Multi-Area Unit Commitment Using Particle Swarm Optimization Approach

S. Chitra Selvi(1*), M. Bala Singh Moses(2), C. Christober Asir Rajan(3)

(1) Anna University, Chennai, India
(2) Anna University, Chennai, India
(3) Anna University, Chennai, India
(*) Corresponding author


DOI's assignment:
the author of the article can submit here a request for assignment of a DOI number to this resource!
Cost of the service: euros 10,00 (for a DOI)

Abstract


This paper presents a novel approach to solve the Multi-Area unit commitment problem using particle swarm optimization algorithm. The objective of the multi-area unit commitment problem is to determine the optimal or a near optimal commitment strategy for generating units located in multiple areas that are interconnected via tie –lines. This strategy of multi-area joint operation of generation resources can result in significant operational cost savings. The dynamic programming method is applied to solve Multi- Area Unit Commitment problem and particle swarm optimization algorithm which is embedded for assigning optimum generation. The optimum allocation of generation is assigned to each area and the power is allocated to all committed units. The tie-line transfer limitations are considered as a set of constraints during the optimization process to ensure the system security and reliability. IEEE test systems are used as numerical examples to test the proposed algorithm. The feasibility of the new algorithm is demonstrated by the numerical example, and particle swarm optimization solution methodology is efficient than other algorithms.
Copyright © 2013 Praise Worthy Prize - All rights reserved.

Keywords


Multi-Area Unit Commitment; Evolutionary Programming; Particle Swarm Optimization; Dynamic Programming

Full Text:

PDF


References


S.K.Tong, and S.M.Shahidehpour, “Combination of Legrange relaxation and linear programming approaches for fuel constrained unit commitment problem,”IEEE proceedings .C, vol.136, No.3, pp, 162-174, 1989.

Z.Ouyang, and S.M.Shahidehpour, “Short term unit commitment expert system,” Electric Power. Syst Research, vol.20, No.1, pp. 1-13, 1990.

S.K.Tong., M.Shahidehpour, and Z.Ouyang.,“A heuristic a short –term unit commitment ,” IEEE Trans. Power Syst, vol.6, No.3, 1991.

Van Den Bosch, and G.Honderd, “A solution of the unit commitment problem via decomposition and dynamic programming,” IEEE Trans. Power Syst, vol.104, No.7, pp 1684-1690, 1985.

A.J.Wood., and Wollenberg: B.F.: Power generation, operation and Control, John Wiley, New York, 1984.

H.H.Happ, “The inter-area matrix: a tie flow model for power pools”, IEEE Trans. Power. Syst, vol .90, No.4, pp. 36-45, 1971.

R.R Shouts., S.K.Chang., S. Helmick., and W.M. Grady., “A practical approach to unit commitment, economic dispatch and savings allocation for multiple-area pool operation with import/export constraints”, IEEE Trans. Power Systs, vol .99, No.2, pp.625 – 635, 1980.

H.T. Yang, P. C.Yang, and C.L.Huang, "Evolutionary Economic dispatch for Units with Non-smooth fuel Cost Functions,” IEEE Trans. Power Syst, vol. 11 . No.2, pp.112-118, 1996.

Z. Ouyang, and S.M.Shahidehpour, “Heuristic multi-area unit commitment with economic dispatch,” IEEE Proceedings, vol.138, No.3, pp 242-252. 1991.

C-L.Tseng.: “Multi-area unit commitment for large scale power system” IEEE Proceedings - Gener. Distrib. vol. 145, No.41, pp.415- 421, 1998.

C.Wang, and M.Shahidehpour, “A decomposition approach to non-linear Multi-area generation scheduling with tie-line constraints using expert systems ,” IEEE Trans. Power Syst ,vol. 7, No.4, pp.1409 -1418,1992.

C.K.Pang, G.B.Sheble, and F.Albuyeh, “Evaluation of dynamic programming based methods and multiple area representation for thermal unit commitments, ” IEEE Trans. Power Syst, vol.100, No.3, pp. 1212-1218, 1981.

C.Wang and S.M.Shahidepur , “ Application of the equivalent area to multi-area generation scheduling with tie-line constraints,” Electrical Power and Energy Syst ,Vol.14,No.4,pp.264-274 ,1992.

F.N.Lee, J.Huang, and R.Adapa, “Multi-area unit commitment via sequential method and a DC power flow network model,” IEEE Trans. Power Syst, vol. 9, No.1, 279- 284, 1994.

Chitra Yingvivatanapong, Wei-Jen Lee and Edwin Liu., “Multi-Area Power Generation Dispatch in Competitive Markets,” IEEE Trans. Power Syst, 2008.

U. B. Fogel, “ On the Philosophical Differences between Evolutionary Algorithms and Genetic Algorithms," IEEE Proceedindings second annual conference on Evolutionary Programming, pp. 23-29.1993.

T. Biick, and H. P. Schwefel, An Overview of evolutionary Algorithm for Parameter Optimization, Evolutionary Computation, vol. 1, No. 1, pp.1-24, 1993.

Q.H.Wu, and J.T.Ma, “ Power System Optimal Reactive Power Dispatch using Evolutionary Programming,” IEEE Trans. Power Syst, vol. 10, No.3, pp, 1243-1249, 1995.

C.Christober Asir Rajan, and M.R.Mohan, “ An evolutionary programming- based Tabu Search method for solving the Unit Commitment problem,” IEEE Trans. Power Syst, vol.19, No. 1, pp .577-585, 2004.

D.Srinivasan, F.Wen, and C.S.Chang, “ A Survey of Applications Evolutionary Computing to Power Systems,” IEEE Procs, USA, pp, 35-41,1996.

J.Kennedy, R. Eberhart, “Particle swarm optimization, “ IEEE Proceedings of the Inter-national Conference on Neural Networks; Perth, Australia: pp-1942–1948,1995.

TAA.Victoire, AE.Jeyakumar, Deterministically guided PSO for dynamic dispatch considering valve-point effects. Electric Power System Research; vol 3No3 :pp- 313–322. 2005

J.Kennedy,“The particle swarm: Social adaptation of know-ledge.” IEEE proceedings International Conference on Evolutionary Computation; Indianapolis:pp- 303-308,1997.

G.Ciuprina, D.Ioan, I.Munteanu,Use of intelligent-particle swarm optimization in electromagnetics. IEEE Trans Mag-netics;vol 38 No 4: 1037-1040,2002.

Vladimiro Miranda and Nuno Fonseca, EPSO Evolutionary self- adapting Particle Swarm optimization, internal report INESC Porto, July 2001.

Rashidinejad, M., Khorasani, H., Rashidinejad, A., Transmission expansion planning in restructured electricity industry using a hybrid heuristic technique, (2010) International Review on Modelling and Simulations (IREMOS), 3 (3), pp. 283-289.

Ganesan, S., Subramanian, S., A novel hybrid method for thermal unit commitment problems, (2010) International Review on Modelling and Simulations (IREMOS), 3 (4), pp. 694-704.

Shafighi, A.R., Jahani, R., Fazli, M., Shayanfar, H.A., Bathaee, S.M.T., A new approach for optimal unit commitment of large scale power system, (2010) International Review on Modelling and Simulations (IREMOS), 3 (5), pp. 870-875.

Nejad, H.C., Jahani, R., Shayanfar, H.A., Olamaei, J., Comparison of novel heuristic technique and other evolutionary methods for optimal unit commitment of power system, (2010) International Review on Modelling and Simulations (IREMOS), 3 (6), pp. 1476-1482.

Barzegari, A., Barforoushi, T., Asgharpour, H., Lesan, S., A new algorithm based on particle swarm optimization for solving power economic dispatch considering valve-point effects and emission constraints, (2011) International Review on Modelling and Simulations (IREMOS), 4 (3), pp. 1303-1311.

Zadeh, A.K., Ameli, M.T., Ehsani, A., Bidding strategy of generating companies in simultaneous energy and spinning reserve markets, (2011) International Review on Modelling and Simulations (IREMOS), 4 (5), pp. 2402-2409.

Ganesan, S., Subramanian, S., Direct search method for solving dynamic economic dispatch problems, (2011) International Review on Modelling and Simulations (IREMOS), 4 (1), pp. 93-103.


Refbacks

  • There are currently no refbacks.



Please send any question about this web site to info@praiseworthyprize.com
Copyright © 2005-2022 Praise Worthy Prize