single predictor-corrector solver thatsupports vectorized computation. However, Simulink offers 12continuous time-domain solvers that outperform PST solver interms of features and speed of computation.

Due to the drawbacks of the mentioned environments andlack of some features that were required for an ongoing researchconducted at West Virginia Universitys Advanced Power En-gineering Research Center (APERC), a power analysis toolbox(PAT) was developed. PAT incorporates most features anddynamic models that are provided by PST. Additionally, PATincludes some FACTS device models that are not part of PSTdistribution. Significant improvements, in terms of speed andmodularity, were obtained by extensively using features that

0885-8950/03$17.00 2003 IEEE

SCHODER et al.: PAT: A POWER ANALYSIS TOOLBOX FOR MATLAB/SIMULINK 43

Fig. 1. PAT modules.

were introduced in Simulink V4.1, such as complex numberand matrix signal propagation. PATs main features are

fast transient simulations; automatic generation of linearized models; addition of new components by using Simulinks GUI; simple interface with other MATLAB/Simulink tool-

boxes; possibility to generate C-code for real-time simulations

using real-time workshop.This paper is organized as follows: overview of PAT data

structure and modules is presented in Section II. Section IIIdemonstrates some simulation and analysis of a 16-generator,68-bus system which is a representation of the New England/New York interconnected system. Also, the implementation of afuzzy damping controller for a UPFC in the two-area-four-gen-erator system used to improve transient stability is presented.Speed comparison of PAT with PST is presented in Section IV.

II. SIMULATION ENVIRONMENT

Modules that constitute the structure of PAT are shown inFig. 1. By combining the functionality of these modules, thetoolbox can perform the following tasks:

load flow; transient stability; small-signal analysis.

The following sections describe these modules and their in-teraction. But first, preprocessing and PATs data structure arepresented.

A. PreprocessorBefore any computations can be performed, a data file that de-

scribes the power system must be read and processed. Currently,PAT supports a modified PST data format that includes FACTSdevices and their controls. As a result of the preprocessing, aMATLAB structure object, shown in Fig. 2, is obtained.

B. PAT Data StructureThe PAT data structure is designed to hierarchically organize

the vast amounts of data necessary to describe the power systemcomponents.

The three top-most levels of the hierarchy are shown in Fig. 2(from left to right). Starting with the abstract layer that storesthe information of power systems components, the tree expands

Fig. 2. PAT data structure.

Fig. 3. Power system model in Simulink.

down to the fields that hold information on specific devices andtheir parameters.

The data structure supports simple access to specific fields,and offers enough flexibility to be extended by the user to ac-commodate new components. The expandability is a major re-quirement for todays power system analysis and simulationsoftware due to the steadily growing number of power elec-tronics devices implemented in power systems.

C. Load FlowThe load-flow module extracts the power system informa-

tion stored in the PAT data structure and solves the load-flowproblem using a NewtonRaphson algorithm. The output fromthis module is the PAT data structure appended with the fieldsthat contain the load-flow solution as well as computed internalsteady-state quantities of the dynamic devices and their controls.This information is used to initialize the transient module.

Elements included at the current development stage aregenerators, slack buses, PI-lines, constant PQ-loads, under loadtap changers (ULTCs), and various FACTS devices [e.g., staticvar compensator (SVC), thyristor-controlled series capacitor(TCSC), static synchronous compensator (STATCOM), staticsynchronous series compensator (SSSC), unified power-flowcontroller (UPFC)], and their controls. The load flow of apower system that includes FACTS devices is solved withrespect to the desired control modes and reference values. Thepossible control modes include fixed compensation mode aswell as constant power-flow and voltage-control modes.


Fig. 4. New England/New York interconnected system.

D. Transient Stability AnalysisThe transient module targets the balanced-power system tran-

sient studies and is organized as a Simulink-Block library. Itallows the user to build a case file via a drag-and-drop featureprovided by Simulink. Each block in the PAT library models onetype of device (e.g., subtransient machine model, UPFC modeletc.). Additionally, each block is vectorized, meaning that theuser needs to add only one block to the Simulink MDL-case fileto represent a number of devices of the same type. For example,if there are detailed machines and classical machines (EM)in a case study one subtransient block and one EM-block willbe used from the PAT library to perform the simulation. The in-ternals of each block have been modeled by Simulink built-inblocks and/or MATLAB-S functions. Through the utilization ofSimulinks ability to propagate complex vectors as signals be-tween blocks, a great improvement in simulation speed has beenachieved.

To properly initialize the time-domain simulation, thetransient analysis module requires consistent steady-stateconditions as found by the load-flow module and a switchingfile describing switching sequence and disturbance scenarios(e.g., type of fault, loss of line/load/generating unit, opening/re-closure of the faulted line, etc.).

Simulink is based on a set of differential equation solvers,ranging from simple fixed step (integration) to variable timestep solvers that can handle stiff systems. These solvers are ableto handle traditional power system elements (e.g., generators,excitation systems, PSSs, etc.). Furthermore, they can cope withthe numerical problems introduced by devices with small timeconstants, such as FACTS devices. Many power system ele-ments have discrete and/or dynamic states (e.g., switches, digitalcontrols, saturation limits, etc.); therefore, they require a simu-lation environment that is capable of handling hybrid models.Simulinks solvers have built-in zero-crossing detection algo-rithms that properly adjust the simulation time step to detectdiscontinuities and automatically reinitialize the simulation.

The problem of incorporating dynamics of FACTS devicesand nonconforming loads into the network solution has beensolved in the following way. Due to the lack of explicit analyt-ical expressions for the injected currents at the FACTS bus(es),the actual influence of FACTS devices has to be found usingan iterative approach at each time step of the simulation. Algo-rithms based on a fixed-point and Newtons method [10], [12]have been implemented as PAT blocks (see bus interface blockin Fig. 5) and can be placed into the mdl-case study file viadrag-and-drop. Elements of varying impedance (i.e., SVC andTCSC) are interfaced via their admittance valuesSTATCOM,SSSC, and UPFC are interfaced as voltage sources, and noncon-forming loads as current sources.

E. Small-Signal Analysis

Though the power system is a highly nonlinear system, awealth of information is obtained from the linearized modelaround an operating point. The eigenstructure of the system, inparticular, can be used to analyze properties of the system, as-sess its stability, select control signals, and site the controllers ordesign controllers using the rich tools of linear control systems.For example, parameters for power system damping controllersare often found by applying various linear control design pro-cedures. Therefore, it was important to choose a simulation en-vironment that guarantees the ability to linearize the dynamicpower system model at the desired operating point, and offersthe use of well-established linear analysis and synthesis tools.

The built-in capabilities of the MATLAB/Simulink environ-ment are used to determine the state-space representation of thepower system and to perform eigenvalue analysis. Additionally,optional toolboxes, such as robust control toolbox, LMI con-trol toolbox, -analysis and synthesis toolbox or control systemtoolbox, can be used to design linear controllers.


Fig. 5. Power system and UPFCs modeled in Simulink.

III. CASE STUDIES

The functionality of PAT is illustrated using two systems. Oneof these is a well-known two-area four-generator system [13]to illustrate usage of PAT in designing a UPFC fuzzy dampingcontroller [14], and the New England/New York interconnectedsystem to illustrate the other modules of PAT.

A. New England/New York SystemThe single line diagram of the system, for which two cases are

presented, is shown in Fig. 4. The first case study is the systemas found in [13]. In the second case, three UPFCs were addedon three heavily loaded tie-lines (line 12, line 89, and line4142). To ensure stability of the system, each generator wasequipped with a simple exciter and PSS.

Simulink representations of these systems are shown inFigs. 3 and 5. Numbers that appear on each connection rep-resent the width of vector signal being propagated. Simulinkautomatically adjusts these values according to the informationstored in PATs data structure. Any signal can be monitoredwhile the simulation is running by connecting one of theblocks from the Sinks-library. Additionally, for the purpose offurther analysis and/or plot generation, signals can be stored inMATLABs workspace.

To find the FACTS devices bus voltages, an iterative pro-cedure is required. The FACTS devices interface is shown inFig. 5. The interfacing block takes the generator internal volt-ages and the interfacing quantities of the FACTS devices as in-puts. In case of the UPFC, the injected shunt and series volt-ages with respect to one of its buses are taken as input signals.The output of the FACTS devices interfacing block is used to-gether with the generator voltages to determine the network cur-rent solutions.

The same simulation scenario is investigated for both casestudies. At time ms, a three-phase fault is applied onthe line between buses 29 and 28, the near end of the line isopened at ms, and the line is completely removed at

ms. The speed response of the generator closest tothe three-phase fault location is shown in Fig. 6. To be able

Fig. 6. Comparing speed of generator closest to the fault location(solidsystem with UPFC; dashedsystem without UPFCs).

to estimate possible improvements in transient stability, the re-sponse of the test system with three UPFCs installed is given inthe same figure. These are only the preliminary results of usingFACTS devices to enhance the overall controllability and sta-bility of power systems. Control schemes and parameter tuningare not investigated further in this paper. Voltage magnitude pro-file of the faulted bus 29 and its two closest neighbors (buses 28and 61), during the first two seconds of simulation, are shownin Fig. 7. It can be seen that the ODE solver accurately adjuststhe time steps taken at the time of fault application (100 ms),opening of faulted line side (190 ms), and removing the faultentirely by opening the remote end (200 ms). The UPFC closeto the faulted area of the power system helps to stabilize the busvoltages.

Linear representations of the two test systems are obtainedwithin the linearization module of PAT. Signals to be used as in-puts and outputs during the linearization procedure can be spec-ified by connecting Simulink in and outports at the desired lo-cations. Part of the eigenvalue plot for the linearized power sys-tems with and without the UPFCs installed is given in Fig. 8.The state space representations of both systems containing 222


Fig. 7. Comparing bus voltages close to fault location with (solid) and without(dashed) UPFCs.

Fig. 8. Comparing eigenvalues with () and without () UPFCs.

and 207 continuous states, respectively, have been verified viacomparison of simulations of the linear and nonlinear systemsusing small disturbances.

B. Two-Area SystemSince this system is widely available in the literature, its

single line diagram is omitted. In [14], the authors have usedfuzzy control to design a UPFC damping controller. Fig. 9compares the response of the system without UPFC, withUPFC, as well as the system with UPFC and fuzzy dampingcontroller. The fuzzy damping controller measures the activeline power flow at the UPFC site and augments the referencesignal for the active line power flow as controlled by the UPFC.The improved transient stability due to the fuzzy dampingscheme can be observed. Also, a reduced first swing stabilityin case of applying a UPFC without fuzzy damping control isnoticeable.

IV. PERFORMANCE EVALUATION

To evaluate the performance of PAT comparisons with thePST, on-the-test systems with and without UPFCs have been

Fig. 9. Relative machine angle between two areas (dashedwithout UPFC,solidwith UPFC, dash-dottedUPFC with fuzzy damping control).

TABLE ISIMULATION TIME FOR PST AND PAT WITHOUT UPFCS

FOR A TRANSIENT PERIOD OF 10 s

TABLE IISIMULATION TIME PAT WITH UPFCS FOR A TRANSIENT PERIOD OF 10 s

performed. Very promising results with speed ratio up to 20 : 1in favor of PAT were achieved. To obtain raw performance mea-surement, all displays that get refreshed during the simulationrun-time were disabled in both toolboxes. Environment used forthe benchmarking purpose consisted of Pentium IV-based PCrunning MATLAB/Simulink 6.0 under Windows 2000.

Table I shows the simulation time required for the powersystem without UPFCs in PST and PAT using different ODEsolvers and time step settings. The simulation outputs producedwith different solver settings were identical in terms of system


behavior and accuracy. The time setting for the varying time stepsolvers should be interpreted as the maximum time step allowed.

Table II gives the time required to simulate the test systemwith UPFCs included. The implicit interface block for dynamicloads and FACTS devices introduces an algebraic loop inSimulink model that needs to be solved iteratively. Hence, asignificant increase in simulation time is recorded. Extremelysmall time steps are required to maintain the numerical stabilityof simulation when fixed step size solvers are used. Therefore,results obtained with these solvers are omitted from the table.

Further comparisons with different modeling approachessuch as EMTPs detailed three-phase analysis have not beenattempted. Electromagnetic transients and switching events ofhigh frequency are not in the scope of PAT.

V. CONCLUSIONA power system simulation environment in MATLAB/

Simulink is presented in this paper. The developed PAT is avery flexible and modular tool for load flow, transient, andsmall-signal analysis of electric power systems. Standard powersystem component models and a wide range of FACTS devicesare included. Its data structure and block library have beentested to confirm its applicability to small-to-medium-sizedpower systems. Its advantages over existing commercialpackages are given. The software presented complementsexisting commercial packages such as PST and it has beendemonstrated on test systems that it is faster and has moreFACTS device models. Two systems have been given toillustrate the capabilities of PAT. The first test system is theNew England/New York power system and illustrates basicfeatures of the toolbox, such as speed of simulation, interfacingof FACTS devices, and extraction of linearized model aroundan operating point. The second system is the well-knowntwo-area system and demonstrates the implementation offuzzy-logic-based damping controller for the UPFC within thesimulation environment. This software library has not beenreleased to the public at this time.

REFERENCES[1] N. G. Hingorani and L. Gyugyi, Understanding FACTS. Piscataway,

NJ: IEEE Press, 2000.[2] PSS/E, Power system simulator for engineering, Power Technologies

Inc., Schenectady, NY, 2001.[3] EUROSTAG, Software for the simulation of power system dynamics,

Tractebel Energy Engineering, Brussels, Belgium, 2001.[4] PSAPAC, The power system analysis package, Powertech Labs Inc.,

Vancouver, BC, Canada, 2001.[5] MATLAB, High-performance numeric computation and visualization

software, The Mathworks Inc., Natick, MA, 2001.

[6] Simulink, Dynamic system simulation software, The Mathworks Inc.,2001.

[7] T. Hiyama and A. Ueno, Development of real time power system sim-ulator in MATLAB/Simulink environment, in Proc. IEEE Power Eng.Soc. Summer Meeting, Seattle, WA, July 1620, 2000.

[8] J. Mahseredjian and F. Alvarado, Creating an electromagnetic transientprogram in MATLAB: MatEMTP, IEEE Trans. Power Delivery, vol.12, pp. 380388, Jan. 1997.

[9] E. Allen, N. LaWhite, Y. Yoon, J. Chapman, and M. Ilic, Interactiveobject-oriented simulation of interconnected power systems usingsimulink, IEEE Trans. Educ., vol. 44, pp. 8795, Feb. 2001.

[10] J. Chow, Power system toolbox 2.0, in Cherry Tree Scientific Software,Colborne, ON, Canada, 2000.

[11] Hydro-Quebec and TEQSIM International, Power system blockset foruse with Simulink, The Mathworks Inc., Natick, MA, 2001.

[12] K. Schoder, A. Hasanovic, and A. Feliachi, Load-flow and dynamicmodel of the Unified Power Flow Controller (UPFC) within the PowerSystem Toolbox (PST), in Proc. IEEE Midwest Symp. Circuits Syst.,Lansing, MI, August 811, 2000.

[13] R. Graham, Power System Oscillation, M. A. Pai, Ed. Norwell, MA:Kluwer, 2000.

[14] K. Schoder, A. Hasanovic, and A. Feliachi, Power system dampingusing fuzzy controlled unified power flow controller, in Proc. IEEEPower Eng. Soc. Winter Meeting, Columbus, OH, 2001.

Karl Schoder received the M.S.E.E. (Dipl.-Ing. der Elektrotechnik) degreefrom Vienna University of Technology, Vienna, Austria, in 1997, and the Ph.D.degree from the Department of Computer Science and Electrical Engineeringat West Virginia University, Morgantown, in 2002.

Currently, he is a visiting Research Assistant Professor at West VirginiaUniversity.

Amer Hasanovic was born in Tuzla, Bosnia-Herzegovina, in 1976. He receivedthe B.S. degree from the University of Tuzla, Bosnia-Herzegovina, in 1999,and the M.S. degree in electrical engineering from West Virginia University,Morgantown, in 2001. He is currently pursuing the Ph.D. degree at West VirginiaUniversity, Morgantown.

Currently, he is a Graduate Research Assistant at West Virginia University.

Ali Feliachi (SM86) received the Diplme dIngnieur en electrotechnique de-gree from Ecole Nationale Polytechnique of Algiers, Algeria, in 1976, and theM.S. and Ph.D. degrees in electrical engineering from Georgia Institute of Tech-nology, Atlanta, in 1979 and 1983, respectively.

Currently, he is full Professor and the holder of the Electric Power SystemsChair endowed position at West Virginia University, Morgantown. He has beena faculty member in the Lane Department of Computer Science and ElectricalEngineering at West Virginia University since 1984.

Azra Hasanovic received the electrical engineering degree from the Univer-sity of Tuzla, Bosnia-Herzegovina, in 1997, and the M.S.E.E. degree from WestVirginia University, Morgantown, in 2000.

Currently, she is with AEP Transmission Planning/System Dynamics Anal-ysis Group, Columbus, OH.

Index:

CCC: 0-7803-5957-7/00/$10.00 2000 IEEE

ccc: 0-7803-5957-7/00/$10.00 2000 IEEE

cce: 0-7803-5957-7/00/$10.00 2000 IEEE

index:

INDEX:

ind:

Documents

2003 Febrero PS Matlab Simulink