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RETRACTED ARTICLE: Dynamic stability enhancement of interconnected multi-source power systems using hierarchical ANFIS controller-TCSC based on multi-objective PSO

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This article was retracted on 21 May 2019

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Abstract

Suppression of the dynamic oscillations of tie-line power exchanges and frequency in the affected interconnected power systems due to loading-condition changes has been assigned as a prominent duty of automatic generation control (AGC). To alleviate the system oscillation resulting from such load changes, implementation of flexible AC transmission systems (FACTSs) can be considered as one of the practical and effective solutions. In this paper, a thyristor-controlled series compensator (TCSC), which is one series type of the FACTS family, is used to augment the overall dynamic performance of a multi-area multi-source interconnected power system. To this end, we have used a hierarchical adaptive neuro-fuzzy inference system controller-TCSC (HANFISC-TCSC) to abate the two important issues in multi-area interconnected power systems, i.e., low-frequency oscillations and tie-line power exchange deviations. For this purpose, a multi-objective optimization technique is inevitable. Multi-objective particle swarm optimization (MOPSO) has been chosen for this optimization problem, owing to its high performance in untangling non-linear objectives. The efficiency of the suggested HANFISC-TCSC has been precisely evaluated and compared with that of the conventional MOPSO-TCSC in two different multi-area interconnected power systems, i.e., two-area hydro-thermal-diesel and three-area hydro-thermal power systems. The simulation results obtained from both power systems have transparently certified the high performance of HANFISC-TCSC compared to the conventional MOPSO-TCSC.

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Change history

  • 21 May 2019

    The Editors-in-Chief have retracted this article of Falehi and Mosallanejad (2017) because of significant overlap with a previous publication by the same authors (Falehi and Mosallanejad 2016). Ali Darvish Falehi disagrees with this retraction. Ali Mosanellanejad did not respond to any correspondence about this retraction.

References

  • Abd-Elazim, S.M., Ali, E.S., 2016. Load frequency controller design via BAT algorithm for nonlinear interconnected power system. Int. J. Electr. Power Energy Syst., 77: 166–177. http://dx.doi.org/10.1016/j.ijepes.2015.11.029

    Article  Google Scholar 

  • Abd-Elaziz, A.Y., Ali, E.S., 2015. Cuckoo search algorithm based load frequency controller design for nonlinear interconnected power system. Int. J. Electr. Power Energy Syst., 73: 632–643. http://dx.doi.org/10.1016/j.ijepes.2015.05.050

    Article  Google Scholar 

  • Ali, E.S., Abd-Elazim, S.M., 2011. Bacteria foraging optimization algorithm based load frequency controller for interconnected power system. Int. J. Electr. Power Energy Syst., 33(3): 633–638. http://dx.doi.org/10.1016/j.ijepes.2010.12.022

    Article  Google Scholar 

  • Ali, E.S., Abd-Elazim, S.M., 2013. BFOA based design of PID controller for two area load frequency control with nonlinearities. Int. J. Electr. Power Energy Syst., 51: 224–231. http://dx.doi.org/10.1016/j.ijepes.2013.02.030

    Article  Google Scholar 

  • Benabid, R., Boudour, M., Abido, M.A., 2009. Optimal location and setting of SVC and TCSC devices using non-dominated sorting particle swarm optimization. Electr. Power Syst. Res., 79(12): 1668–1677. http://dx.doi.org/10.1016/j.epsr.2009.07.004

    Article  Google Scholar 

  • Benítez, A.D., Casillas, J., 2013. Multi-objective genetic learning of serial hierarchical fuzzy systems for large-scale problems. Soft Comput., 17(1): 165–194. http://dx.doi.org/10.1007/s00500-012-0909-2

    Article  Google Scholar 

  • Bevrani, H., Hiyama, T., Mitani, Y., 2008. Power system dynamic stability and voltage regulation enhancement using an optimal gain vector. Contr. Eng. Pract., 16(9): 1109–1119. http://dx.doi.org/10.1016/j.conengprac.2008.01.001

    Article  Google Scholar 

  • Cai, L., Erlich, I., 2005. Simultaneous coordinated tuning of PSS and FACTS damping controllers in large power systems. IEEE Trans. Power Syst., 20(1): 294–300. http://dx.doi.org/10.1109/TPWRS.2004.841177

    Article  Google Scholar 

  • Chaudhuri, B., Pal, B., 2004. Robust damping of multiple swings modes employing global stabilizing signals with TCSC. IEEE Trans. Power Syst., 19(1): 499–506. http://dx.doi.org/10.1109/TPWRS.2003.821463

    Article  MathSciNet  Google Scholar 

  • Chaudhuri, B., Pal, B., Zolotas, A.C., 2003. Mixed-sensitivity approach to H∞ control of power system oscillations employing multiple FACTS devices. IEEE Trans. Power Syst., 18(3): 1149–1156. http://dx.doi.org/10.1109/TPWRS.2003.811311

    Article  Google Scholar 

  • Dash, P.K., Morris, S., Mishra, S., 2004. Design of a nonlinear variable-gain fuzzy controller for FACTS devices. IEEE Trans. Contr. Syst. Technol., 12(3): 428–438. http://dx.doi.org/10.1109/TCST.2004.824332

    Article  Google Scholar 

  • del Rosso, A.D., Canizares, C.A., Dona, V.M., 2003. A study of TCSC controller design for power system stability improvement. IEEE Trans. Power Syst. 18(4): 1487–1496. http://dx.doi.org/10.1109/TPWRS.2003.818703

    Article  Google Scholar 

  • Divya, K.C., Nagendra Rao, P.S., 2005. A simulation model for AGC studies of hydro-hydro systems. Int. J. Electr. Power Energy Syst., 27(5–6): 335–342. http://dx.doi.org/10.1016/j.ijepes.2004.12.004

    Article  Google Scholar 

  • Eberhart, R.C., Shi, Y.H., Kennedy, J., 2001. Swarm Intelligence. Academic Press, San Diego, CA.

    Google Scholar 

  • Elshafei, A.L., El-Metwally, K.A., Shaltout, A.A., 2005. A variable-structure adaptive fuzzy-logic stabilizer for single and multi-machine power systems. Contr. Eng. Pract., 13(4): 413–423. http://dx.doi.org/10.1016/j.conengprac.2004.03.017

    Article  Google Scholar 

  • Falehi, A.D., 2012. Simultaneous coordinated design of TCSC-based damping controller and AVR based on PSO technique. Electr. Rev., 88(5): 136–140.

    Google Scholar 

  • Falehi, A.D., 2013. Design and scrutiny of maiden PSS for alleviation of power system oscillations using RCGA and PSO techniques. J. Electr. Eng. Technol., 8(3): 402–410. http://dx.doi.org/10.5370/JEET.2013.8.3.402

    Article  Google Scholar 

  • Falehi, A.D., Rostami, M., 2011. Design and analysis of a novel dual-input PSS for damping of power system oscillations employing RCGA-optimization technique. Int. Rev. Electr. Eng., 6(2): 938–945.

    Google Scholar 

  • Falehi, A.D., Dankoob, A., Amirkhan, S., et al., 2011. Coordinated design of STATCOM-based damping controller and dual-input PSS to improve transient stability of power system. Int. Rev. Electr. Eng., 6(3): 1308–1318.

    Google Scholar 

  • Falehi, A.D., Rostami, M., Doroudi, A., et al., 2012. Optimization and coordination of SVC-based supplementary controllers and PSSs to improve the power system stability using genetic algorithm. Turk. J. Electr. Eng. Comput. Sci., 20(5): 639–654. http://dx.doi.org/10.3906/elk-1010-838

    Google Scholar 

  • Goshal, S.P., 2004. Optimization of PID gains by particle swarm optimization in fuzzy based automatic generation control. Electr. Power Syst. Res., 72(3): 203–212. http://dx.doi.org/10.1016/j.epsr.2004.04.004

    Article  Google Scholar 

  • Gyugyi, L., 1992. Unified power-flow control concept for flexible AC transmission systems. IEE Proc. C, 139(4): 323–331. http://dx.doi.org/10.1049/ip-c.1992.0048

    Google Scholar 

  • Gyugyi, L., Schauder, C.D., Sen, K.K., 1997. Static synchronous series compensator: a solid-state approach to the series compensation of transmission lines. IEEE Trans Power Del., 12(1): 406–417. http://dx.doi.org/10.1109/61.568265

    Article  Google Scholar 

  • Hingorani, N.G., Gyugyi, L., 2000. Understanding FACTS: Concepts and Technology of Flexible AC Transmission Systems. IEEE Press, New York.

    Google Scholar 

  • Iracleous, D.P., Alexandridis, A.T., 2005. A multi-task automatic generation control for power regulation. Electr. Power Syst. Res., 73(3): 275–285. http://dx.doi.org/10.1016/j.epsr.2004.06.011

    Article  Google Scholar 

  • Jang, J.S.R., 1993. ANFIS: adaptive-network-based fuzzy inference system. IEEE Trans. Syst. Man Cybern., 23(3): 665–685. http://dx.doi.org/10.1109/21.256541

    Article  Google Scholar 

  • Karnavas, Y.L., Papadopoulos, D.P., 2000. Excitation control of a power-generating system based on fuzzy logic and neural networks. Int. Trans. Electr. Energy Syst., 10(4): 233–241. http://dx.doi.org/10.1002/etep.4450100406

    Google Scholar 

  • Kazemi, A., Jahed Motlagh, M.R., Naghshbandy, A.H., 2007. Application of a new multi-variable feedback linearization method for improvement of power systems transient stability. Int. J. Electr. Power Energy Syst., 29(4): 322–328. http://dx.doi.org/10.1016/j.ijepes.2006.07.011

    Article  Google Scholar 

  • Kikuchi, H., Otake, A., Nakanishi, S., 1998. Functional completeness of hierarchical fuzzy modeling. Inform. Sci., 110(1–2): 51–60. http://dx.doi.org/10.1016/S0020-0255(97)10076-7

    Article  MathSciNet  Google Scholar 

  • Kundur, P., Klein, M., Rogers, G.J., et al., 1989. Application of power system stabilizers for enhancement of overall system stability. IEEE Trans. Power Syst., 4(2): 614–626. http://dx.doi.org/10.1109/59.193836

    Article  Google Scholar 

  • Larsen, E.V., Sanchez-Gasca, J.J., Chow, J.H., 1995. Concepts of design of FACTS controllers to damp power swings. IEEE Trans. Power Syst., 10(2): 948–956. http://dx.doi.org/10.1109/59.387938

    Article  Google Scholar 

  • Lee, M.L., Chung, H.Y., Yu, F.M., 2003. Modeling of hierarchical fuzzy systems. Fuzzy Sets Syst., 138(2): 343–361. http://dx.doi.org/10.1016/S0165-0114(02)00517-1

    Article  MathSciNet  Google Scholar 

  • Li, B.H., Wu, Q.H., Turner, D.R., et al., 2000. Modeling of TCSC dynamics for control and analysis of power system stability. Int. J. Electr. Power Energy Syst., 22(1): 43–49. http://dx.doi.org/10.1016/S0142-0615(99)00037-X

    Article  Google Scholar 

  • Mattavelli, P., Verghese, G.C., Stankovic, A.M., 1997. Phasor dynamics of thyristor-controlled series capacitor systems. IEEE Trans. Power Syst., 12(3): 1259–1267. http://dx.doi.org/10.1109/59.630469

    Article  Google Scholar 

  • Moradi, A., Shirazi, K.H., Keshavarz, M., et al., 2014. Smart piezoelectric patch in non-linear beam: design, vibration control and optimal location. Trans. Instit. Meas. Contr., 36(1): 131–144. http://dx.doi.org/10.1177/0142331213495041

    Article  Google Scholar 

  • Panda, S., Padhy, N.P., 2008. Comparison of particle swarm optimization and genetic algorithm for FACTS-based controller design. Appl. Soft Comput., 8(4): 1418–1427. http://dx.doi.org/10.1016/j.asoc.2007.10.009

    Article  Google Scholar 

  • Raju, G., Zhou, J., Kisner, R., 1991. Hierarchical fuzzy control. Int. J. Contr., 54(5): 1201–1216. http://dx.doi.org/10.1080/00207179108934205

    Article  MathSciNet  MATH  Google Scholar 

  • Rojas, I., Bernier, J.L., Rodriguez-Alvarez, R., et al., 2000. What are the main functional blocks involved in the design of adaptive neuro-fuzzy inference systems? IEEEINNS-ENNS Int. Joint Conf. on Neural Networks, p.551–556. http://dx.doi.org/10.1109/IJCNN.2000.859453

    Google Scholar 

  • Soliman, H.M., Dabroum, A., Mahmoud, M.S., et al., 2011. Guaranteed-cost reliable control with regional pole placement of a power system. J. Franklin Instit., 348(5): 884–898. http://dx.doi.org/10.1016/j.jfranklin.2011.02.013

    Article  MATH  Google Scholar 

  • Takagi, T., Sugeno, M., 1983. Derivation of fuzzy control rules from human operator’s control actions. IFAC Symp. on Fuzzy Information, Knowledge Representation and Decision Analysis, p.55–60.

    Google Scholar 

  • Talaat, H.E.A., Abdennour, A., Al-Sulaiman, A.A., 2010. Design and experimental investigation of a decentralized GA-optimized neuro-fuzzy power system stabilizer. Int. J. Electr. Power Energy Syst., 32(7): 751–759. http://dx.doi.org/10.1016/j.ijepes.2010.01.011

    Article  Google Scholar 

  • Tan, W., Xu, Z., 2009. Robust analysis and design of load frequency controller for power systems. Electr. Power Syst. Res., 79(5): 846–853. http://dx.doi.org/10.1016/j.epsr.2008.11.005

    Article  Google Scholar 

  • Zhang, Y., Zhou, Q., Sun, C.X., et al., 2008. RBF neural network and ANFIS-based short-term load forecasting approach in real-time price environment. IEEE Trans. Power Syst., 23(3): 853–858. http://dx.doi.org/10.1109/TPWRS.2008.922249

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Electrical Engineering, Shahid Beheshti University, Tehran, 1983963113, Iran

    Ali Darvish Falehi & Ali Mosallanejad

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  1. Ali Darvish Falehi
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  2. Ali Mosallanejad
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Correspondence to Ali Darvish Falehi.

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The Editors-in-Chief have retracted this article Falehi and Mosallanejad (2017) because of significant overlap with a previous publication by the same authors (Falehi and Mosallanejad 2016). Ali Darvish Falehi disagrees with this retraction. Ali Mosanellanejad did not respond to any correspondence about this retraction.

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Falehi, A.D., Mosallanejad, A. RETRACTED ARTICLE: Dynamic stability enhancement of interconnected multi-source power systems using hierarchical ANFIS controller-TCSC based on multi-objective PSO. J. Zhejiang Univ. - Sci. C 18, 394–409 (2017). https://doi.org/10.1631/FITEE.1500317

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