Discrete optimization algorithm for optimal design of a solar/wind/battery hybrid energy conversion scheme
Author(s) -
Weiping Zhang,
Akbar Maleki,
Ali Komeili Birjandi,
Mohammad Alhuyi Nazari,
Omid Mohammadi
Publication year - 2020
Publication title -
international journal of low-carbon technologies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.458
H-Index - 26
eISSN - 1748-1325
pISSN - 1748-1317
DOI - 10.1093/ijlct/ctaa067
Subject(s) - tabu search , sizing , harmony search , renewable energy , computer science , mathematical optimization , wind power , algorithm , energy storage , engineering , mathematics , power (physics) , electrical engineering , art , physics , quantum mechanics , visual arts
Renewable energy technologies have been developed in recent years due to the limited sources of fossil fuels, the possibility of depletion of fossil fuels and the related environmental issues. In these types of systems, it is crucial to reach optimum sizing in order to have an affordable system based on solar and wind energy and energy storage. In this study, a powerful optimization scheme based on tabu search, called discrete tabu search, has been proposed for sizing three stand-alone solar/wind/energy storage (battery) hybrid systems. For validating the applied algorithm effectiveness, the results are compared with the results found by the discrete harmony search. The obtained outcomes are compared on the basis of total annual cost. The components of the scheme are analyzed in different operating conditions by applying meteorological data in addition to real time information from three typical regions of Iran. According to the obtained data, applying ‘discrete tabu search’ leads to better outputs on the basis of mean, standard deviation and worst indexes.
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