학술논문

A time consistent risk averse three-stage stochastic mixed integer optimisation model for power generation capacity expansion [reprint of Energy Economics {\bf 53} (2016), 203--211].
Document Type
Proceedings Paper
Author
Pisciella, P. (I-BERG-MEQ) AMS Author Profile; Vespucci, M. T. (I-BERG-MEQ) AMS Author Profile; Bertocchi, M. I. (I-BERG-MEQ) AMS Author Profile; Zigrino, S. (I-BERG-MEQ) AMS Author Profile
Source
Collected works of Marida Bertocchi (20200101), 395-423.
Subject
90 Operations research, mathematical programming -- 90C Mathematical programming
  90C11 Mixed integer programming
  90C15 Stochastic programming
Language
English
Abstract
Summary: ``We propose a multi-stage stochastic optimization model for the generation capacity expansion problem of a price-taker power producer. Uncertainties regarding the evolution of electricity prices and fuel costs play a major role in long term investment decisions, therefore the objective function represents a trade-off between expected profit and risk. The Conditional Value at Risk is the risk measure used and is defined by a nested formulation that guarantees time consistency in the multi-stage model. The proposed model allows one to determine a long term expansion plan which takes into account uncertainty, while the LCoE approach, currently used by decision makers, only allows one to determine which technology should be chosen for the next power plant to be built. A sensitivity analysis is performed with respect to the risk weighting factor and budget amount.''

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