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A software tool for capacity optimization of hybrid power systems including renewable energy technologies based on a hybrid genetic algorithm—tabu search optimization methodology

Katsigiannis Ioannis, Kanellos Fotios, Papaefthymiou Spyridon

Απλή Εγγραφή


URIhttp://purl.tuc.gr/dl/dias/42E4433F-CF89-4FBE-AF1C-A36FD074B81E-
Αναγνωριστικόhttps://link.springer.com/article/10.1007%2Fs12667-014-0138-0-
Αναγνωριστικόhttps://doi.org/10.1007/s12667-014-0138-0-
Γλώσσαen-
Μέγεθος16 pagesen
ΤίτλοςA software tool for capacity optimization of hybrid power systems including renewable energy technologies based on a hybrid genetic algorithm—tabu search optimization methodologyen
ΔημιουργόςKatsigiannis Ioannisen
ΔημιουργόςΚατσιγιαννης Ιωαννηςel
ΔημιουργόςKanellos Fotiosen
ΔημιουργόςΚανελλος Φωτιοςel
ΔημιουργόςPapaefthymiou Spyridonen
ΔημιουργόςΠαπαευθυμιου Σπυριδωνel
ΕκδότηςSpringer Verlagen
ΠερίληψηThis paper presents a software tool that has been developed for optimal configuration of hybrid power systems. These systems can be either interconnected to the main power grid or operated autonomously, and may contain a variety of components, including dispatchable generators (e.g., diesel generators, microturbines, biogas generators), non-dispatchable renewable energy technologies (e.g., wind turbines, photovoltaics), batteries, converters and dump loads. A software tool that optimizes such systems has been developed in MATLAB, using a combination of genetic algorithms and tabu search. The optimal configuration is expressed in terms of minimum cost of electricity (in €/kWh), taking into account operational and component size constraints. The needed input includes weather data (e.g., solar, wind, and temperature time-series), load data, system components data, and general parameters (e.g., project lifetime, discount rate). As a case study, in this paper the tool is used for evaluating an autonomous hybrid power system that includes renewable energy technologies in Chania region, Crete. Moreover, the performance of the tool is investigated for seven additional scenarios of the case study, via sensitivity analysis, studying the effect on the results of the uncertainty of weather and cost data. en
ΤύποςPeer-Reviewed Journal Publicationen
ΤύποςΔημοσίευση σε Περιοδικό με Κριτέςel
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by/4.0/en
Ημερομηνία2018-10-22-
Ημερομηνία Δημοσίευσης2016-
Θεματική ΚατηγορίαΓενετικοί αλγόριθμοιel
Θεματική ΚατηγορίαGAsen
Θεματική ΚατηγορίαGenetic algorithmsen
Θεματική ΚατηγορίαHybrid power systemsen
Θεματική ΚατηγορίαΑΠΕel
Θεματική ΚατηγορίαΑνανεώσιμες πηγές ενέργειαςel
Θεματική ΚατηγορίαRESen
Θεματική ΚατηγορίαRenewable energy sourcesen
Θεματική ΚατηγορίαSensitivity analysisen
Θεματική ΚατηγορίαTSen
Θεματική ΚατηγορίαTabu searchen
Βιβλιογραφική ΑναφοράY. A. Katsigiannis, F. D. Kanellos and S. Papaefthimiou, "A software tool for capacity optimization of hybrid power systems including renewable energy technologies based on a hybrid genetic algorithm—tabu search optimization methodology," Energ. Syst., vol. 7, no. 1, pp. 33-48, Feb. 2016. doi: 10.1007/s12667-014-0138-0en

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