### Abstract

The paper describes the analyses of wave data recorded at various locations and water depths around northern Europe to determine the temporal characteristics of individual wave periods and other wave period statistics. These analyses show that, just as there are group characteristics for wave heights, there are similar, but less pronounced, characteristics for wave periods. This is observed in three separate sets of data from different locations in water depths of 18, 50, and 130 m. It is also found in time series simulated using random linear wave theory from a Jonswap spectrum. A simple, new statistic, R, is introduced that measures the rate of change in the wave period from one wave to the next. This is relevant to wave energy devices that may try to tune themselves to obtain optimum power output from each individual wave. The characteristics of this statistic and its variation with significant wave height, mean energy period, and spectral bandwidth have been examined for the three datasets and are discussed. It is found that the R statistic can be fitted quite well by a Gaussian distribution for all the datasets examined. In a real sea there will be many small waves with comparatively very little energy, and the effect of filtering these out upon the R statistic has been examined. It is seen that removing the small waves has very little effect upon the energy available for extraction but significantly reduces the rate at which the wave energy device must retune to obtain optimum power conversion. This is illustrated by considering a hypothetical wave energy device, with a representative power transfer function, that can retune at prescribed rates. It is shown that being able to tune to individual waves can greatly increase power output. © IMechE 2006.

Original language | English |
---|---|

Pages (from-to) | 99-115 |

Number of pages | 17 |

Journal | Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment |

Volume | 220 |

Issue number | 3 |

DOIs | |

Publication status | Published - 2006 |

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### Keywords

- Device tuning
- Wave energy converters
- Wave groups
- Wave period statistics
- Wave power

### Cite this

*Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment*,

*220*(3), 99-115. https://doi.org/10.1243/14750902JEME37

}

*Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment*, vol. 220, no. 3, pp. 99-115. https://doi.org/10.1243/14750902JEME37

**Wave period group statistics for real sea waves and wave energy extraction.** / Smith, G. H.; Venugopal, V.; Wolfram, J.

Research output: Contribution to journal › Article

TY - JOUR

T1 - Wave period group statistics for real sea waves and wave energy extraction

AU - Smith, G. H.

AU - Venugopal, V.

AU - Wolfram, J.

PY - 2006

Y1 - 2006

N2 - The paper describes the analyses of wave data recorded at various locations and water depths around northern Europe to determine the temporal characteristics of individual wave periods and other wave period statistics. These analyses show that, just as there are group characteristics for wave heights, there are similar, but less pronounced, characteristics for wave periods. This is observed in three separate sets of data from different locations in water depths of 18, 50, and 130 m. It is also found in time series simulated using random linear wave theory from a Jonswap spectrum. A simple, new statistic, R, is introduced that measures the rate of change in the wave period from one wave to the next. This is relevant to wave energy devices that may try to tune themselves to obtain optimum power output from each individual wave. The characteristics of this statistic and its variation with significant wave height, mean energy period, and spectral bandwidth have been examined for the three datasets and are discussed. It is found that the R statistic can be fitted quite well by a Gaussian distribution for all the datasets examined. In a real sea there will be many small waves with comparatively very little energy, and the effect of filtering these out upon the R statistic has been examined. It is seen that removing the small waves has very little effect upon the energy available for extraction but significantly reduces the rate at which the wave energy device must retune to obtain optimum power conversion. This is illustrated by considering a hypothetical wave energy device, with a representative power transfer function, that can retune at prescribed rates. It is shown that being able to tune to individual waves can greatly increase power output. © IMechE 2006.

AB - The paper describes the analyses of wave data recorded at various locations and water depths around northern Europe to determine the temporal characteristics of individual wave periods and other wave period statistics. These analyses show that, just as there are group characteristics for wave heights, there are similar, but less pronounced, characteristics for wave periods. This is observed in three separate sets of data from different locations in water depths of 18, 50, and 130 m. It is also found in time series simulated using random linear wave theory from a Jonswap spectrum. A simple, new statistic, R, is introduced that measures the rate of change in the wave period from one wave to the next. This is relevant to wave energy devices that may try to tune themselves to obtain optimum power output from each individual wave. The characteristics of this statistic and its variation with significant wave height, mean energy period, and spectral bandwidth have been examined for the three datasets and are discussed. It is found that the R statistic can be fitted quite well by a Gaussian distribution for all the datasets examined. In a real sea there will be many small waves with comparatively very little energy, and the effect of filtering these out upon the R statistic has been examined. It is seen that removing the small waves has very little effect upon the energy available for extraction but significantly reduces the rate at which the wave energy device must retune to obtain optimum power conversion. This is illustrated by considering a hypothetical wave energy device, with a representative power transfer function, that can retune at prescribed rates. It is shown that being able to tune to individual waves can greatly increase power output. © IMechE 2006.

KW - Device tuning

KW - Wave energy converters

KW - Wave groups

KW - Wave period statistics

KW - Wave power

U2 - 10.1243/14750902JEME37

DO - 10.1243/14750902JEME37

M3 - Article

VL - 220

SP - 99

EP - 115

JO - Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment

JF - Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment

SN - 1475-0902

IS - 3

ER -