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Boroujeni, Sayed Mojtaba Shirvani
- Optimal PID Power System Stabilizer Tuning Based on Particle Swarm Optimization
Abstract Views :509 |
PDF Views:119
Authors
Sayed Mojtaba Shirvani Boroujeni
1,
Reza Hemmati
1,
Hamideh Delafkar
1,
Amin Safarnezhad Boroujeni
1
Affiliations
1 Islamic Azad University, Boroujen Branch, Department of Electrical Engineering, Boroujen, IR
1 Islamic Azad University, Boroujen Branch, Department of Electrical Engineering, Boroujen, IR
Source
Indian Journal of Science and Technology, Vol 4, No 4 (2011), Pagination: 379-383Abstract
Power system stabilizers (PSS) are used to generate supplementary damping control signals for the excitation system in order to damp the low frequency oscillations (LFO) of the electric power system. The PSS is usually designed based on classical control approaches but this conventional PSS (CPSS) has some problems. To overcome the drawbacks of CPSS, numerous techniques have been proposed in literatures. In this paper a PID type PSS is considered for damping electric power system oscillations. The parameters of this PID type PSS are tuned based on particle swarm optimization method. The proposed PSS (PSO-PSS) is evaluated against the conventional power system stabilizer (CPSS) at a single machine infinite bus power system considering system parametric uncertainties. The simulation results clearly indicate the effectiveness and validity of the proposed method.Keywords
Electric Power System Stabilizer, Low Frequency Oscillations, Particle Swarm OptimizationFull Text
References
- Bouhamida M, Mokhatri A and Denai MA (2005) Power system stabilizer design based on robust control techniques. ACSE J. 5, 33-41
- Chatterjee A, Ghoshal SP and Mukherjee V (2009). A comparative study of single input and dual input power system stabilizer by hybrid evolutionary programming. World Cong. on Nature & Biologically Inspired Computing. pp:1047-1059.
- Dubey M (2007) Design of genetic algorithm based fuzzy logic power system stabilizers in multi machine power system. Int. Conf. on soft computing & intelligent systems. pp:214-219.
- Gupta R, Bandopadhya B and Kulkarni AM (2005) Power system stabilizer for multi machine power system using robust decentralized Periodic output feedback. IEE Proc. control theory application. 152, 3–8.
- Hwanga GH, Kimb DW, Leec JH and Joo Y (2008) Design of fuzzy power system stabilizer using adaptive evolutionary algorithm. Engg. Appl. Artificial Intelligence. 21, 86–96.
- Jiang P, Yan W and Weigu (2008) PSS parameter optimization with genetic algorithms. DRPT 2008, Nanjing China. pp: 900-903.
- Kundur P (1993) Power system stability and control. McGraw-Hill, Inc., NY. pp:700-822.
- Linda MM and Nair NK (2010) Dynamic stability enhancement with fuzzy based power system stabilizer tuned by hottest non-traditional optimization technique. Second Int. Conf. on Computing, Communication & Networking Technol. pp:1-5.
- Liu W, Venayagamoorthy GK and Wunsch DC (2005) A heuristic dynamic programming based power system stabilizer for a turbo generator in a single machine power system. IEEE Trans. on Industry Appl. 4, 1377-1385.
- Mocwane K and Folly KA (2007) Robustness evaluation of H∞ power system stabilizer. IEEE PES Power Africa Conf. Exhibition. pp:16-20.
- Nambu M and Ohsawa Y (1996) Development of an advanced power system stabilizer using a strict linearization approach. IEEE Trans. on Power Sys. 11, 813-818.
- Randy LH and Sue EH (2004) Practical genetic algorithms. 2nd edn., John Wiley & Sons. pp:25-67.
- Sil A, Gangopadhyay TK, Paul S and Maitra AK (2009) Design of robust power system stabilizer using H∞ mixed sensitivity technique. 3rd Int. Conf. on Power Sys. India. pp:1-4.
- Sudha KR, Vakula VS and Vijayasanthi R (2009) Particle swarm optimization in fine tuning of PID fuzzy logic power system stabilizer. Int. Conf. on Advances in Computing, Control & Telecommunication Technol. pp:356-358.
- Sumathi N, Selvan MP and Kumaresan N (2007) A hybrid genetic algorithm based power system stabilizer. Int. conf. on intelligent & advanced systems. pp:876-881.
- Yassami H, Darabi A and Rafiei SMR (2010) Power system stabilizer design using strength pareto multiobjective optimization approach. Electric Power Systems Res. 80, 838–846
- Robust PID Power System Stabilizer Design Based on Pole Placement and Nonlinear Programming Methods
Abstract Views :525 |
PDF Views:161
Authors
Affiliations
1 Department of Electrical Engineering, Islamic Azad University, Boroujen Branch, Boroujen, IR
1 Department of Electrical Engineering, Islamic Azad University, Boroujen Branch, Boroujen, IR
Source
Indian Journal of Science and Technology, Vol 4, No 4 (2011), Pagination: 456-461Abstract
Power system stabilizers (PSS) are used to generate supplementary damping control signals for the excitation system in order to damp the low frequency oscillations (LFO) of the electric power system. The PSS is usually designed based on classical control approaches but this conventional PSS (CPSS) has some problems. To overcome the drawbacks of CPSS, numerous techniques have been proposed in literatures. In this paper a new robust hybrid method based on the combination of pole placement and nonlinear programming methods is proposed in order to design a robust power system stabilizer. The classical robust methods usually lead to a high order controller which is expensive, difficult to implement and somehow impossible. As a solution, in this paper a PID type PSS is considered for damping electric power system oscillations. The parameters of this PID type PSS (PID-PSS) are tuned based on pole placement and nonlinear programming methods. Therefore, not only the obtained PID-PSS is low order and easy to implement but also it has robust characteristics like robust controllers. The proposed PID-PSS is evaluated against the conventional and robust power system stabilizers in a single machine infinite bus power system considering system parametric uncertainties. The simulation results clearly indicate the effectiveness and validity of the proposed method.Keywords
Electric Power System Stabilizer, Pole Placement, Nonlinear Programming, Robust Control, PID ControllerFull Text
References
- Bazaraa MS, Shrali HD and Shetty CM (2006) Nonlinear programming theory and algorithms. John Wiley & sons, Inc., 3rd edn. publication.
- Bouhamida M, Mokhatri A and Denai MA (2005) Power system stabilizer design based on robust control techniques. ACSE J. 5, 33-41.
- Chatterjee A, Ghoshal SP and Mukherjee V (2009) A comparative study of single input and dual input power system stabilizer by hybrid evolutionary programming. World cong. on nature & biologically inspired computing. pp:1047- 1059.
- Chow JH (1988) A pole-placement design approach for systems with multiple operating conditions. IEEE Proc. Decision Control. 2, 1272–1277.
- Dubey M (2007) Design of genetic algorithm based fuzzy logic power system stabilizers in multi machine power system. Int. Conf. on soft computing & intelligent systems. pp:214-219.
- Gupta R, Bandopadhya B and Kulkarni AM (2005) Power system stabilizer for multi machine power system using robust decentralized periodic output feedback. IEE Proc. Control Theory Appl. 152, 3–8.
- Hemmati R, Shirvani SM and Abdollahi M (2010) Comparison of robust and intelligent based power system stabilizers. Int. J. Phy. Sci. 5, 2564-2573.
- Hwanga GH, Kimb DW, Leec JH and Joo Y (2008) Design of fuzzy power system stabilizer using adaptive evolutionary algorithm. Engg. Appl. Artificial Intelligence. 21, 86–96
- Jiang P, Yan W and Weigu K (2008) PSS parameter optimization with genetic algorithms. DRPT 2008, Nanjing China. pp: 900-903.
- Kundur P (1993) Power system stability and control. McGraw-Hill, Inc., NY. pp:700-822.
- Linda MM and Nair NK (2010) Dynamic stability enhancement with fuzzy based power system stabilizer tuned by hottest non-traditional optimization technique. 2nd Int. Conf. on Computing, Commun. & Networking Technol. pp:1-5.
- Liu W, Venayagamoorthy GK and Wunsch DC (2005) A heuristic dynamic programming based power system stabilizer for a turbo generator in a single machine power system. IEEE Trans. Industry Appl. 4, 1377-1385.
- Marsden GE, Sirovich L and Antman SS (2004) Introduction to optimization. Springer publication.
- Mocwane K and Folly KA (2007) Robustness evaluation of H∞ power system stabilizer. IEEE PES Power Africa Conf. Exhibition. pp16-20.
- Nambu M and Ohsawa Y (1996) Development of an advanced power system stabilizer using a strict linearization approach. IEEE Trans. Power Sys. 11, 813-818.
- Poulin E and Pomerleau A (1997) Unified PID design method based on a maximum peak resonance specification. IEE Proc. Control Theory Appl. 144, 566–574
- Sil A, Gangopadhyay TK, Paul S and Maitra AK (2009) Design of robust power system stabilizer using H∞ mixed sensitivity technique. 3rd Intl. Conf. on Power Sys. India. pp:1-4.
- Sudha KR, Vakula VS and Vijayasanthi R (2009) Particle swarm optimization in fine tuning of PID fuzzy logic power system stabilizer. Int. Conf. on Advances in Computing, Control & Telecommunication Technol. pp:356-358.
- Sumathi N, Selvan MP and Kumaresan N (2007) A hybrid genetic algorithm based power system stabilizer. Int. conf. on intelligent & advanced systems. pp:876-881.
- Yassami H, Darabi A and Rafiei SMR (2010) Power system stabilizer design using strength pareto multi-objective optimization approach. Electric Power Systems Res. 80, 838–846.
- Supplementary Stabilizer Design Based on STATCOM
Abstract Views :486 |
PDF Views:439
Authors
Affiliations
1 Department of Electrical Engineering, Boroujen Branch, Islamic Azad University, Boroujen, IR
1 Department of Electrical Engineering, Boroujen Branch, Islamic Azad University, Boroujen, IR
Source
Indian Journal of Science and Technology, Vol 4, No 5 (2011), Pagination: 525-529Abstract
This paper presents the application of static synchronous compensator (STATCOM) to enhance damping of Low Frequency Oscillations at a single-machine infinite-bus power system installed with a STATCOM as cast study. STATCOM is considered in order to damping of Low Frequency Oscillations. Therefore, the supplementary stabilizer based STATCOM (like power system stabilizer) is designed to reach defined purpose. Optimization methods such as Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) are considered to design STATCOM supplementary stabilizer controller. To show effectiveness and also comparing these two methods, the proposed methods are simulated under different operating conditions. Several linear time-domain simulation tests visibly show the validity of proposed methods in damping of power system oscillations. Also simulation results emphasis on the better performance of PSO in comparison with GA method.Keywords
Static Synchronous Compensator, Particle Swarm Optimization, Genetic Algorithms, Power StabilizerFull Text
References
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- Fuzzy Load Frequency Control in Multi Area Electric Power System
Abstract Views :426 |
PDF Views:123
Authors
Reza Hemmati
1,
Sayed Mojtaba Shirvani Boroujeni
1,
Hamideh Delafkar
1,
Amin Safarnezhad Boroujeni
1
Affiliations
1 Department of Electrical Engineering, Boroujen Branch, Islamic Azad University, Boroujen, IR
1 Department of Electrical Engineering, Boroujen Branch, Islamic Azad University, Boroujen, IR
Source
Indian Journal of Science and Technology, Vol 4, No 7 (2011), Pagination: 796-800Abstract
The Load Frequency Control (LFC) problem is one of the most important subjects in the electric power system operation and control. In practical systems, the conventional PI type controllers are applied for LFC. In order to overcome the drawbacks of the conventional PI controllers, PI and PID Fuzzy controllers are considered for LFC problem. The parameters of the proposed Fuzzy controllers are tuned using Genetic Algorithms (GA). A multi area electric power system with a wide range of parametric uncertainties is given to illustrate proposed method. The simulation results visibly show the validity of proposed controllers in LFC problem.Keywords
Multi Area Electric Power System, Load Frequency Control, PID Fuzzy Controller, PI Fuzzy Controller, Genetic AlgorithmsFull Text
References
- Kocaarslan I and Cam E (2005) Fuzzy logic controller in interconnected electrical power Systems for loadfrequency control. Electrical Power & Energy Systems. 27, 542–549.
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- Tan W (2010) Unified tuning of PID load frequency controller for power systems via IMC. IEEE Transactions Power Systems. 25(1), 341-350.
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- Stabilizer Design Based on UPFC Using Simulated Annealing
Abstract Views :457 |
PDF Views:111
Authors
Reza Hemmati
1,
Sayed Mojtaba Shirvani Boroujeni
1,
Hamideh Delafkar
1,
Amin Safarnezhad Boroujeni
1
Affiliations
1 Department of Electrical Engineering, Boroujen Branch, Islamic Azad University, Boroujen, IR
1 Department of Electrical Engineering, Boroujen Branch, Islamic Azad University, Boroujen, IR
Source
Indian Journal of Science and Technology, Vol 4, No 7 (2011), Pagination: 815-819Abstract
This paper presents the application of Unified Power Flow Controller (UPFC) to enhance damping of Low Frequency Oscillations (LFO) at a Single-Machine Infinite-Bus (SMIB) power system installed with UPFC. Since UPFC is considered to mitigate LFO, a supplementary UPFC like power system stabilizer is designed to reach the defined purpose. Simulated Annealing (SA) is used to tune UPFC supplementary stabilizer. To show effectiveness, the proposed method is compared with another optimization method named Genetic Algorithms (GA). Several linear timedomain simulation tests visibly show the validity of proposed method in damping of power system oscillations. Also simulation results emphasis on the better performance of SA in comparison with GA.Keywords
Flexible AC Transmission Systems, Unified Power Flow Controller, Low Frequency Oscillations, Simulated Annealing, Genetic AlgorithmsFull Text
References
- Alasooly H and Redha M (2010) Optimal control of UPFC for load flow control and voltage flicker elimination and current harmonics elimination. Compu. Math. Appl. 60, 926-943.
- Al-Awami A (2007) A Particle-Swarm based approach of power system stability enhancement with UPFC. Elec. Power & Energy Systems. 29, 251-259.
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- Tambey N and Kothari ML (2003) Damping of power system oscillation with Unified Power Flow Controller. IEE Proc. Gene., Trans. & Dist. 50 (2), 129-140.
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- Harmony Search Algorithm for Power System Stabilizer Tuning
Abstract Views :358 |
PDF Views:117
Authors
Sayed Mojtaba Shirvani Boroujeni
1,
Babak Keyvani Boroujeni
1,
Hamideh Delafkar
1,
Elahe Behzadipour
1,
Reza Hemmati
1
Affiliations
1 Department of Electrical Engineering, Boroujen Branch, Islamic Azad University, Boroujen, IR
1 Department of Electrical Engineering, Boroujen Branch, Islamic Azad University, Boroujen, IR
Source
Indian Journal of Science and Technology, Vol 4, No 9 (2011), Pagination: 1025-1030Abstract
The problem of tuning Power system stabilizers (PSSs) is commonly formulated as a nonlinear optimization problem with some constraints. In this paper a new optimization technique based on Harmony Search (HS) to solve the proposed optimization problem is presented. This is a very complex nonlinear programming problem. A constructive heuristic algorithm aimed at obtaining an excellent quality solution for this problem is presented. Results of the tests, carried out with a multi machine electric power system, show the capabilities of the method and also the viability of using the HS to solve the problem.Keywords
Multi Machine Power System, Power System Stabilizer, Low Frequency Oscillations, Harmony Search AlgorithmFull Text
References
- Bouhamida M, Mokhatri A and Denai MA (2005) Power system stabilizer design based on robust control techniques. ACSE J. 5, 33-41.
- Dubey M (2007) Design of harmony search algorithm based fuzzy logic power system stabilizers in multi machine power system. Intl. Conf. on Soft Computing and Intelligent Systems. pp: 214-219.
- Gupta R, Bandopadhya B and Kulkarni AM (2005) Power system stabilizer for multi machine power system using robust decentralized Periodic output feedback. IEE Proc.-Control Theory Appl. 152, 3–8.
- Hong-qi, L, Tai-hoon K and Shao-long X (2008) An improved PSO-based of harmony search for complicated optimization problems. Intl. J. Hybrid Information Technol. 1(1), 57-64.
- Hwanga GH, Kimb DW, Leec JH and Joo Y (2008) Design of fuzzy power system stabilizer using adaptive evolutionary algorithm. Engg. Appl. of Artificial Intelligence. 21, 86–96.
- Jiang P, Yan W and Weigu (2008) PSS parameter optimization with Harmony Search algorithm. DRPT 2008, Nanjing China. pp: 900-903.
- Kundur P (1993). Power system stability and control. McGraw-Hill, Inc., NY. pp: 700-822.
- Linda MM and Nair NK (2010) Dynamic stability enhancement with fuzzy based power system stabilizer tuned by hottest non-traditional optimization technique. 2nd Intl. Conf. on Computing, Communication and Networking Technologies. pp:1-5.
- Liu W, Venayagamoorthy GK and Wunsch DC (2005) A heuristic dynamic programming based power system stabilizer for a turbo generator in a single machine power system. IEEE Transact. Industry Appl. 4, 1377-1385.
- Mocwane K and Folly KA (2007) Robustness evaluation of H8 power system stabilizer. IEEE PES Power Africa Conference and Exhibition. pp: 16-20.
- Sil A, Gangopadhyay TK, Paul S and Maitra AK (2009) Design of robust power system stabilizer using H8 mixed sensitivity technique. Third Intl. Conf. on Power Systems, India. pp: 1- 4.
- Sudha KR, Vakula VS and Vijayasanthi R (2009) Particle swarm optimization in fine tuning of PID fuzzy logic power system stabilizer. Intl. Conf. on Advances in Computing, Control, and Telecommunication Technologies. pp: 356-358.
- Sumathi N, Selvan MP and Kumaresan N (2007) A hybrid Harmony Search algorithm based power system stabilizer. Intl. Conf. on Intelligent and Advanced Systems. pp: 876- 881.
- Verma A, Panigrahi BK and Bijwe PR (2010) Harmony search algorithm for transmission network expansion planning. IET Generation, Transmission & Distribution. 4, 663–673.
- Yassami H, Darabi A and Rafiei SMR (2010) Power system stabilizer design using strength pareto multiobjective optimization approach. Electric Power Systems Res. 80, 838–846.
- Harmony Search Algorithm for STATCOM Controllers Tuning in a Multi Machine Environment
Abstract Views :342 |
PDF Views:92
Authors
Sayed Mojtaba Shirvani Boroujeni
1,
Babak Keyvani Boroujeni
1,
Hamideh Delafkar
1,
Elahe Behzadipour
1,
Reza Hemmati
1
Affiliations
1 Department of Electrical Engineering, Boroujen Branch, Islamic Azad University, Boroujen, IR
1 Department of Electrical Engineering, Boroujen Branch, Islamic Azad University, Boroujen, IR
Source
Indian Journal of Science and Technology, Vol 4, No 9 (2011), Pagination: 1031-1035Abstract
This paper presents the application of static synchronous compensator (STATCOM) to voltage support in a multimachine electric power system. Harmony Search (HS) Algorithm as a meta-heuristic optimization method is considered for tuning the parameters of STATCOM. In order to evaluate the performance of STATCOM in voltage support, a multi-machine electric power system installed with STATCOM is considered as case study. The system under study is IEEE 14 bus standard system testing. The results are compared with the system without STATCOM. Several nonlinear time-domain simulation tests visibly show the ability of STATCOM in voltage support.Keywords
Static Synchronous Compensator, Voltage, Multi-machine Power System, Harmony Search, AlgorithmFull Text
References
- Chatterjee D and Ghosh A (2011) Improvement of transient stability of power systems with STATCOMcontroller using trajectory sensitivity. Intl. J. Electrical Power & Energy Systems. 33(3), 531-539.
- Furini MA, Pereira ALS and Araujo PB (2011) Pole placement by coordinated tuning of Power System Stabilizers and FACTS-POD stabilizers. Intl. J. Electrical Power & Energy Systems. 33(3), 615-622.
- Hemmati R, Shirvani Boroujeni SM, Behzadipour E and Delafkar H (2011) Supplementary stabilizer design based on STATCOM. Indian J. Sci.Technol. 4(5), 525-529.
- Hingorani NG and Gyugyi L (2000) Understanding FACTS. IEEE Press.
- Hong-qi L, Tai-hoon K and Shao- long X (2008) An improved PSO-based of harmony search for complicated optimization problems. Intl. J. Hybrid Info.Technol. (1), 57-64.
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- Shirvani Boroujeni SM, Keyvani Boroujeni B, Delafkar H and Safarnezhad Boroujeni A (2011) Harmony Search algorithm for power system stabilizer tuning. Indian J. Sci. Technol. 4 (9),1025-1030.
- Singh B, Murthy SS and Gupta S (2004) Analysis and design of STATCOM-based voltage regulator for selfexcited induction generators. IEEE Transact. on Energy Conversion. 19(4), 783-790.
- Slepchenkov MN, Smedley KM, and Wen J (2011) Hexagram-Converter-Based STATCOM for voltage support in fixed-speed wind turbine generation systems. IEEE Transact. on Industrial Electronics. 58(4), 1120–1131.
- Valderrábano A and Ramirez JM (2010) StatCom regulation by a fuzzy segmented PI controller. Electric Power Systems Res. 80(6), 707-715. Wang HF (1999) Phillips-Heffron model of power systems installed with STATCOM and applications. IEE Proc. Generation, Trans. and Distribution, 146 (5), 521-527.
- Harmony Search Algorithm for SVC Controller Tuning in Voltage Support Mode
Abstract Views :321 |
PDF Views:101
Authors
Sayed Mojtaba Shirvani Boroujeni
1,
Babak Keyvani Boroujeni
1,
Hamideh Delafkar
1,
Elahe Behzadipour
1,
Reza Hemmati
1
Affiliations
1 Department of Electrical Engineering, Boroujen Branch, Islamic Azad University, Boroujen, IR
1 Department of Electrical Engineering, Boroujen Branch, Islamic Azad University, Boroujen, IR
Source
Indian Journal of Science and Technology, Vol 4, No 9 (2011), Pagination: 1155-1159Abstract
Static Var Compensator (SVC) in one of the most widely used FACTS devices in industry and real world power systems. The problem of finding optimal values of SVC parameters has been studied for years. Many different methods have been carried out to design SVC controllers. But trying to find better controller is still remains. In this scope, Harmony Search (HS) Algorithms method as a meta-heuristic optimization method is considered for tuning the parameters of SVC. A multi machine electric power system is used to test viability of SVC in voltage support under disturbances. Simulation results on a multi machine power system show the ability of SVC in control of voltage as well as stability enhancement. The results are carried out by numerical simulations by using MATLAB software.Keywords
Static Var Compensator, Voltage Support, Multi-machine Power System, Harmony Search AlgorithmsFull Text
References
- Ahmed T, Noro O, Hiraki E and Nakaoka M (2004) Terminal voltage regulation characteristics by static var compensator for a three-phase self-excited induction generator. IEEE Transact. on Industry Appl. 40(4), 978–988.
- Bian XY, Tse CT, Zhang JF and Wang KW (2011) Coordinated design of probabilistic PSS and SVC damping controllers. Intl. J. Electrical Power & Energy Systems. 33(3), 445-452.
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- Power System Stabilizer Tuning in Multi Machine Electric Power Systems
Abstract Views :425 |
PDF Views:114
Authors
Affiliations
1 Department of Electrical Engineering, Boroujen Branch, Islamic Azad University, Boroujen, Iran
1 Department of Electrical Engineering, Boroujen Branch, Islamic Azad University, Boroujen, Iran
Source
Indian Journal of Science and Technology, Vol 4, No 12 (2011), Pagination: 1619-1623Abstract
Power System Stabilizers (PSS) are used to generate supplementary damping control signals for the excitation system in order to damp the Low Frequency Oscillations (LFO) of the electric power system. The PSS is usually designed based on classical control approaches but this Conventional PSS (CPSS) has some problems. The CPSS is usually designed based on a linear model of the plant for a particular operating point. However, power systems are inherently nonlinear and the operating point frequently changes. Therefore, CPSS performance may deteriorate under variations that result from nonlinear and time-variant characteristics of the controlled plant. In this paper, to develop a highperformance PSS for a wide range of operating conditions, meta-heuristic optimization methods such as Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) are used for tuning PSS parameters. The proposed optimization methods are evaluated against each other at a multi machine electric power system considering different loading conditions. The simulation results clearly indicate the effectiveness and validity of the proposed methods.Keywords
Multi Machine Power System, Low Frequency Oscillations, Particle Swarm Optimization, Power System StabilizerFull Text
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- Multi Machine Power System Identification by Using Recursive least Square Method
Abstract Views :496 |
PDF Views:101
Authors
Affiliations
1 Department of Electrical Engineering, Boroujen Branch, Islamic Azad University, Boroujen, Iran
1 Department of Electrical Engineering, Boroujen Branch, Islamic Azad University, Boroujen, Iran
Source
Indian Journal of Science and Technology, Vol 4, No 12 (2011), Pagination: 1624-1629Abstract
Electric power systems are nonlinear and complicate in nature. Along with increasing size of power systems, their complexity becomes more. Besides, by using additional and auxiliary components such as Flexible AC Transmission Systems (FACTS) devises, Power System Stabilizers (PSSs), excitation systems, turbine-governor systems and etc, the dynamic model of network is increased and power system becomes more complicate. The nonlinear dynamic model of these large power systems is easily obtained. But, the complexity makes it difficult to obtain a linear dynamic model of power system. Obtaining an appropriate linear model is necessary in order to analysis and study of power system. In tradition method, a linear dynamic model of power system is obtained by linearization of nonlinear dynamic model around an operating condition. But in large electric power systems, the linearization technique is very sophisticate and maybe impossible. Concerning this matter, in this paper a Recursive Least Square (RLS) technique is used to parameter identification in a multi machine electric power system. In this method a linear model is assumed for power system and its parameters are accurately computed by using RLS method. In order to verifying the results, the obtained linear model is compared with the nonlinear model. The simulation results show the validity of identified model, as the response of identified linear model is very near to nonlinear model.Keywords
Recursive Least Square, Multi Machine Electric Power System, Nonlinear Simulation, System IdentificationFull Text
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