A Modified on-Line Rolling Generation Dispatch Model for Accommodating Large-Scale Wind Power

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This paper proposes an improved strategy for on-line rolling generation dispatch. Based on the framework of Lagrange dual relaxation, the problem is transformed and decomposed into primal-problem and N subproblems multipliers and system constrains are satisfied iteratively. The sub-problems are solved by an efficient dynamic programming algorithm without changing the condition of convergence of the framework. Numerical results indicate that the proposed method is fast and efficient in dealing with numerous system constrains.

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569-572

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June 2013

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] M.E. El-hawary and G.S. Christtensen: Optimal economic operation of electric power system. New York, NY, US. Academic Press (1979).

Google Scholar

[2] ZHANG Boming, WU Wenchuan, ZHENG Taiyi, et al: Design of a multi-time scale coordinated active power dispatching system for accommodating large scale wind power penetration. Automation of Electric Power Systems. 35 (1). (2011),pp.1-6

DOI: 10.1109/pesgm.2012.6344832

Google Scholar

[3] SHEN Wei, WU Wenchuan, ZHANG Boming, ZHENG Taiyi and SUN Hongbin: An on-line rolling dispatch method and model for accommodating large-scale wind power. Automation of Electric Power Systems.35 (22). (2011),p.136

DOI: 10.1109/powercon.2010.5666420

Google Scholar

[4] R.R. Shoults, S.K. Chang, S. Helmick, et al: A practical approach to unit commitment, economic dispatch, and savings allocation for multiple-area pool operation with import/export constrains. IEEE Trans on Power Apparatus and Systems. 99(2). (1980), pp.625-635

DOI: 10.1109/tpas.1980.319654

Google Scholar

[5] Tseng Chung-li, S.O. Shmuel, A.J. Svoboda, et al: A unit decommitment method in power system scheduling. Electrical Power and Energy Systems. 19(6). (1997), pp.357-365

DOI: 10.1016/s0142-0615(96)00055-5

Google Scholar

[6] C. Wang, S.M. Shahidepour: A decomposition approach to non-linear multi-area generation scheduling with tie-line constraints using expert systems. IEEE Trans on Power Systems. 19(6). (1992), pp.1409-1418

DOI: 10.1109/59.207362

Google Scholar

[7] WANG Mingliang, ZHANG Boming, XIA Qing: A novel unit commitment method considering various operation constraints. Automation of Electric Power Systems. 24(12). (2000), pp.29-35

DOI: 10.1109/pesw.2000.847621

Google Scholar

[8] O. Weerakorn, P. Nit: Unit commitment by enhanced adaptive Lagrangian relaxation. IEEE Trans on Power Systems. 19(1). (2004), pp.620-628

DOI: 10.1109/tpwrs.2003.820707

Google Scholar

[9] F. Antonio, G. Claudio. Solving nonlinear single-unit commitment problems with ramping constrains. Operations Research. 54(4). (2006), pp.767-775

DOI: 10.1287/opre.1060.0309

Google Scholar

[10] F. Antonio, G. Claudio, L. Fabrizio: Solving unit commitment problems with general ramp constrains. Electrical Power and Energy Systems. 30(5). (2008), pp.316-326

DOI: 10.1016/j.ijepes.2007.10.003

Google Scholar

[11] A. Bakirtzis, V. Petridis, S. Kazarlis: Genetic algorithm solution to the economic dispatch problem. IEEE Proceedings: Generation, Transmission and Distribution. 141(4). (1994), pp.377-382

DOI: 10.1049/ip-gtd:19941211

Google Scholar

[12] C.L. Chen: Simulated anneal-based optimal wind-thermal coordination scheduling. IET Generation, Transmission and Distribution. 1(3). (2007), pp.447-455

DOI: 10.1049/iet-gtd:20060208

Google Scholar

[13] A.I. Selvakumar, K. Thanushkodi: A new particle swarm optimization solution to nonconvex economic dispatch problems. 22(1). (2007), pp.42-51

DOI: 10.1109/tpwrs.2006.889132

Google Scholar

[14] L.S. Coelho, V.C. Mariani: Combining of chaoic differential evolution and quadratic programming for economic dispatch optimization with value-point effect. 21(2). (2006), pp.989-996

DOI: 10.1109/tpwrs.2006.873410

Google Scholar