A solution to stochastic unit commitment problem for a wind-thermal system coordination

doi:10.1007/s11708-014-0306-x

Front. Energy

2014, Vol. 8

Issue (2) : 192-200 https://doi.org/10.1007/s11708-014-0306-x

RESEARCH ARTICLE

A solution to stochastic unit commitment problem for a wind-thermal system coordination

B. SARAVANAN(

),Shreya MISHRA,Debrupa NAG

School of Electrical Engineering, VIT University, Vellore 632014, India

Download: PDF(131 KB) HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks

Abstract

Unit commitment (UC) problem is one of the most important decision making problems in power system. In this paper the UC problem is solved by considering it as a real time problem by adding stochasticity in the generation side because of wind-thermal co-ordination system as well as stochasticity in the load side by incorporating the randomness of the load. The most important issue that needs to be addressed is the achievement of an economic unit commitment solution after solving UC as a real time problem. This paper proposes a hybrid approach to solve the stochastic unit commitment problem considering the volatile nature of wind and formulating the UC problem as a chance constrained problem in which the load is met with high probability over the entire time period.

Keywords unit commitment (UC) randomness wind generation univariate chance constrained

Corresponding Author(s): B. SARAVANAN

Issue Date: 19 May 2014

Cite this article:

B. SARAVANAN,Shreya MISHRA,Debrupa NAG. A solution to stochastic unit commitment problem for a wind-thermal system coordination[J]. Front. Energy, 2014, 8(2): 192-200.

URL:

https://academic.hep.com.cn/fie/EN/10.1007/s11708-014-0306-x
https://academic.hep.com.cn/fie/EN/Y2014/V8/I2/192

Fig.1 Flowchart

Tab.1 Input data for the 10 unit thermal system [9]

Tab.2 Load data for 24 h [9] (Case 1)

Tab.3 Available wind data for 24 h [11]

Tab.4 UC schedule for Case 1

Tab.5 Economic dispatch for Case 1

Tab.6 Mean and standard deviation of load for Case 2

Tab.7 UC schedule for Case 2

Tab.8 Economic dispatch result for Case 2

Tab.9 Validation of proposed algorithm

1	OzturkU A, MazumdarM, NormanB A. A Solution to the stochastic unit commitment problem using chance constrained programming. IEEE Transactions on Power Systems, 2004, 19(3): 1589–1598 doi: 10.1109/TPWRS.2004.831651
2	BurnsR M, GibsonC A. Optimization of priority lists for a unit commitment program. In: IEEE/PES Summer Meeting, New York: Institute of Electrical and Electronics Engineers, 1975, Paper A 75 453–1
3	SenjyuT, MiyagiT, SaberA Y, UrasakiN, FunabashiT.Emerging solution of large-scale unit commitment problem byStochastic Priority List. Electric Power Systems Research, 2006, 76(5): 283–292 doi: 10.1016/j.epsr.2005.07.002
4	OuyangZ, ShahidehpourS M. An intelligent dynamic programming for unit commitment application. IEEE Transactions on Power Systems, 1991, 6(3): 1203–1209 doi: 10.1109/59.119267
5	CohenA I, YoshimuraM. A branch-and-bound algorithm for unit commitment. IEEE Transactions on Power Apparatus and Systems, 1983, PAS-102(2): 444–451 doi: 10.1109/TPAS.1983.317714
6	WangY, XiaQ, KangC. A novel security stochastic unit commitment for wind-thermal system operation. In: Proceedings of the 4th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT). Weihai, China, 2011, 386–393
7	ChenC L. Optimal wind-thermal generating unit commitment. IEEE Transactions on Energy Conversion, 2008, 23(1): 273–280 doi: 10.1109/TEC.2007.914188
8	EbrahimiJ, HosseinianS H, GharehpetianG B. Unit commitment problem solution using shuffled frog leaping algorithm. IEEE Transactions on Power Systems, 2011, 26(2): 573–581 doi: 10.1109/TPWRS.2010.2052639
9	EslamianM, HosseinianS H, VahidiB. Bacterial foraging-based solution to the unit-commitment problem. IEEE Transactions on Power Systems, 2009, 24(3): 1478–1488 doi: 10.1109/TPWRS.2009.2021216
10	LeeT Y. Optimal spinning reserve for a wind-thermal power system using EIPSO. IEEE Transactions on Power Systems, 2007, 22(4): 1612–1621 doi: 10.1109/TPWRS.2007.907519
11	DaneshiH, SrivastavaA K. Security-constrained unit commitment with wind generation and compressed air energy storage. IET Generation, Transmission & Distribution, 2012, 6(2): 167–175 doi: 10.1049/iet-gtd.2010.0763
12	WoodJ, WollenbergB F. Power Generation, Operation & Control. John Wiley & Sons, Inc., 1996
13	PappalaV S, ErlichI, RohrigK, DobschinskiJ. A stochastic model for the optimal operation of a wind-thermal power system. IEEE Transactions on Power Systems, 2009, 24(2): 940–950 doi: 10.1109/TPWRS.2009.2016504
14	UmmelsB C, GibescuM, PelgrumE, KlingW L, BrandA J. Impacts of wind power on thermal generation unit commitment and dispatch. IEEE Transactions on Energy Conversion, 2007, 22(1): 44–51 doi: 10.1109/TEC.2006.889616
15	LogenthiranT, SrinivasanD. Particle swarm optimization for unit commitment Problem. In: 2010 IEEE 11th International Conference on Probabilistic Methods Applied to Power Systems (PMAPS). Singapore, 2010, 642–647
16	SriyanyongP, SongY H. Unit commitment using particle swarm optimization combined with Lagrange relaxation. In: 2005 IEEE Power Engineering Society General Meeting. San Francisco, USA, 2005, 2752–2759
17	HargreavesJ J, HobbsB F. Commitment and dispatch with uncertain wind generation by dynamic programming. IEEE Transactions on sustainable energy, 2012, 3(4): 724–734
18	SaravananB, DasS, SikriS, KothariD P. A solution to the unit commitment problem–a review. Frontiers in Energy, 2013, 7(2): 223–236
19	SaravananB, SikriS, SwarupK S, KothariD P. Unit commitment using dynamic programming–an exhaustive working of both classical and stochastic approach. Frontiers in Energy, 2013, 7(3): 333–341
20	SaravananB, VasudevanE R, KothariD P. A solution to unit commitment problem using invasive weed optimization algorithm. Frontiers in Energy, 2013, 7(4): 487–494

[1]	Balasubramaniyan SARAVANAN, Surbhi SIKRI, K. S. SWARUP, D. P. KOTHARI. Unit commitment using dynamic programming–an exhaustive working of both classical and stochastic approach[J]. Front Energ, 2013, 7(3): 333-341.
[2]	B. SARAVANAN, Siddharth DAS, Surbhi SIKRI, D. P. KOTHARI. A solution to the unit commitment problem—a review[J]. Front Energ, 2013, 7(2): 223-236.

Viewed

Full text

Abstract

Cited

Shared

Discussed