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A Stochastic Discrete Choice Dynamic Programming Model of Power Plant Operations and Retirement

Author

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  • Çam, Eren

    (Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI))

  • Hinkel, Niklas

    (Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI))

  • Schönfisch, Max

    (Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI))

Abstract

We present a methodology to estimate fixed cost parameters relevant to the decision to operate, mothball or retire an open-cycle gas turbine (OCGT) using a dynamic discrete choice model, based on fuel and electricity prices, as well as technical data and the operational status of OCGTs in the PJM market area. With operational and mothballed OCGTs, we find for both, age of the power plant and plant vintage statistically significant positive correlations with the fixed operation and maintenance (O&M) costs. We also show a statistically significant negative relationship between the installed capacity and the fixed O&M costs, confirming that an increase in scale results in lower specific costs. The estimated fixed O&M cost parameters for an operational OCGT vary from 15.3 USD/kW/yr for new, large, high-efficiency units, to 50.8 USD/kW/yr for older, small, low-efficiency units. Mothballing a plant reduces these costs by 75% to 95%, depending on plant vintage and size. Decommissioning an OCGT was found to be cash flow negative, which means that the associated cost exceeds any scrap value the equipment may have on secondary markets. Our estimated cost parameters depend on operational status, capacity, vintage, and age of a generation unit. This differentiation is valuable for a better understanding of costs in the context of competition policy. It would also allow for a more realistic parameterisation of power market models. Using the estimates and market data, we also compute the probabilities of operating, mothballing or retiring an OCGT. Sensitivity analyses regarding changes in prices of capacity, electricity, and natural gas reveal that the operating decisions for OCGTs are significantly affected by the profitability potential, most notably by electricity prices.

Suggested Citation

  • Çam, Eren & Hinkel, Niklas & Schönfisch, Max, 2022. "A Stochastic Discrete Choice Dynamic Programming Model of Power Plant Operations and Retirement," EWI Working Papers 2022-1, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
  • Handle: RePEc:ris:ewikln:2022_001
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    More about this item

    Keywords

    Dynamic discrete choice models; electricity markets; fixed cost estimation; maximum likelihood estimation; open-cycle gas turbine (OCGT);
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

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