Abstract
The objective of this work is to present a decision support system that determines the optimal dispatch strategy of thermal power plants while considering the particular specifications of fuel supply agreements, such as take-or-pay and make-up clauses. Opportunities for energy purchase and selling at the spot market as well as a detailed modeling of the power plant (maintenance cycles, influence of temperature, etc.) are also considered during the optimization. In an integrated approach, the model also determines the plants’ optimal schedule for maintenance. Since decisions in a stage have an impact in the future stages, the problem is time-coupled with a multi-stage framework. Moreover, the main driver for the decision-making is the energy spot price, which is unknown in the future and is modeled in this tool through user-defined scenarios. Therefore, the calculation of the optimal dispatch strategy is modeled as a decision under uncertainty problem, where at each stage the objective is to determine the optimal operation strategy that maximizes the total revenues taking into account the constraints and characteristics of the fuel supply contract. The methodology applied is a hybrid Stochastic Dual Dynamic Programming (SDDP)/Stochastic Dynamic Programming (SDP). Examples and case studies will be analyzed for the Brazilian system.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Barroso, L. A., Flach, B., Kelman, R., Binato, S., Bressane, J. M., & Pereira, M. (2005). Integrated gas-electricity adequacy planning in Brazil: technical and economical aspects. Proceedings of the IEEE General Meeting, San Francisco.
Chabar, R. M. (2005). Otimização da operação e manutenção de usinas termelétricas sob incerteza em sistemas hidrotérmicos MSc Dissertation, PUC-Rio, (jn Portuguese).
Flatabo, N., Haugstad, A., Mo, B., & Fosso, O. (1998). Short and medium-term generation scheduling in the Norwegian hydro system under a competitive power market. Proceedings of EPSOM Conference.
Granville, S., Kelman, R., Barroso, L. A., Chabar, R., Pereira, M. V., Lino, P., Xavier, P., & Capanema, I. (2003a). Um sistema integrado para gerenciamento de riscos em mercados de energia elétrica. XVII SNPTEE, Uberlândia, (in Portuguese).
Granville, S., Oliveira, G. C., Thomé, L. M., Campodónico, N., Latorre, M., Pereira, M. V., & Barroso, L. A. (2003b). Stochastic optimization of transmission constrained and large scale hydrothermal systems in a competitive framework. Proceedings of the IEEE General Meeting, Toronto. Available at http://www.psr-inc.com.
Gjelsvik, A., Belsnes, M., & Haugstad, A. (1999). An algorithm for stochastic medium-term hydrothermal scheduling under spot price uncertainty. Proceedings of 13th Power Systems Computation Conference.
Pereira, M. V. F., & Pinto, L. M. V. G. (1984). Operation planning of large-scale hydrothermal systems. Proceedings of the 8th PSCC, Helsinki, Finland.
Pereira, M. V. F., & Pinto, L. M. V. G. (1985). Stochastic otimization of multireservoir hydroelectric system – a decomposition approach. Water Resource Research, 21(6).
Pereira, M. V. F., Campodónico, N. M., & Kelman, R. (1998). Long-term hydro scheduling based on stochastic models. EPSOM’98, Zurich.
Wallace, S., & Fleten, S. E. (2003). Stochastic programming models in energy. Stochastic Programming in the series Handbooks in Operations Research and Management Science (Vol. 10, pp. 637–677).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Chabar, R.M., Granville, S., Pereira, M.V.F., Iliadis, N.A. (2010). Optimization of Fuel Contract Management and Maintenance Scheduling for Thermal Plants in Hydro-based Power Systems. In: Bjørndal, E., Bjørndal, M., Pardalos, P., Rönnqvist, M. (eds) Energy, Natural Resources and Environmental Economics. Energy Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12067-1_13
Download citation
DOI: https://doi.org/10.1007/978-3-642-12067-1_13
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12066-4
Online ISBN: 978-3-642-12067-1
eBook Packages: EngineeringEngineering (R0)