Ιδρυματικό Αποθετήριο
Πολυτεχνείο Κρήτης
Πολυτεχνείο Κρήτης
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| URI | http://purl.tuc.gr/dl/dias/42E4433F-CF89-4FBE-AF1C-A36FD074B81E | - |
| Αναγνωριστικό | https://link.springer.com/article/10.1007%2Fs12667-014-0138-0 | - |
| Αναγνωριστικό | https://doi.org/10.1007/s12667-014-0138-0 | - |
| Γλώσσα | en | - |
| Μέγεθος | 16 pages | en |
| Τίτλος | A software tool for capacity optimization of hybrid power systems including renewable energy technologies based on a hybrid genetic algorithm—tabu search optimization methodology | en |
| Δημιουργός | Katsigiannis Ioannis | en |
| Δημιουργός | Κατσιγιαννης Ιωαννης | el |
| Δημιουργός | Kanellos Fotios | en |
| Δημιουργός | Κανελλος Φωτιος | el |
| Δημιουργός | Papaefthymiou Spyridon | en |
| Δημιουργός | Παπαευθυμιου Σπυριδων | el |
| Εκδότης | Springer Verlag | en |
| Περίληψη | This 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 |
| Τύπος | Peer-Reviewed Journal Publication | en |
| Τύπος | Δημοσίευση σε Περιοδικό με Κριτές | el |
| Άδεια Χρήσης | http://creativecommons.org/licenses/by/4.0/ | en |
| Ημερομηνία | 2018-10-22 | - |
| Ημερομηνία Δημοσίευσης | 2016 | - |
| Θεματική Κατηγορία | Γενετικοί αλγόριθμοι | el |
| Θεματική Κατηγορία | GAs | en |
| Θεματική Κατηγορία | Genetic algorithms | en |
| Θεματική Κατηγορία | Hybrid power systems | en |
| Θεματική Κατηγορία | ΑΠΕ | el |
| Θεματική Κατηγορία | Ανανεώσιμες πηγές ενέργειας | el |
| Θεματική Κατηγορία | RES | en |
| Θεματική Κατηγορία | Renewable energy sources | en |
| Θεματική Κατηγορία | Sensitivity analysis | en |
| Θεματική Κατηγορία | TS | en |
| Θεματική Κατηγορία | Tabu search | en |
| Βιβλιογραφική Αναφορά | Y. 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/s12667-014-0138-0 | en |
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