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Optimal Economic Dispatch and Risk Management of Thermal Power Plants in Deregulated Markets

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  • Matt Thompson

    (Queen's School of Business, Queen's University, Kingston, Ontario K7L 3N6, Canada)

Abstract

This paper presents a methodology for the valuation, optimization, market, margin and credit risk management of gas-fired power plants and associated tolling contracts. Term structure models for the power and gas forward curves are employed to facilitate hedging and risk adjustment and for improved forecasting of short-term prices. The model for the power forward curve is capable of reproducing the important phenomena often observed in power markets, including spot price spikes and spike clustering, negative prices, and the empirically observed volatility term structures of power and gas forward prices as well as the correlation term structure between these forward curves. The method solves the stochastic dynamic optimization problem that arises from the inclusion of the various operational constraints of gas-fired power plants including minimum uptime and downtime requirements, ramp rate restrictions and costs, variable output and efficiency rates, and minimum generation levels. The model involves the solution of a system of partial differential equations (PDEs), which are solved using the radial basis function (RBF) method. At each time step and operational configuration the model produces an analytic function (RBF expansion) for the value of the power plant as a function of the independent risk factors. These functions can be used for determining optimal operating strategies and can be differentiated analytically to obtain the relevant hedging statistics for the dynamic management of market risk. In addition, these value functions facilitate the calculation of the credit value adjustment (CVA) and potential future exposure (PFE) measurement of tolling contracts. The analytic differentiability of these value functions also facilitates the pricing and risk management of commodity contingent revolvers (CCRs), credit vehicles used to manage margin requirements that result from hedging market risk on an exchange.

Suggested Citation

  • Matt Thompson, 2013. "Optimal Economic Dispatch and Risk Management of Thermal Power Plants in Deregulated Markets," Operations Research, INFORMS, vol. 61(4), pages 791-809, August.
    • Handle: RePEc:inm:oropre:v:61:y:2013:i:4:p:791-809
    DOI: 10.1287/opre.2013.1190
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    References listed on IDEAS

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    Cited by:

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    3. Woo, C.K. & Shiu, A. & Liu, Y. & Luo, X. & Zarnikau, J., 2018. "Consumption effects of an electricity decarbonization policy: Hong Kong," Energy, Elsevier, vol. 144(C), pages 887-902.
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    5. Zarnikau, J. & Woo, C.K. & Zhu, S. & Tsai, C.H., 2019. "Market price behavior of wholesale electricity products: Texas," Energy Policy, Elsevier, vol. 125(C), pages 418-428.
    6. Thompson, Matt, 2016. "Natural gas storage valuation, optimization, market and credit risk management," Journal of Commodity Markets, Elsevier, vol. 2(1), pages 26-44.
    7. Woo, C.K. & Chen, Y. & Olson, A. & Moore, J. & Schlag, N. & Ong, A. & Ho, T., 2017. "Electricity price behavior and carbon trading: New evidence from California," Applied Energy, Elsevier, vol. 204(C), pages 531-543.
    8. Woo, C.K. & Chen, Y. & Zarnikau, J. & Olson, A. & Moore, J. & Ho, T., 2018. "Carbon trading’s impact on California’s real-time electricity market prices," Energy, Elsevier, vol. 159(C), pages 579-587.
    9. Ratha, Anubhav & Pinson, Pierre & Le Cadre, Hélène & Virag, Ana & Kazempour, Jalal, 2023. "Moving from linear to conic markets for electricity," European Journal of Operational Research, Elsevier, vol. 309(2), pages 762-783.
    10. Secomandi, Nicola & Seppi, Duane J., 2014. "Real Options and Merchant Operations of Energy and Other Commodities," Foundations and Trends(R) in Technology, Information and Operations Management, now publishers, vol. 6(3-4), pages 161-331, July.
    11. Nadarajah, Selvaprabu & Secomandi, Nicola, 2023. "A review of the operations literature on real options in energy," European Journal of Operational Research, Elsevier, vol. 309(2), pages 469-487.
    12. Woo, C.K. & Moore, J. & Schneiderman, B. & Ho, T. & Olson, A. & Alagappan, L. & Chawla, K. & Toyama, N. & Zarnikau, J., 2016. "Merit-order effects of renewable energy and price divergence in California’s day-ahead and real-time electricity markets," Energy Policy, Elsevier, vol. 92(C), pages 299-312.
    13. Niu, Shilei & Insley, Margaret, 2016. "An options pricing approach to ramping rate restrictions at hydro power plants," Journal of Economic Dynamics and Control, Elsevier, vol. 63(C), pages 25-52.
    14. Chi-Keung Woo, Ira Horowitz, Jay Zarnikau, Jack Moore, Brendan Schneiderman, Tony Ho, and Eric Leung, 2016. "What Moves the Ex Post Variable Profit of Natural-Gas-Fired Generation in California?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    15. Weiwei Liu & Zhile Yang & Kexin Bi, 2017. "Forecasting the Acquisition of University Spin-Outs: An RBF Neural Network Approach," Complexity, Hindawi, vol. 2017, pages 1-8, October.
    16. Nadarajah, Selvaprabu & Margot, François & Secomandi, Nicola, 2017. "Comparison of least squares Monte Carlo methods with applications to energy real options," European Journal of Operational Research, Elsevier, vol. 256(1), pages 196-204.
    17. Thompson, Matt & Barr, Drew, 2014. "Cut-off grade: A real options analysis," Resources Policy, Elsevier, vol. 42(C), pages 83-92.

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