Transmission Congestion Management using a Wind Integrated Compressed Air Energy Storage System

Authors

  • S. Gope Electrical Engineering Department, Mizoram University, Tanhril, Aizawl, Mizoram, India
  • A. K. Goswami Electrical Engineering Department, National Institute of Technology, Silchar, Assam, India
  • P. K. Tiwari Electrical Engineering Department, National Institute of Technology, Silchar, Assam, India
Volume: 7 | Issue: 4 | Pages: 1746-1752 | August 2017 | https://doi.org/10.48084/etasr.1316

Abstract

Transmission congestion is a vital problem in the power system security and reliability sector. To ensure the stable operation of the system, a congestion free power network is desirable. In this paper, a new Congestion Management (CM) technique, the Wind integrated Compressed Air Energy Storage (WCAES) system is used to alleviate transmission congestion and to minimize congestion mitigation cost. The CM problem has been solved by using the Generator Sensitivity Factor (GSF) and the Bus Sensitivity Factor (BSF). BSF is used for finding the optimal location of WCAES in the system. GSF with a Moth Flame Optimization (MFO) algorithm is used for rescheduling the generators to alleviate congestion and to minimize congestion cost by improving security margin. The impact of the WCAES system is tested with a 39 bus system. To validate this approach, the same problem has been solved with a Particle Swarm Optimization (PSO) algorithm and the obtained results are compared with the ones from the MFO algorithm.

Keywords:

wind farm, compressed air energy storage, bus sensitivity factor, generator sensitivity factor, moth flame optimization algorithm

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References

S. Dutta, S. P Singh, “Optimal rescheduling of generators for congestion management based on particle swarm optimization”, IEEE Transaction on Power System, Vol. 23, pp. 1560-1569, 2008 DOI: https://doi.org/10.1109/TPWRS.2008.922647

A. Kumar, C. Sekhar, “Congestion management with FACTS devices in deregulated electricity markets ensuring loadability limit”, Electrical Power and Energy Systems, Vol. 46, pp. 258-273, 2013 DOI: https://doi.org/10.1016/j.ijepes.2012.10.010

M. Esmaili, H. A. Shayanfar, R. Moslemi, “Locating series FACTS devices for multi-objective congestion management improving voltage and transient stability”, European Journal of Operational Research, Vol. 236, pp. 763-773, 2014 DOI: https://doi.org/10.1016/j.ejor.2014.01.017

A. Kumar, R. K. Mittapalli, “Congestion management with generic load model in hybrid electricity markets with FACTS devices”, Electrical Power and Energy Systems, Vol. 57, pp. 49-63, 2014 DOI: https://doi.org/10.1016/j.ijepes.2013.11.035

G. Yesuratnam, D. Thukaram, “Congestion management in open access based on relative electrical distances using voltage stability criteria,” Electrical Power Systems Research, Vol. 77, pp. 1608-1618, 2007 DOI: https://doi.org/10.1016/j.epsr.2006.11.007

A. Kumar, S. C. Srivastava, S. N. Singh, “A zonal congestion management approach using real and reactive power rescheduling”, IEEE Transaction on Power Systems, Vol. 19, pp. 554-562, 2004 DOI: https://doi.org/10.1109/TPWRS.2003.821448

A. Kumar, S. C. Srivastava, S. N. Singh, “Congestion management in competitive power market: A bibliographical survey”, Electrical Power Systems Research, Vol. 76, pp. 153-164, 2005 DOI: https://doi.org/10.1016/j.epsr.2005.05.001

C. Luo, Y. Hou, J. Wen, S. Cheng, “Assessment of Market Flows for Interregional Congestion Management in Electricity Markets”, IEEE Transactions on Power Systems, Vol. 29, pp. 1673-1682, 2014 DOI: https://doi.org/10.1109/TPWRS.2014.2297951

A. K. Singh, S. K. Parida, “Congestion management with distributed generation and its impact on electricity market”, Electrical Power and Energy Systems, Vol. 48, pp 39-47, 2013 DOI: https://doi.org/10.1016/j.ijepes.2012.11.025

S. Deb, S. Gope, A. K. Goswami, “Generator rescheduling for congestion management with incorporation of wind farm using artificial bee colony optimization technique”, IEEE India Conference, pp. 1-6, 2013 DOI: https://doi.org/10.1109/INDCON.2013.6726002

S. Deb, S. Gope, A. K. Goswami, “Congestion Management Considering Wind Energy Sources using Evolutionary Algorithm”, Electric Power Components and Systems, Vol. 43, pp. 723-732, 2015 DOI: https://doi.org/10.1080/15325008.2014.1002587

M. Ghofrani, A. Arabali, M. Etezadi-Amoli, M. S. Fadali, “A Framework for Optimal Placement of Energy Storage Units Within a Power System With High Wind Penetration”, IEEE Transactions on Sustainable Energy, Vol. 4, No. 2 , pp. 434-442, 2013 DOI: https://doi.org/10.1109/TSTE.2012.2227343

H. Lund, G. Salgi, B. Elmegaard, A. N. Andersen, “Optimal operation strategy of compressed air energy storage (CAES) on electricity spot market with fluctuating price”, Applied Thermal Engineering, Vol. 29, pp. 799-806, 2009 DOI: https://doi.org/10.1016/j.applthermaleng.2008.05.020

G. Grazzini, A. Milazzo, “Thermodynamic analysis of CAES/TES systems for renewable energy plants”, Renewable Energy, Vol. 33, pp. 1998–2006, 2008 DOI: https://doi.org/10.1016/j.renene.2007.12.003

H. Ibrahim, R. Younès, A. Ilinca, M. Dimitrova, J. Perron, “Study and design of a hybrid wind–diesel-compressed air energy storage system for remote areas”, Applied Energy, Vol. 87, pp. 1749–1762, 2010 DOI: https://doi.org/10.1016/j.apenergy.2009.10.017

S. Mirjalili, “Moth Flame Optimization Algorithm-A novel nature inspired heuristic paradigm”, Knowledge Based System, Vol. 89, pp. 228-249, 2015 DOI: https://doi.org/10.1016/j.knosys.2015.07.006

“Database: World temperatures- weather around the world”, available at www.timeanddate.com/weather

S. Dawn, P. K. Tiwari, “Improvement of economic profit by optimal allocation of TCSC & UPFC with wind power generators in double auction competitive power market”, Electric Power and Energy Systems, Vol. 80, pp. 190-201, 2016 DOI: https://doi.org/10.1016/j.ijepes.2016.01.041

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How to Cite

[1]
S. Gope, A. K. Goswami, and P. K. Tiwari, “Transmission Congestion Management using a Wind Integrated Compressed Air Energy Storage System”, Eng. Technol. Appl. Sci. Res., vol. 7, no. 4, pp. 1746–1752, Aug. 2017.

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