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Multiobjective Improved Particle Swarm Optimisation for Transmission Congestion and Voltage Profile Management using Multilevel UPFC Cover

Multiobjective Improved Particle Swarm Optimisation for Transmission Congestion and Voltage Profile Management using Multilevel UPFC

Open Access
|Nov 2019

References

  1. Albatsh, F. M., Mekhilef, S., Ahmad, S. and Mokhlis, H. (2017). Fuzzy-Logic-Based UPFC and Laboratory Prototype Validation for Dynamic Power Flow Control in Transmission Lines. IEEE Transactions on Industrial Electronics, 64(12), pp. 9538–9548.10.1109/TIE.2017.2711546
  2. Batra, I. and Ghosh, S. (2018). An Improved Tent Map-Adaptive Chaotic Particle Swarm Optimization (ITM-CPSO)-Based Novel Approach Toward Security Constraint Optimal Congestion Management. Iranian Journal of Science and Technology, Transactions of Electrical Engineering, pp. 1–29.10.1007/s40998-018-0072-6
  3. Dutta, S. and Singh, S. P. (2008). Optimal Rescheduling of Generators for Congestion Management Based on Particle Swarm Optimization. IEEE Transactions on Power Systems, 23(4), pp. 1560–1569.10.1109/TPWRS.2008.922647
  4. Guan, M. and Xu, Z. (2012). Modeling and Control of A Modular Multilevel Converter-Based HVDC System Under Unbalanced Grid Conditions. IEEE Transactions on Power Electronics, 27(2), pp. 4858–4867.10.1109/TPEL.2012.2192752
  5. Gyugyi, L. (2003). Unified Power-Flow Control Concept for Flexible AC Transmission Systems Generation. Proceedings of Transmission Distribution Conference, 139, pp. 323–331.10.1049/ip-c.1992.0048
  6. Hajforoosh, S., Nabavi, S. M. and Masoum, M. A. (2012). Coordinated Aggregated-Based Particle Swarm Optimisation Algorithm for Congestion Management in Restructured Power Market by Placement and Sizing of Unified Power Flow Controller. IET Science, Measurement & Technology, 6(4), pp. 267–278.10.1049/iet-smt.2011.0143
  7. Hao, Q., Man, J., Gao, F. and Guan, M. (2018). Voltage Limit Control of Modular Multilevel Converter Based Unified Power Flow Controller Under Unbalanced Grid Conditions. IEEE Transactions on Power Delivery, 33(3), pp. 1319–1327.10.1109/TPWRD.2017.2736562
  8. Jordehi, A. R. (2015). Particle Swarm Optimisation (PSO) for Allocation of FACTS Devices in Electric Transmission Systems: A Review. Renewable and Sustainable Energy Reviews, 52, pp. 1260–1267.10.1016/j.rser.2015.08.007
  9. Kapse, S. S. S., Daigavane, M. B. and Daigavane, P. M. (2018). Improvement of ORPD Algorithm for Transmission Loss Minimization and Voltage Control Using UPFC by HGAPSO Approach. Journal of the Institution of Engineers (India): Series B, pp. 1–11.
  10. Kumar, A. and Sekhar, C. (2013). Congestion Management with FACTS Devices in Deregulated Electricity Markets Ensuring Loadability Limit. International Journal of Electrical Power & Energy Systems, 46, pp. 258–273.10.1016/j.ijepes.2012.10.010
  11. Kumar, A., Srivastava, S. C. and Singh, S. N. (2005). Congestion Management in a Competitive Power Market: A Bibliographical Survey. Electric Power Systems Research, 76(1–3), pp. 153–164.10.1016/j.epsr.2005.05.001
  12. Mishra, A. and Kumar Gundavarapu, V. N. (2016). Line Utilisation Factor-Based Optimal Allocation of IPFC and Sizing Using Firefly Algorithm for Congestion Management. IET Generation Transmission and Distribution, 10(1), pp. 115–122.10.1049/iet-gtd.2015.0493
  13. Mukherjee, V. and Verma, S. (2016). Optimal Real Power Rescheduling of Generators for Congestion Management Using A Novel Ant Lion Optimiser. IET Generation Transmission and Distribution, 10(10), pp. 2548–2561.10.1049/iet-gtd.2015.1555
  14. Panigrahi, B. K. and Ravikumar Pandi, V. (2009). Congestion management using adaptive bacterial foraging algorithm. Energy Conversion and Management, 50(5), pp. 1202–1209.10.1016/j.enconman.2009.01.029
  15. Pillay, A., Karthikeyan, S. P. and Kothari, D. P. (2015). Congestion Management in Power Systems – A Review. International Journal of Electrical Power & Energy Systems, 70, pp. 83–90.10.1016/j.ijepes.2015.01.022
  16. Pratap, R., Mukherjee, V. and Ghoshal, S. P. (2016). Particle Swarm Optimization with an Aging Leader and Challengers Algorithm for the Solution of Optimal Power Flow Problem. Applied Soft Computing Journal, 40, pp. 161–177.10.1016/j.asoc.2015.11.027
  17. Raj, S. and Bhattacharyya, B. (2018). Optimal Placement of TCSC and SVC for Reactive Power Planning Using Whale Optimization Algorithm. Swarm and Evolutionary Computation, 40, pp. 131–143.10.1016/j.swevo.2017.12.008
  18. Singh, K., Yadav, V. K., Padhy, N. P. and Sharma, J. (2014). Congestion Management Considering Optimal Placement of Distributed Generator in Deregulated Power System Networks. Electric Power Components and Systems, 42(1), pp. 13–22.10.1080/15325008.2013.843218
  19. Tu, Q., Xu, Z. and Xu, L. (2011). Reduced Switching-Frequency Modulation and Circulating Current Suppression for Modular Multilevel Converters. IEEE Transactions on Power Delivery, 26(3), pp. 2009–2017.10.1109/TPWRD.2011.2115258
  20. Venkaiah, C. and Vinod Kumar, D. M. (2011). Fuzzy Adaptive Bacterial Foraging Congestion Management Using Sensitivity Based Optimal Active Power Re-Scheduling of Generators. Applied Soft Computing Journal, 11(8), pp. 4921–4930.10.1016/j.asoc.2011.06.007
  21. Wang, J. and Peng, F. Z. (2004). Unified Power Flow Controller Using the Cascade Multilevel Inverter. IEEE Transactions on Power Electronics, 19(4), pp. 1077–1084.10.1109/TPEL.2004.830073
  22. Yamin, H. Y. and Shahidehpour, S. M. (2003). Transmission Congestion and Voltage Profile Management Coordination in Competitive Electricity Markets. International Journal of Electrical Power & Energy Systems, 25(10), pp. 849–861.10.1016/S0142-0615(03)00070-X
DOI: https://doi.org/10.2478/pead-2019-0005 | Journal eISSN: 2543-4292 | Journal ISSN: 2451-0262
Language: English
Page range: 79 - 93
Submitted on: Dec 13, 2018
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Accepted on: Feb 9, 2019
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Published on: Nov 26, 2019
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2019 Mallavolu Malleswara Rao, Geetha Ramadas, published by Wroclaw University of Science and Technology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.