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Review of Reservoir Sediment Inflow Estimation for Teriang Reservoir, Malaysia Read chapter Read first chapter

2018 | OriginalPaper | Chapter

6. A MCDM-NBO Approach for Selection of Installation Location for Wave Energy Power Plants

Author : Tilottama Chakraborty

Published in: Application of Geographical Information Systems and Soft Computation Techniques in Water and Water Based Renewable Energy Problems

Publisher: Springer Singapore

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Abstract

Wave energy is deemed to be one of the major options to substitute conventional energy sources. But due to the irregularity in wave patterns, technical shortcoming of converters, hostility from local populations and many other factors the cost of installation for wave power plant is expensive compared to other forms of renewable energy of the obstacles seems to be location dependent. That is why; selection of an ideal location for wave energy production can ensure optimal conversion of wave into electrical energy. The present study first tries to identify the most important parameters for location selection by MCDM methods. Then it attempts to identify the single most significant parameter for which production potential can be maximum. In this regard this study utilized three population based nature oriented optimization algorithms. The results from the study will reduce the search space of finding ideal location for installation of wave energy power plants. After applying the method in coastal region of Europe the results encouraged further applications of the method.

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previous chapter Wave Energy Potential Site Selection Based on MCDM and Neural Network Analysis
next chapter Cost Optimization of High Head Run of River Small Hydropower Projects
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Metadata
Title
A MCDM-NBO Approach for Selection of Installation Location for Wave Energy Power Plants
Author
Tilottama Chakraborty
Copyright Year
2018
Publisher
Springer Singapore
Book
Application of Geographical Information Systems and Soft Computation Techniques in Water and Water Based Renewable Energy Problems

Print ISBN: 978-981-10-6204-9

Electronic ISBN: 978-981-10-6205-6

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-981-10-6205-6_6