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Environment, Development and Sustainability

, Volume 21, Issue 1, pp 199–219 | Cite as

Application of statistical charts, multi-criteria decision making and polynomial neural networks in monitoring energy utilization of wave energy converters

  • Tilottama Chakraborty
  • Mrinmoy MajumderEmail author
Article
  • 62 Downloads

Abstract

The rise in the demand for energy from the burgeoning population has enhanced the importance of renewable energy resources to substitute conventional energy resources. In this regard, energy extracted from ocean waves is found to be one of the most reliable but expensive alternatives. The cost of installation and monitoring of wave energy converters are the reasons why it is not a popular alternative to replace fossil fuels. One of the major reasons for higher cost lies in the subjective methods adopted to monitor or predict the wave energy potential. Also very few studies were conducted to monitor the efficiency of the converters in utilization of the available potential. The present investigation is an attempt to propose an objective, unbiased and adaptive procedure to monitor as well as estimate the utilization efficiency of the wave energy converters. The method was experimented on the coastal regions of India, and the results encourage further application of the novel method.

Keywords

Wave energy converter Multi-criteria decision making (MCDM) Control charts Group method of data handling (GMDH) 

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Copyright information

© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  1. 1.School of Hydro-Informatics EngineeringNational Institute of Technology AgartalaWest TripuraIndia

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