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

2018 | OriginalPaper | Chapter

5. Wave Energy Potential Site Selection Based on MCDM and Neural Network Analysis

Author : Soumya Ghosh

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

The present study, an improved wave energy potential estimate has been made. Based on various parameters such as physical site characteristics, environmental conditions and socio-economic regional state, the selection criteria have been suggested. This would form the basis for energy device selection for the decision makers. If analytical network process (ANP) is used to determine the weight vector to be assigned to the criteria considered for a certain decision-making problem, the output of the result will be more logical and the haziness of the conversion to a crisp rating will not influence the decision. Thus, we investigated a hybrid ANP method to identify the most suitable location for a wave energy potential site. The index also provided a heuristic and cognitive optimal value to way from a suitability of small scale hydro power plant installation. Both models were able to fit the data well, with R2 values of 0.98462 and 0.9964 for the linear regression model and the ANN model respectively. According to the results, wave height was found to have maximum importance followed by wind speed, wave period, water depth and salinity. The total three different neural networks were developed to predict the same output, all the models of five input to have a optimal performance.

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previous chapter Development of Financial Liability Index for Hydropower Plant with MCDM and Neuro-genetic Models
next chapter A MCDM-NBO Approach for Selection of Installation Location for Wave Energy Power Plants
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Metadata
Title
Wave Energy Potential Site Selection Based on MCDM and Neural Network Analysis
Author
Soumya Ghosh
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_5