A fuzzy prescriptive analytics approach to power generation capacity planning

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dc.authoridDursun Delen / 0000-0001-8857-5148en_US
dc.authorscopusidDursun Delen / 55887961100en_US
dc.authorwosidDursun Delen / AGA-9892-2022
dc.contributor.authorTektaş, Berna
dc.contributor.authorTuran, Hasan Hüseyin
dc.contributor.authorKasap, Nihat
dc.contributor.authorCebi, Ferhan
dc.contributor.authorDelen, Dursun
dc.date.accessioned2022-05-23T13:05:21Z
dc.date.available2022-05-23T13:05:21Z
dc.date.issued2022en_US
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Endüstri Mühendisliği Bölümüen_US
dc.description.abstractThis study examines the long-term energy capacity investment problem of a power generation company (GenCo), considering the drought threat posed by climate change in hydropower resources in Turkey. The mid-term planning decisions such as maintenance and refurbishment scheduling of power plants are also considered in the studied investment planning problem. In the modeled electricity market, it is assumed that GenCos conduct business in uncertain market conditions with both bilateral contracts (BIC) and day-ahead market (DAM) transactions. The problem is modeled as a fuzzy mixed-integer linear programming model with a fuzzy objective and fuzzy constraints to handle the imprecisions regarding both the electricity market (e.g., prices) and environmental factors (e.g., hydroelectric output due to drought). Bellman and Zadeh’s max-min criteria are used to transform the fuzzy capacity investment model into a model with a crisp objective and constraints. The applicability of methodology is illustrated by a case study on the Turkish electric market in which GenCo tries to find the optimal power generation investment portfolio that contains five various generation technologies alternatives, namely, hydropower, wind, conventional and advanced combined-cycle natural gas, and steam (lignite) turbines. The results show that wind turbines with low marginal costs and steam turbines with high energy conversion efficiency are preferable, compared with hydroelectric power plant investments when the fuzziness in hydroelectric output exists (i.e., the expectation of increasing drought conditions as a result of climate change). Furthermore, the results indicate that the gas turbine investments were found to be the least preferable due to high gas prices in all scenarios. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.en_US
dc.identifier.citationTektaş, B., Turan, H. H., Kasap, N., Çebi, F., & Delen, D. (2022). A fuzzy prescriptive analytics approach to power generation capacity planning. Energies, 15(9) doi:10.3390/en15093176en_US
dc.identifier.doi10.3390/en15093176en_US
dc.identifier.issn1996-1073en_US
dc.identifier.issue9en_US
dc.identifier.scopus2-s2.0-85129765342en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.3390/en15093176
dc.identifier.urihttps://hdl.handle.net/20.500.12713/2726
dc.identifier.volume15en_US
dc.identifier.wosWOS:000794544000001en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorDelen, Dursun
dc.language.isoenen_US
dc.publisherMDPIen_US
dc.relation.ispartofEnergiesen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectUncertaintyen_US
dc.subjectMaintenance and Refurbishment Schedulingen_US
dc.subjectGeneration Investment Planningen_US
dc.subjectFuzzy Mathematical Programmingen_US
dc.subjectClimate Changeen_US
dc.titleA fuzzy prescriptive analytics approach to power generation capacity planningen_US
dc.typeArticleen_US

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