Congestion Management in Deregulated Electricity Market with Facts Devices using Firefly Algorithm
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2014 by IJETT Journal|
|Year of Publication : 2014|
|Authors : P.Mutharasu , R.M.Sasiraja
P.Mutharasu , R.M.Sasiraja . "Congestion Management in Deregulated Electricity Market with Facts Devices using Firefly Algorithm", International Journal of Engineering Trends and Technology (IJETT), V10(9),423-428 April 2014. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
The job of an self-governing system operator in a aggressive market atmosphere would be to make easy the total send off of the power that gets constricted among the market. With the development of an growing quantity of bilateral contracts being assigned for bazaar trades, the opportunity of inadequate property primary to group congestion may be inevitable. Real-time congestion in transmission line can be defined as the working situation in which present is not sufficient transmission potential to apply all the traded communication concurrently due to a number of unpredicted contingencies. Firefly algorithms is assigned to locate best solutions of piercing non-linear uninterrupted mathematical designs. Firefly Algorithm is solitary of the current elapsing designs which is encouraged by fireflies actions in environment. A sequence of elapsing experiments by every algorithm were studied. The outcome of this testing were understand and compared to the optimal solutions set up consequently far-off on the origin of signify of completing moment to join to the most favorable. The Firefly algorithm seems to execute superior for advanced mode of noise.
 Glavitsch H, Alavardo F. Management of multiple congested conditions in unbundled operation of a power system. IEEE Trans Power Syst 1998,13(3), 1013–9.
 Christie RD, Wollenberg BF, Wangstien I. Transmission management in the deregulated environment. Proc IEEE 2000,88(2),170–95.
 Alomoush MI, Shahidehpour SM. Contingency-constrained congestion management with a minimum number of adjustments in preferred schedules. Int J Electr Power Energy Syst 2000,22(4),277–90.
 Wang X, Song YH. Apply Lagrangian relaxation to multi-zone congestion management. In: Proc of IEEE PES, winter meeting, 2001. p. 309–314.
 Wang X, Song YH, Lu Q. Lagrangian decomposition approach to active power congestion management across interconnected regions. IEE Proc Gener, Transm, Distrib 2001,148(5),497–503.
 Bompard E, Correia P, Gross G, Amelin M. Congestion-management schemes: a comparative analysis under a unified framework. IEEE Trans Power Syst 2003,18(1),346–52.
 Yamin HY, Shahidehpour SM. Transmission congestion and voltage profile management coordination in competitive electricity markets. Int J Electr Power Energy Syst 2003,25(10),849 61.
 Kumar Ashwani, Srivastava SC, Singh SN. Congestion management in competitive electricity markets – a bibliographical survey. Electr Power Syst Res 2005,76(4),153–64.
 Kumar Ashwani, Srivastava SC, Singh SN. A zonal congestion management approach using real and reactive power rescheduling. IEEE Trans Power Syst2004,18(1),554–62.
 Kumar A, Srivastava SC, Singh SN. A zonal congestion management approach using AC transmission congestion distribution factors. Electr Power Syst Res 2004,72(11),85–93.
 Chanana S, Kumar Ashwani. Power flow contribution factors based congestion management with real and reactive power bids in competitive electricity markets. In: Porc IEEE PEDES. New Delhi, 2007. p. 1–8.
 Rania Hassan, Babak Cohanim, Olivier de Weck, A Comparison of the Particle Swarm Algorithm and the Genetic Algorithm, published by AIAA, 2004.
 Bajeh, A. O., Abolarinwa, K. O., A Comparative Study of Genetic and Tabu Search Algorithms, International Journal of Computer Applications, 2011.
 Xin-She Yang, Chaos-Enhanced Firefly Algorithm with Automatic Parameter Tuning, International Journal of Swarm Intelligence Research, December 2011.
 Xiang-yin Meng, Yu-long Hu, Yuan-hang Hou, Wen-quan Wang, The Analysis of Chaotic Particle Swarm Optimization and the Application in Preliminary Design of Ship”, International Conference on Mechatronics and Automation, August, 2010.
Flexible AC Transmission system(FACTS), unified power flow controller(UPFC),30 bus system, firefly algorithm.