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Evaluation of approaches used for optimization of stand-alone hybrid renewable energy systems
Energy resources are an irreplaceable life resource in the current world, with the use and management of these an important indicator of development. In parallel to the developing world economy, the increase in the use of energy resources is increasingly consuming existing fossil sources and also in...
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Published in: | Renewable & sustainable energy reviews 2017-06, Vol.73, p.840-853 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Energy resources are an irreplaceable life resource in the current world, with the use and management of these an important indicator of development. In parallel to the developing world economy, the increase in the use of energy resources is increasingly consuming existing fossil sources and also increasing the amount of greenhouse gas released into the atmosphere. As a result of resulting material and environmental concerns, renewable energy resources have begun to be used as alternative energy resources. These resources have advantages such as sustainability and environmental friendliness, in addition to having disadvantages such as higher investment costs and also system reliability is insufficient to provide for continuous demand for energy. To resolve these disadvantages, hybrid systems have been developed involving the use of more than one type of renewable energy resource and/or use with traditional energy resources and/or integration with storage systems. The use of these systems requires finding the solution to optimization problems including one or more objectives such as sizing the system to minimize energy costs, system management to balance the uncertainty of energy produced or reduction of greenhouse gas emissions. This article was prepared with the aim of investigating optimization techniques developed from past to present to solve this problem and especially to determine the efficacy of multi-objective optimization approaches. |
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ISSN: | 1364-0321 1879-0690 |
DOI: | 10.1016/j.rser.2017.01.118 |