2017
DOI: 10.3390/en10122179
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A Probabilistically Constrained Approach for the Energy Procurement Problem

Abstract: Abstract:The definition of the electric energy procurement plan represents a fundamental problem that any consumer has to deal with. Bilateral contracts, electricity market and self-production are the main supply sources that should be properly combined to satisfy the energy demand over a given time horizon at the minimum cost. The problem is made more complex by the presence of uncertainty, mainly related to the energy requirements and electricity market prices. Ignoring the uncertain nature of these elements… Show more

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Cited by 17 publications
(8 citation statements)
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“…Nowadays, with the rapid growth of the world population and the fast development of society and economy, energy consumption is dramatically increasing year by year [1][2][3]. The great demands for petroleum, coal, and natural gas are remarkably stimulating the development of efficient exploitation and deep-hole drilling for energy resources, as the shallow ones are being depleted gradually [4][5][6][7].…”
Section: Introductionmentioning
confidence: 99%
“…Nowadays, with the rapid growth of the world population and the fast development of society and economy, energy consumption is dramatically increasing year by year [1][2][3]. The great demands for petroleum, coal, and natural gas are remarkably stimulating the development of efficient exploitation and deep-hole drilling for energy resources, as the shallow ones are being depleted gradually [4][5][6][7].…”
Section: Introductionmentioning
confidence: 99%
“…This can be achieved using the linear model 7, stochastic forecasting data and model uncertainties. Let us split power vectors P in (8) and Q in (9) in consumptions P l and Q l and productions P p and Q p (the nominal power of the DG of the node i is noted P N i ). P l is a stochastic variable which is not used for feedback.…”
Section: B Stochastic Modeling Of Inputsmentioning
confidence: 99%
“…On the other hand, confidence level optimization aims to maximize p when V max is given, that is find the minimum possible risk (here of voltage overvoltage). In the power system literature, adjusting or minimizing the confidence level has been done so far only for Unit Commitment or pricing problems [7], [8], but has not addressed control parameter tuning. In general, confidence level optimization are not convex [9], and chance-constrained relaxation as Chebychev generating functions [10] are not applicable.…”
Section: Introductionmentioning
confidence: 99%
“…During the last decades, CC-based models have been applied to formulate several real-world problems (see, for example, Beraldi et al 2012Beraldi et al , 2015Beraldi et al , 2017, where providing reliable solutions is considered a primary concern. Their use is actually not new in the field of portfolio optimization: the well-known Value at Risk measure, being a quantile, is modeled by a chance constraint and a large amount of papers on portfolio optimization can be "labeled" as CC-based models.…”
Section: Introductionmentioning
confidence: 99%