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dc.contributor.authorAngarita-Márquez, Jorge L.
dc.contributor.authorMokryani, Geev
dc.contributor.authorMartínez-Crespo, J.
dc.date.accessioned2021-10-13T10:20:05Z
dc.date.accessioned2021-11-17T14:57:48Z
dc.date.available2021-10-13T10:20:05Z
dc.date.available2021-11-17T14:57:48Z
dc.date.issued2021-09
dc.identifier.citationAngarita-Márquez JL, Mokryani G and Martínez-Crespo J (2021) Two-Stage Stochastic Model to Invest in Distributed Generation Considering the Long-Term Uncertainties. Energies, 14 (18): 5694.
dc.identifier.urihttp://hdl.handle.net/10454/18637
dc.descriptionYes
dc.description.abstractThis paper used different risk management indicators applied to the investment optimization performed by consumers in Distributed Generation (DG). The objective function is the total cost incurred by the consumer including the energy and capacity payments, the savings, and the revenues from the installation of DG, alongside the operation and maintenance (O&M) and investment costs. Probability density function (PDF) was used to model the price volatility in the long-term. The mathematical model uses a two-stage stochastic approach: investment and operational stages. The investment decisions are included in the first stage and which do not change with the scenarios of the uncertainty. The operation variables are in the second stage and, therefore, take different values with every realization. Three risk indicators were used to assess the uncertainty risk: Value-at-Risk (VaR), Conditional Value-at-Risk (CVaR), and Expected Value (EV). The results showed the importance of migration from deterministic models to stochastic ones and, most importantly, the understanding of the ramifications of every risk indicator.
dc.language.isoenen
dc.publisherMDPI
dc.rights© The Authors, published by MDPI. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/ 4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
dc.subjectDistributed generation
dc.subjectEnergy trading
dc.subjectEnergy markets
dc.subjectMix-integer linear programming
dc.subjectTwo-stage stochastic programming
dc.titleTwo-Stage Stochastic Model to Invest in Distributed Generation Considering the Long-Term Uncertainties
dc.status.refereedYes
dc.typeArticle
dc.type.versionPublished version
dc.identifier.doihttps://doi.org/10.3390/en14185694
dc.rights.licenseCC-BY
dc.date.updated2021-10-13T10:20:07Z
refterms.dateFOA2021-11-17T14:59:01Z
dc.openaccess.statusopenAccess


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