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Medium-term Planning for Thermal Electricity Production

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  • Kovacevic, Raimund M.
  • Paraschiv, Florentina

Abstract

In the present paper we demonstrate a mid-term planning model for thermal power generation which is based on multistage stochastic optimization and involves stochastic electricity spot prices, mixture of fuels with stochastic prices, the effect of CO2 emission prices and various types of further operating costs. Going from data to decisions, the first goal is to estimate simulation models for various commodity prices. We apply geometric Brownian motions with jumps to model gas, coal, oil and emission allowance (EUA) spot prices. Electricity spot prices are modeled by a regime switching approach which takes into account seasonal effects as well as jumps and spikes. Given the estimated models we simulate scenario paths and then use a novel approach based on a multiperiod generalization of the Wasserstein distance for constructing the stochastic trees used in the optimization model. Finally, we solve a one year planning problem for a fictitious configuration of thermal units, producing against the markets. Numerical examples are used to demonstrate the effect of CO2 prices on cumulated emissions and to show an application of indifference pricing to electricity delivery contracts.

Suggested Citation

  • Kovacevic, Raimund M. & Paraschiv, Florentina, 2012. "Medium-term Planning for Thermal Electricity Production," Working Papers on Finance 1220, University of St. Gallen, School of Finance.
    • Handle: RePEc:usg:sfwpfi:2012:20
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    1. Karl Frauendorfer & Florentina Paraschiv & Michael Schürle, 2018. "Cross-Border Effects on Swiss Electricity Prices in the Light of the Energy Transition," Energies, MDPI, vol. 11(9), pages 1-30, August.
    2. Kovacevic, Raimund M. & Pflug, Georg Ch., 2014. "Electricity swing option pricing by stochastic bilevel optimization: A survey and new approaches," European Journal of Operational Research, Elsevier, vol. 237(2), pages 389-403.
    3. Paraschiv, Florentina & Erni, David & Pietsch, Ralf, 2014. "The impact of renewable energies on EEX day-ahead electricity prices," Energy Policy, Elsevier, vol. 73(C), pages 196-210.
    4. Paraschiv, Florentina & Fleten, Stein-Erik & Schürle, Michael, 2015. "A spot-forward model for electricity prices with regime shifts," Energy Economics, Elsevier, vol. 47(C), pages 142-153.
    5. Lars Ivar Hagfors & Hilde Hørthe Kamperud & Florentina Paraschiv & Marcel Prokopczuk & Alma Sator & Sjur Westgaard, 2016. "Prediction of extreme price occurrences in the German day-ahead electricity market," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1929-1948, December.
    6. Raimund M. Kovacevic, 2019. "Valuation and pricing of electricity delivery contracts: the producer’s view," Annals of Operations Research, Springer, vol. 275(2), pages 421-460, April.
    7. Andreas Welling, 2017. "Green Finance: Recent developments, characteristics and important actors," FEMM Working Papers 170002, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.
    8. Hannes Schwarz & Valentin Bertsch & Wolf Fichtner, 2018. "Two-stage stochastic, large-scale optimization of a decentralized energy system: a case study focusing on solar PV, heat pumps and storage in a residential quarter," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(1), pages 265-310, January.

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