Optimizing renewable energy portfolios under uncertainty: A multi-segment fuzzy goal programming approach
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F18%3A10241317" target="_blank" >RIV/61989100:27510/18:10241317 - isvavai.cz</a>
Result on the web
<a href="https://apps.webofknowledge.com/full_record.do?product=WOS&search_mode=GeneralSearch&qid=1&SID=D3cXtwXy4ryu5fd1Pmw&page=1&doc=8" target="_blank" >https://apps.webofknowledge.com/full_record.do?product=WOS&search_mode=GeneralSearch&qid=1&SID=D3cXtwXy4ryu5fd1Pmw&page=1&doc=8</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.renene.2018.06.013" target="_blank" >10.1016/j.renene.2018.06.013</a>
Alternative languages
Result language
angličtina
Original language name
Optimizing renewable energy portfolios under uncertainty: A multi-segment fuzzy goal programming approach
Original language description
Selecting a renewable energy source portfolio is an uncertain multi-criteria decision-making (MCDM) problem. In particular, it involves searching for the best portfolio of renewable energy that meets the decision maker's preferences by considering and leveraging conflicting criteria such as technical, environmental, societal, and economic. To tackle such complex problems, this paper proposes an efficient method, called multi-segment fuzzy goal programming (MS-FGP), which addresses decision-making problems with high levels of uncertainty. The paper makes the following contributions: i) extends the conventional fuzzy goal programming (FGP) model to solve a wide range of uncertainties decision making problems and ii) proposes a method based on a recent development in the FGP area that considers all types of fuzzy goals in real-world problems. The model is validated by applying it to a real world scenario: optimizing the renewable portfolio for electricity generation in Italy. These renewables are solar photovoltaic (PV), wind, biomass, and tidal currents. The results show that the proposed methodology can assist decision makers in determining the most sustainable renewable energy source portfolio for electricity generation under uncertain conditions and in imprecise environments. (C) 2018 Elsevier Ltd. All rights reserved.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
50200 - Economics and Business
Result continuities
Project
<a href="/en/project/GA17-19981S" target="_blank" >GA17-19981S: Financial applications of stochastic ordering rules</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Renewable Energy
ISSN
0960-1481
e-ISSN
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Volume of the periodical
129
Issue of the periodical within the volume
december
Country of publishing house
GB - UNITED KINGDOM
Number of pages
13
Pages from-to
540-552
UT code for WoS article
000439745700042
EID of the result in the Scopus database
2-s2.0-85049308990