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• W2019488240 abstract "We propose a two-stage stochastic optimization model for maximizing the profit of a price-taker power producer who has to decide his own power generation capacity expansion plan in a long time horizon, taking into account the uncertainty of the following parameters: fuel costs; market electricity prices, as well as prices of green certificates and CO <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2</sub> emission allowances; market share. The parameter uncertainty is represented by scenarios on their values along the planning horizon and the associated probability of occurrence. We first discuss the risk neutral stochastic model, that maximizes over all scenarios the net present value of the expected profit along the planning horizon. The risk neutral model does not take into account the variability of the objective function value over the scenarios and, then, the possibility of realizing in some scenarios a very low profit. Several approches have been introduced in the literature for measuring the profit risk. In this work we consider the Conditional Value at Risk, that requires a confidence level to be defined, and the First-order Stochastic Dominance constraints, for which a benchmark need to be assigned. By using a realistic case study, we report the main results of considering risk averse strategies under different hypotheses of the available budget, analysing the impact on the expected profit." @default.
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• W2019488240 date "2013-05-01" @default.
• W2019488240 modified "2023-10-14" @default.
• W2019488240 title "Stochastic optimization models for power generation capacity expansion with risk management" @default.
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• W2019488240 doi "https://doi.org/10.1109/eem.2013.6607352" @default.
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