Abstract
This paper discusses a new method for enhanced power conversion with heaving point absorbers. The proposed scheme incorporates an intelligent neuro-adaptive controller for efficient heave velocity tracking. A novel algorithm is presented to generate the reference velocity signal by introducing a power loss control factor. It is observed through computer simulations that by increasing this factor improves the captured wave energy, which in turn enhances the converted electrical power. Overall, superior performance is achieved by the proposed methodology as opposed to the traditional passive control technique.
| Original language | English |
|---|---|
| Title of host publication | 5th International Conference on Renewable Energy |
| Subtitle of host publication | Generation and Application, ICREGA 2018 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 128-131 |
| Number of pages | 4 |
| ISBN (Electronic) | 9781538622513 |
| DOIs | |
| Publication status | Published - Apr 12 2018 |
| Event | 5th International Conference on Renewable Energy: Generation and Application, ICREGA 2018 - Al Ain, United Arab Emirates Duration: Feb 26 2018 → Feb 28 2018 |
Publication series
| Name | 5th International Conference on Renewable Energy: Generation and Application, ICREGA 2018 |
|---|---|
| Volume | 2018-January |
Other
| Other | 5th International Conference on Renewable Energy: Generation and Application, ICREGA 2018 |
|---|---|
| Country/Territory | United Arab Emirates |
| City | Al Ain |
| Period | 2/26/18 → 2/28/18 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- artificial neural network
- heaving point absorber
- radiation resistance
- wave energy converter
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Renewable Energy, Sustainability and the Environment
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