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Exploring Uncertainties and Challenges in Wave Energy Resource Assessment

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Exploring Uncertainties and Challenges in Wave Energy Resource Assessment. / Oikonomou, Charikleia; Rizaev, Igor; Korres, Gerasimos et al.
Proceedings of the Thirty-fourth (2024) International Ocean and Polar Engineering Conference. 2024. p. 624-632 192-2024-TPC-0911.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Oikonomou, C, Rizaev, I, Korres, G, Sheng, W & Aggidis, G 2024, Exploring Uncertainties and Challenges in Wave Energy Resource Assessment. in Proceedings of the Thirty-fourth (2024) International Ocean and Polar Engineering Conference., 192-2024-TPC-0911, pp. 624-632.

APA

Oikonomou, C., Rizaev, I., Korres, G., Sheng, W., & Aggidis, G. (2024). Exploring Uncertainties and Challenges in Wave Energy Resource Assessment. In Proceedings of the Thirty-fourth (2024) International Ocean and Polar Engineering Conference (pp. 624-632). Article 192-2024-TPC-0911

Vancouver

Oikonomou C, Rizaev I, Korres G, Sheng W, Aggidis G. Exploring Uncertainties and Challenges in Wave Energy Resource Assessment. In Proceedings of the Thirty-fourth (2024) International Ocean and Polar Engineering Conference. 2024. p. 624-632. 192-2024-TPC-0911

Author

Oikonomou, Charikleia ; Rizaev, Igor ; Korres, Gerasimos et al. / Exploring Uncertainties and Challenges in Wave Energy Resource Assessment. Proceedings of the Thirty-fourth (2024) International Ocean and Polar Engineering Conference. 2024. pp. 624-632

Bibtex

@inproceedings{44203a52a6c24a0e9f9ce54208827997,
title = "Exploring Uncertainties and Challenges in Wave Energy Resource Assessment",
abstract = "We evaluate the uncertainties in wave parameters that are critical for the wave energy sector using the high-quality Mediterranean waves dataset from the Copernicus Marine Service. The reanalysis dataset is benchmarked against data from buoys deployed offshore south Spain. While the reanalysis offers accurate predictions of wave height and period, well capturing their variability, it slightly under predicts them within the operational range of wave energy converters. During extreme waves (wave energy converter survival mode conditions), the model underestimates the wave height marginally. We demonstrate the applicability of two bias correction techniques: Delta-change and empirical quantile mapping.While both are effective in reducing uncertainty, the empirical quantile mapping method outperforms the former for extreme waves. This study seeks to improve the accuracy of wave energy resource assessments by providing a comprehensive set of guidelines outlining a systematic approach to address uncertainties. The guidelines cover essential aspects such as data collection and preparation, uncertainty evaluation, and bias correction implementation and efficiency assessment. The framework ensures the integrity of the data and the robustness of the model performance, potentially facilitating the preparation of future resource projections.",
keywords = "Wave Energy Resource, Model Uncertainty, Mediterranean Wave Reanalysis, Bias correction, Wave Energy Variability, Survival Mode Wave Conditions",
author = "Charikleia Oikonomou and Igor Rizaev and Gerasimos Korres and Wanan Sheng and George Aggidis",
year = "2024",
month = jun,
day = "17",
language = "English",
pages = "624--632",
booktitle = "Proceedings of the Thirty-fourth (2024) International Ocean and Polar Engineering Conference",

}

RIS

TY - GEN

T1 - Exploring Uncertainties and Challenges in Wave Energy Resource Assessment

AU - Oikonomou, Charikleia

AU - Rizaev, Igor

AU - Korres, Gerasimos

AU - Sheng, Wanan

AU - Aggidis, George

PY - 2024/6/17

Y1 - 2024/6/17

N2 - We evaluate the uncertainties in wave parameters that are critical for the wave energy sector using the high-quality Mediterranean waves dataset from the Copernicus Marine Service. The reanalysis dataset is benchmarked against data from buoys deployed offshore south Spain. While the reanalysis offers accurate predictions of wave height and period, well capturing their variability, it slightly under predicts them within the operational range of wave energy converters. During extreme waves (wave energy converter survival mode conditions), the model underestimates the wave height marginally. We demonstrate the applicability of two bias correction techniques: Delta-change and empirical quantile mapping.While both are effective in reducing uncertainty, the empirical quantile mapping method outperforms the former for extreme waves. This study seeks to improve the accuracy of wave energy resource assessments by providing a comprehensive set of guidelines outlining a systematic approach to address uncertainties. The guidelines cover essential aspects such as data collection and preparation, uncertainty evaluation, and bias correction implementation and efficiency assessment. The framework ensures the integrity of the data and the robustness of the model performance, potentially facilitating the preparation of future resource projections.

AB - We evaluate the uncertainties in wave parameters that are critical for the wave energy sector using the high-quality Mediterranean waves dataset from the Copernicus Marine Service. The reanalysis dataset is benchmarked against data from buoys deployed offshore south Spain. While the reanalysis offers accurate predictions of wave height and period, well capturing their variability, it slightly under predicts them within the operational range of wave energy converters. During extreme waves (wave energy converter survival mode conditions), the model underestimates the wave height marginally. We demonstrate the applicability of two bias correction techniques: Delta-change and empirical quantile mapping.While both are effective in reducing uncertainty, the empirical quantile mapping method outperforms the former for extreme waves. This study seeks to improve the accuracy of wave energy resource assessments by providing a comprehensive set of guidelines outlining a systematic approach to address uncertainties. The guidelines cover essential aspects such as data collection and preparation, uncertainty evaluation, and bias correction implementation and efficiency assessment. The framework ensures the integrity of the data and the robustness of the model performance, potentially facilitating the preparation of future resource projections.

KW - Wave Energy Resource

KW - Model Uncertainty

KW - Mediterranean Wave Reanalysis

KW - Bias correction

KW - Wave Energy Variability

KW - Survival Mode Wave Conditions

M3 - Conference contribution/Paper

SP - 624

EP - 632

BT - Proceedings of the Thirty-fourth (2024) International Ocean and Polar Engineering Conference

ER -