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Tabar, Mohammad Bigdeli
- Comparison of Robust Control Methods Performance in the UPFC Controllers Design
Abstract Views :369 |
PDF Views:95
Authors
Mehdi Nikzad
1,
Shoorangiz Shams Shamsabad Farahani
1,
Mehdi Ghasemi Naraghi
1,
Mohammad Bigdeli Tabar
1,
Ali Javadian
1
Affiliations
1 Department of Electrical Engineering, Islamic Azad University, Islamshahr Branch, Tehran, P. O. Box 3135-369, IR
1 Department of Electrical Engineering, Islamic Azad University, Islamshahr Branch, Tehran, P. O. Box 3135-369, IR
Source
Indian Journal of Science and Technology, Vol 4, No 6 (2011), Pagination: 670-676Abstract
The Unified Power Flow Controller (UPFC) integrates properties of shunt and series compensations and can effectively alters power system parameters in a way that increases power transfer capability and stabilizes system. Simple Proportional-Integral (PI) controllers are applied to UPFC as usual controllers, but parameters of PI controllers are usually tuned based on the trial-and-error approaches and they are incapable to obtain a good dynamic performance under a wide range of operating conditions. To solve this problem, robust control methods are proposed to design UPFC controllers. Also a supplementary damping controller to increase damping of power system oscillations is developed. A Single-Machine Infinite Bus (SMIB) power system installed with a UPFC with system parametric uncertainties is considered as case study. The system parametric uncertainties are obtained by 40% changing parameters from their typical values. Proposed methods are compared with each other to show their effectiveness and robustness. The objectives are to study and comparison robust control methods performance for UPFC control problem.Keywords
Flexible AC Transmission Systems, Unified Power Flow Controller, μ-synthesis, H∞ Loop-shapingFull Text
References
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- Taher SA, Akbari SH, Abdoalipour A and Hematti R (2010) Robust decentralized controller design for UPFC controllers using µ synthesis. Commun. in Non Linear Sci. & Numerical Simulation. 15, 2149-2161.
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- Comparison of Meta Heuristic Optimization Methods in Load Frequency Control
Abstract Views :450 |
PDF Views:106
Authors
Mehdi Nikzad
1,
Shoorangiz Shams Shamsabad Farahani
1,
Mehdi Ghasemi Naraghi
1,
Mohammad Bigdeli Tabar
1,
Ali Javadian
1
Affiliations
1 Department of Electrical Engineering, Islamshahr Branch, Islamic Azad University, Tehran, IR
1 Department of Electrical Engineering, Islamshahr Branch, Islamic Azad University, Tehran, IR
Source
Indian Journal of Science and Technology, Vol 4, No 7 (2011), Pagination: 792-795Abstract
In this paper an optimal load frequency controller for two area interconnected power system is presented to quench the deviations in frequency and tie line power due to different load disturbances. Here, a PI type controller is considered for LFC problem. The parameters of the proposed PI controller are tuned using Particle Swarm Optimization (PSO) method. A two-area electric power system with a wide range of parametric uncertainties is given to illustrate proposed method. To show effectiveness of the proposed method, a PI type controller optimized by Genetic Algorithms (GA) is designed in order to comparison with the proposed PI controller. The simulation results visibly show the validity of PSO-PI controller in comparison with the GA-PI controller.Keywords
Load Frequency Control, Two Area Electric Power System, Particle Swarm Optimization, Genetic Algorithms, PI ControllerFull Text
References
- Kocaarslan I and Cam E (2005) Fuzzy logic controller in interconnected electrical power systems for load-frequency control. Electrical Power & Energy Systems. 27, 542–549.
- Liu F, Song YH, Ma J, Mai S and Lu Q (2003) Optimal load frequency control in restructured power systems. IEE Proc. Generation, Transmissions & Distribution. 150(1), 87-95.
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- Rerkpreedapong D, Hasanovic A and Feliachi A (2003) Robust load frequency control using genetic algorithms and linear mmatrix inequalities. IEEE Transactions Power Systems. 18(2), 855-861.
- Shayeghi H, Shayanfar HA and Malik OP (2007) Robust decentralized neural networks based LFC in a deregulated power system. Electric Power Systems Res. 77, 241–251.
- Taher SA and Hematti R (2008) Robust decentralized load frequency control using multi variable QFT method in deregulated power systems. Am. J. Appl. Sci. 5(7), 818-828.
- 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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- Zribi M, Al-Rashed M and Alrifai M (2005) Adaptive decentralized load frequency control of multi-area power systems. Electrical Power & Energy Systems. 27, 575–583.
- Dynamic Stability Enhancement of Power System Using STATCOM
Abstract Views :453 |
PDF Views:132
Authors
Shoorangiz Shams Shamsabad Farahani
1,
Mehdi Nikzad
2,
Mohammad Bigdeli Tabar
2,
Behrang Yousefpour
2,
Hossein Tourang
2
Affiliations
1 Department of Electrical Engineering, Islamshahr Branch, Islamic Azad University, Tehran, IR
2 Department of Electrical Engineering, Islamshahr Branch, Islamic Azad University, Tehran
1 Department of Electrical Engineering, Islamshahr Branch, Islamic Azad University, Tehran, IR
2 Department of Electrical Engineering, Islamshahr Branch, Islamic Azad University, Tehran
Source
Indian Journal of Science and Technology, Vol 4, No 11 (2011), Pagination: 1551-1555Abstract
In this paper multi-objective tuning of a supplementary stabilizer for Static Synchronous Compensator (STATCOM) is presented. A meta-heuristic optimization method named genetic algorithms (GA) is used for tuning the parameters of the proposed stabilizer. The potential of the GA for optimal setting of the proposed stabilizer are investigated. The stabilizer is designed to shift slightly damped and undammed electromechanical modes of power system. The validity of the proposed method is verified on a single-machine infinite-bus power system (SMIB) installed with a STATCOM. Several linear time-domain simulation tests visibly show the validity of proposed method in damping of power system oscillations.Keywords
Flexible AC Transmission Systems, Static Synchronous Compensator, Low Frequency Oscillations, Genetic Algorithms, Power System StabilizerFull Text
References
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- Mehdi Nikzad, Shoorangiz Shams Shamsabad Farahani, Mohammad Bigdeli Tabar, Mehdi Ghasemi Naraghi and Ali Javadian (2011) Adjustment of PSS in a multi machine power system based on particle swarm optimization technique. Indian J.Sci.Technol. 4 (8), 876-880.
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- Shoorangiz Shams Shamsabad Farahani, Mehdi Nikzad, Mohammad Bigdeli Tabar, Mehdi Ghasemi Naraghi and Ali Javadian (2011a) Multi-machine power system stabilizer adjustment using genetic algorithms. Indian J.Sci.Technol. 4 (8), 881-885. Domain site: http://www.indjst.org.
- Shoorangiz Shams Shamsabad Farahani, Mehdi Nikzad, Mohammad Bigdeli Tabar, Mehdi Ghasemi Naraghi and Ali Javadian (2011b) Multi-machine power system stabilizer adjustment using Simulated Annealing. Indian J.Sci.Technol. 4 (8), 886-889.
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- Adjustment of PSS in a Multi Machine Power System Based on Particle Swarm Optimization Technique
Abstract Views :473 |
PDF Views:86
Authors
Mehdi Nikzad
1,
Shoorangiz Shams Shamsabad Farahani
1,
Mohammad Bigdeli Tabar
1,
Mehdi Ghasemi Naraghi
1,
Ali Javadian
1
Affiliations
1 Department of Electrical Engineering, Islamshahr Branch, Islamic Azad University, Tehran, IR
1 Department of Electrical Engineering, Islamshahr Branch, Islamic Azad University, Tehran, IR
Source
Indian Journal of Science and Technology, Vol 4, No 8 (2011), Pagination: 876-880Abstract
The tuning of the PSS parameters for a multi-machine power system is usually formulated as an objective function with constraints consisting of the damping factor and damping ratio. A novel Meta heuristic optimization method, called particle swarm optimization method (PSO), is proposed to solve this kind of problem. An objective function based on the integral of the error is incorporated. The IEEE 14 bus standard power system, under various system configurations, is employed to illustrate the performance of the proposed method. Nonlinear time domain simulation results demonstrate the effectiveness of the proposed algorithm and the objective function with a remote signal.Keywords
Multi Machine Electric Power System, Power System Stabilizer, Particle Swarm OptimizaFull 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 genetic algorithm based fuzzy logic power system stabilizers in multi machine power system. Intl. 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.
- 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 Intl. Conf. on Computing, Commun. & 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. on Industry Appl. 4,1377-1385.
- Mocwane K and Folly KA (2007) Robustness evaluation of H8 power system stabilizer. IEEE PES Power Africa Conf. & Exhibition. pp: 16-20.
- Randy LH and Sue EH (2004) Practical genetic algorithms. 2nd Edition, John Wiley & Sons. pp: 25-67.
- 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 genetic algorithm based power system stabilizer. Intl. Conf. on Intelligent & Adv. 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.
- Multi-Machine Power System Stabilizer Adjustment Using Genetic Algorithms
Abstract Views :496 |
PDF Views:79
Authors
Shoorangiz Shams Shamsabad Farahani
1,
Mehdi Nikzad
1,
Mohammad Bigdeli Tabar
1,
Mehdi Ghasemi Naraghi
1,
Ali Javadian
1
Affiliations
1 Department of Electrical Engineering, Islamshahr Branch, Islamic Azad University, Tehran, IR
1 Department of Electrical Engineering, Islamshahr Branch, Islamic Azad University, Tehran, IR
Source
Indian Journal of Science and Technology, Vol 4, No 8 (2011), Pagination: 881-885Abstract
In this paper, the problem of tuning lead-lag power system stabilizer parameters of a multi machine power system is considered. This problem is formulated as an optimization problem, which is solved using Genetic Algorithms (GA). Simulation results show the effectiveness of the proposed Genetic Algorithms-based lead-lag power system stabilizer to damp the oscillation of multimachine system and work effectively under variable loading and fault conditions. The proposed GA-PSS is evaluated on the IEEE 14 bus test system as a multi machine electric power system.Keywords
Multi Machine Electric Power System, Power System Stabilizer, Genetic AlgorithmsFull 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 genetic algorithm based fuzzy logic power system stabilizers in multi machine power system. Intl. Conf. on Soft Computing & Intelligent Systems. pp: 214-219.
- El-Zonkoly AM, Khalil AA and Ahmied NM (2009) Optimal tuning of lead-lag and fuzzy logic power system stabilizers using particle swarm optimization. Expert Systems with Applications. 36. 2097–2106.
- 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 App. 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 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. Second Intl. 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 Transact. on Industry Appl. 4,1377-1385.
- Mocwane K and Folly KA (2007) Robustness evaluation of H8 power system stabilizer. IEEE PES Power Africa Conf. & Exhibition. pp: 16-20.
- Nikzad M, Shams Shamsabad Farahani S, Bigdeli Tabar M, Ghasemi Naraghi M and Javadian A (Aug 2011) Adjustment of PSS in a multi machine power system based on particle swarm optimization technique. Indian Journal of Science and Technology. 4(8), 1-5.
- Randy LH and Sue EH (2004) Practical genetic algorithms. 2nd Edition, John Wiley & Sons. pp: 25-67.
- 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 genetic algorithm based power system stabilizer. Intl. Conf. on Intelligent & Adv. 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.
- Multi-Machine Power System Stabilizer Adjustment Using Simulated Annealing
Abstract Views :574 |
PDF Views:82
Authors
Shoorangiz Shams Shamsabad Farahani
1,
Mehdi Nikzad
1,
Mohammad Bigdeli Tabar
1,
Mehdi Ghasemi Naraghi
1,
Ali Javadian
1
Affiliations
1 Department of Electrical Engineering, Islamshahr Branch, Islamic Azad University, Tehran, IR
1 Department of Electrical Engineering, Islamshahr Branch, Islamic Azad University, Tehran, IR
Source
Indian Journal of Science and Technology, Vol 4, No 8 (2011), Pagination: 886-889Abstract
In this paper, the authors are willing to find the optimal and robust design for power system stabilizers (PSSs) in a multi-machine power system. In this regard a new Meta heuristic method as Simulated Annealing (SA) is used. The PSS parameters are computed to assure maximum damping performance under different scenarios. A multi machine electric power system is used to illustrative the performance of proposed method. The efficacy of this technique in damping local and inter-area modes of oscillations in multimachine power systems is confirmed through nonlinear simulation results. Simulation results are carried out by numerical simulations on MATLAB software.Keywords
Multi Machine, Power System Stabilizer, Low Frequency Oscillations, Simulated AnnealingFull Text
References
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