Economic Transmission Planning Model Suitable for a Regulated Network Service Provider
Publication: Journal of Energy Engineering
Volume 135, Issue 3
Abstract
Conventional transmission planning models are subject to constant debate in the context of competitive markets, due to the functional unbundling of transmission sector from generation and distribution sectors and due to the new environment regulations. A value-based transmission planning model is proposed, suitable for an unbundled transmission network service provider having no assets in the generation sector. The model minimizes the long-term transmission investment costs and the expected social costs incurred to its clients, energy producers, and consumers, in the power auctions due to transmission bottlenecks. The uncertainties involved when incorporating short-term market models into long-term planning models are modeled with probabilistic representations for the bid prices, the component availabilities, and the hourly load variations. These features make this model suitable in the new environment paradigm. Generalized Benders decomposition technique with nonsequential Monte Carlo technique is employed to solve the final stochastic mixed-integer optimization model. Case studies are given to illustrate the performance of this model by implementing it in the modified Garver’s six-bus test system and the IEEE 24-bus reliability test system for a single planning year.
Get full access to this article
View all available purchase options and get full access to this article.
References
Abdelaziz, A. R. (2000). “Genetic algorithm-based power transmission expansion planning.” Proc., 7th Int. Conf. on Electronics, Circuits, and Systems, Lebanon, 642–645.
Barmack, M., Griffes, P., Kahn, E., and Oren, S. (2003). “Performance incentives for transmission.” Electr. J., 16(3), 9–22.
Benders, J. F. (1962). “Partitioning procedures for solving mixed variables programming problems.” Numer. Math., 4, 238–252.
Binato, S., Pereira, M. V. F., and Granville, S. (2001). “A new Benders decomposition approach to solve power transmission network design problems.” IEEE Trans. Power Syst., 16(2), 235–240.
Chebbo, H. M., and Irving, M. R. (1997). “Application of genetic algorithms to transmission planning.” Proc., 2nd Int. Conf. on Genetic Algorithms in Engineering Systems: Innovations and Applications, Glasgow, Pub. No. 446.
Crousillat, E. O., Dorfner, P., Alvarado, F., and Hyde, H. M. (1993). “Conflicting objectives and risk in power system planning.” IEEE Trans. Power Syst., 8(3), 887–893.
Da Silva, E. L., Gil, H. A., and Areiza, J. M. (2000). “Transmission network expansion planning under an improved genetic algorithm.” IEEE Trans. Power Syst., 15(3), 1168–1174.
Da Silva, E. L., Oritz, J. M. A., De Oliveira, G. C., and Binato, S. (2001). “Transmission network expansion planning under a tabu search approach.” IEEE Trans. Power Syst., 16(1), 62–68.
David, A. K., and Fushun, W. (2001). “Transmission planning and investment under competitive electricity market environment.” Proc., IEEE PES Summer Meeting, IEEE, Vancouver, Canada, 1725–1730.
De la Torre, T., Feltes, J. W., Roman, T. G. S., and Hyde, H. M. (1999). “Deregulation, privatization, and competition: Transmission planning under uncertainty.” IEEE Trans. Power Syst., 14(2), 460–465.
Dusonchet, Y. P., and El-Abiad, A. H. (1973). “Transmission planning using discrete dynamic optimization.” IEEE Trans. Power Appar. Syst., PAS-92, 1358–1371.
Gallego, R. A., Alves, A. B., Monticelli, A., and Romero, R. (1997). “Parallel simulated annealing applied to long term transmission network expansion planning.” IEEE Trans. Power Syst., 12(1), 181–188.
Garver, L. L. (1970). “Transmission network estimation using linear programming.”IEEE Trans. Power Syst., PAS-89(7), 1688–1697.
Geoffrion, A. M. (1972). “Generalized benders decomposition.” J. Optim. Theory Appl., 10(4), 237–260.
Matlab Software Optimization Toolbox user’s guide. (2003). The Mathworks, Inc., Natick, Mass.
McCusker, S. A., Hobbs, B. F., and Li, Y. (2002). “Distributed utility planning using probabilistic production costing and generalized benders decomposition.” IEEE Trans. Power Syst., 17(2), 497–505.
Reliability Test System Task Force of the Application of Probability Methods Subcommittee. (1999). “The IEEE reliability test system-1996.” IEEE Trans. Power Syst., 14(3), 1010–1020.
Romero, R., Gallego, R. A., and Monticelli, A. (1996). “Transmission system expansion planning by simulated annealing.” IEEE Trans. Power Syst., 11(1), 364–369.
Romero, R., and Monticelli, A. (1994a). “A hierarchical decomposition approach for transmission network expansion planning.” IEEE Trans. Power Syst., 9(1), 373–380.
Romero, R., and Monticelli, A. (1994b). “A zero-one implicit enumeration method for optimizing investments in transmission expansion planning.” IEEE Trans. Power Syst., 9(3), 1385–1391.
Sauma, E. E., and Oren, S. S. (2006). “Proactive planning and valuation of transmission investments in restructured electricity markets.” J. Regul. Econ., 30(3), 358–387.
Shrestha, G. B., and Fonseka, P. A. J. (2004). “Congestion-driven transmission expansion in competitive power markets.” IEEE Trans. Power Syst., 19(3), 1658–1665.
Siddiqi, S. N. (1993). “Reliability differentiated pricing and optimal planning for electrical power systems.” Ph.D. dissertation, Fac. of Grad. School, Univ. of Texas at Austin, Austin, Tex.
Siddiqi, S. N., and Baughman, M. L. (1993). “Reliability differentiated real-time pricing of electricity.” IEEE Trans. Power Syst., 8(2), 548–554.
Villasana, R., Garver, L. L., and Salon, S. L. (1985). “Transmission network planning using linear programming.” IEEE Trans. Power Appar. Syst., PAS-104(2), 349–356.
Information & Authors
Information
Published In
Journal of Energy Engineering
Volume 135 • Issue 3 • September 2009
Pages: 64 - 72
Copyright
© 2009 ASCE.
History
Received: May 6, 2008
Accepted: Dec 11, 2008
Published online: Aug 14, 2009
Published in print: Sep 2009
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.