CONGESTION MANAGEMENT IN DEREGULATED POWER SYSTEM INCORPORATING SOFT COMPUTING TECHNIQUES
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Mar 7, 2019
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Abstract
:In the competing power market, congestion is one of the technical concerns in transmission lines which threaten the system security. Its solution technique, congestion management is the most significant element of Independent System Operator (ISO). It is the responsibility of ISO to endorse a corrective action so as to alleviate congestion without disturbing the security of the system. Besides, the problem of congestion contributes to the electricity price surge that propagate incompetent market environment. Thus,the need for an exceptional solution technique that would take care ofall the risks in the power market,has become the need of the hour. One such solution methodology is proposed in this paper. Here, an optimization based solution methodology to relieve congestion both by rescheduling the generation as well as locating series FACTS device, Thyristor Controlled Series Compensator (TCSC) in the congested line is discussed. The proposed objective function being non-linear, is solved using Particle Swarm Optimization (PSO) and Biogeography Based Krill Herd (BBKH) algorithms. The effectiveness of both the optimization techniqueswas compared to various parameters. The proposed objective wasverified on IEEE 30 bus and Indian Utility 75 bus systems.
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[33] G.Sophia Jasmine, P.Vijayakumar, Congestion management in deregulated power system using heuristic search algorithms incorporating wireless technology, International Journal of wireless personal communications, 2017, 94(4), pp.2665-2680.
[2] Shahidepour Mohammed and Alomoush Muwaffaq, electrical power systems operation, trading and volatility, Marcel Dekker,Inc. New York; 2001.
[3] Kumar Ashwani, Srivastava S.C., Singh S.N, A zonal congestion management approach using real and reactive power rescheduling, IEEE Transactions on Power System, 2004, 19(1), pp.554- 562
[4] Baldick R. and Kahn E, Contract paths, phase shifters and efficient electricity trade, IEEE Transactions on Power System, 1997, 12 ( 2), pp.749-755.
[5] Deependra Singh and K.S.Verma, GA- based Congestion Management in Deregulated power system using Facts Devices’, Proceedings onIEEE International Conference on Utility Exhibitions on Power and Energy Systems, DOI.10.1109/ICUEPES.2011.6497716, 2011.
[6] Hadi Besharat, Syed abbas Taher, Congestion management by determining optimal location of TCSC in deregulated power systems, Electric Power and Energy Systems, 2008, 30, pp.563-568.
[7] Rahmat Allah Hooshmand, Mohammad Javad Morshed, Moein Parastegari, Congestion Management by determining optimal location of seires FACTS devices using hybrid bacterial foraging and Nelder-Mead, Applied Soft Computing, 2015, 28, pp. 57-58.
[8] Kirthika N., Balamurugan S, A new dynamic control strategy for power Transmission congestion management using series compensation, Electrical power and energy systems, Vol. 77, 271-279, 2016
[9] Shrestha G.B., Wang Feng, Effects of series compensation on spot price power markets, Electrical power and energy systems, 2005, 27, pp.428-436.
[10] Muneender E. and Vinod Kumar D.M, Optimal real and reactive power dispatch for zonal congestion management problem for multi congestion case using adaptive fuzzy PSO, Proceedings on IEEE conference TENCON 2009, DOI: 10.1109/TENCON.2009.5395934
[11] Muneender E. and Vinod Kumar D.M, A zonal congestion management using PSO and real coded genetic algorithm, IEEE conference on Power Systems and Expositions, DOI:978-1-4244- 3811-2/2009.
[12] Richa Bansal and Gupta S.K, TCDFs based congestion management using TCSC, Proceedings on IEEE Power India Conference, DOI: 10.1109/PowerI.2012.6479528.
[13] B.V.Manikandan, S.Charles Raja, P.Venkatesh and Manasarani Mandala, Comparitive study of two congestion management methods for therestructured power systems, Journal of electrical engineering and technology, 2011, 6(3) ,pp. 302-310
[14] Seyyed Ahmad Hosseini, Nima Amjady, Miadreza Shafie-khah, Joao P.S.Catalao, A new multi objective solution approach to solve transmission congestion management problem of energy markets, Applied Energy, 2016, l(165) pp. 462-471
[15] Partha Kayal, Sayonsom Chanda, Tunir Das, Abhishek Sen and C.K.Chanda, , Congestion management in transmission network on viewpoint of voltage stability enhancement, Proceedings on IEEE International conference on advances in power conversion and energy technologies, DOI: 10.1109/APCET.2012.6301992, 2012
[16] G.Yesuratnam, D.Thukaram, Congestion mangement in open access based on relative electrical distance using voltage stability criteria’, Electric Power Systems Research, 2007, 77, pp.1608-1618
[17] Acharya and N. Mithulananthan, Locating series FACTS devices for congestion management in deregulated electricity markets’, Electric power Systems Research, 2007, 77, pp. 352-360
[18] Manasarani Mandala and C.P.Gupta, Optimal placement of TCSC for transmission congestion management using hybrid optimization approach, Proceedings on IEEE International Conference on IT Convergence and Security, DOI: 10.1109/ICITCS.2013.6717865, 2013, pp:1-5
[19] Cai L.J., Erlich I, Optimal choice and allocation of FACTS devices using genetic algorithm, Proceedings on IEEE conference on Power Systems Conference and Exposition, DOI: 10.1109/PSCE.2004.1397562, 2004.
[20] UshaSurendra and Parthasarathy S.S, Congestion Management in Deregulated power sector using fuzzy based optimal location technique for series flexible alternative current transmission system (FACTS) device, Journal of Electrical and Electronics Research , 2012, 4(1) ,pp12-20.
[21] J.Kennedy, Eberhart R.C & Y. Shi, , Swarm Intelligence, Morgan Kaufman Publishers, SanFrancisco, 2001
[22] Bonabeau.E, M. Do Ringo and G.Theraulaz, Swarm Intelligence: from natural to artificialsystems, Oxford University Press, Santa Fe Institute studies in the Science of Complexity, 1999.
[23] Gai-Ge Wang, Amir H.Gandomi, Amir H.Alavi, An effective krill herd algorithm with migration operator in biogeography based optimization, Applied Mathematical Modelling, 2014, 38, pp. 2454-2462
[24] D.Simon, Biogeography based optimization, IEEE transactions on Evolutionary Comuting, 2008, 12(6), pp.702-713.
[25] Gandomi A.H., Alavi A.H, Krill herd: a new bio-inspired optimization algorithm, Communicationsin non-linear science and numerical simulation, 2012, 17 (12), pp. 4831-4845.
[26] Hingorani N.G. and L.Gyugyi, Understanding FACTS’, The Institution of Electrical and Electronics Engineers, 1998.
[27] Hingorani N.G, High Power electronics and flexible AC transmission system’, IEEE Power Eng Rev, July 1998.
[28] Rony Seto Wibowo, Naoto Yorino, Mehdi Eghbal, Yoshifumi Zoka, and Yutaka Sasaki, FACTS devices allocation with control coordination considering congestion relief and voltage stability, IEEE Transactions on Power Syst., 2011, 26(1), pp. 2302-2310.
[29] Gerbex S., Cherkaoui R. and Germond A.J, Optimal location of multi-type FACTS devices in a power system by means of genetic algorithms’, IEEE Trans. Power Systems, 2001, 16, pp. 537-344
[30] Lie T.T., Deng W, Optimal flexible AC transmission systems (FACTS) device allocation, , Electrical power and energy systems, 1997, 19 (2), pp.125-134
[31] G.Sophia Jasmine, P.Vijayakumar, Congestion management in competitive power market using TCSC, ARPN Journal of engineering and applied sciences, 2014, 10(9), pp. 4271-4274.
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[33] G.Sophia Jasmine, P.Vijayakumar, Congestion management in deregulated power system using heuristic search algorithms incorporating wireless technology, International Journal of wireless personal communications, 2017, 94(4), pp.2665-2680.