Abstract
For many decades, electric power systems have been faced with one of the major problems of optimizing the short-term operation of their resources. This problem is known in the electricity supply industry as the unit commitment (UC) problem. It consists of determining both the hourly schedule and economic dispatch of each supply-side resource over a period ranging from 1 day to approximately 1 week. The schedule of a resource specifies its hourly status (on-line or off-line), when it starts up and shuts down while the dispatch defines the output level of each operating resource. The upcoming changes in the electricity industry towards the development of competitive electricity markets in many countries has increased the importance for companies to dispose of unit commitment software enabling them to systematically analyze and formulate optimal bidding strategies. The solution has to minimize the sum of all operating costs while satisfying the equipment and operating constraints of the resources. The study period extends from 1 to 7 days.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Batut, J. and R.P. Sandrin (1990) ‘New Software for the Generation Rescheduling in the Future EDF National Control Center’, Proceedings of the 10th PSCC, Graz.
Dash Associates (1997a) XPRESS-MP Optimization Subroutine Library XOSL, Reference Manual.
Dash Associates (1997b) XPRESS-MP User Guide and Reference Manual.
Dash Associates (1998) XPRESS-MP Entity Modeling and Optimization Libraiy EMOSL, Reference Manual.
Happ, H.H., R.C. Johnson and W.J. Wright (1971) ‘Large Scale Unit Commitment Method and Results’, IEEE Transactions on PAS, PAS-90, No. 3, 1373–83.
Lekane T (1997) Memips Esprit Project 20118 - Workpackage 2: Tractebel Model Analysis Report and Solution Approaches #2’, DR 2.2.2, November.
Orero, S.O. and M.R. Irving (1997) Large Scale Unit Commitment using a Hybrid Genetic Algorithm’, Electrical Power and Energy Systems, 19(1), 45–55.
Pang, C.K., G.B. Sheble and F. Albuyeh (1981) ‘Evaluation of Dynamic Programming Based Methods and Multiple Area Representation for Thermal Unit Commitments’, IEEE Transactions on PAS, PAS-100, No. 3, 1212–18.
Wang, S.J., S.M. Shahidehpour, D.S. Kirschen, S. Mokhtari and G.D. Irisarri (1995) ‘Short-Term Generation Scheduling with Transmission and Environmental Constraints Using an Augmented Lagrangian-Relaxation’, IEEE Transactions on Power Systems, 10(3), 1294–1301.
Xiaohong, G, P.B. Luh and L. Zhang (1995) ‘Nonlinear Approximation Method in Lagrangian-Relaxation-Based Algorithms for Hydrothermal Scheduling’, IEEE Transactions on Power Systems, 10(2), 772–8.
Editor information
Editors and Affiliations
Copyright information
© 1999 Thomas Lekane and Jacques Gheury
About this chapter
Cite this chapter
Lekane, T., Gheury, J. (1999). Short-term Operation of an Electric-power System. In: Ciriani, T.A., Gliozzi, S., Johnson, E.L., Tadei, R. (eds) Operational Research in Industry. Palgrave Macmillan, London. https://doi.org/10.1057/9780230372924_14
Download citation
DOI: https://doi.org/10.1057/9780230372924_14
Publisher Name: Palgrave Macmillan, London
Print ISBN: 978-1-349-41051-4
Online ISBN: 978-0-230-37292-4
eBook Packages: Palgrave Business & Management CollectionBusiness and Management (R0)