{rfName}
An

Indexed in

License and Use

Icono OpenAccess

Altmetrics

Analysis of institutional authors

Mendonca, HCorresponding AuthorMartinez, SAuthorDe Castro, R MAuthor

Share

November 11, 2025
Publications
>
Article
Sí

An Artificial Neural Network-Based Approach for Instantaneous Estimation of the Sea Surface Elevation in a Wave Farm

Publicated to: IEEE Access. 13 181088-181099 - 2025-01-01 13(), DOI: 10.1109/ACCESS.2025.3622308

Authors:

Mendonca, H; Martinez, S; de Castro, RM
[+]

Affiliations

Univ Politecn Madrid, Escuela Tecn Super Ingn Ind, Madrid 28006, Spain - Author

Abstract

Many control strategies to maximise the captured power by wave energy converters depend on the knowledge of the incoming wave in a short term future. However, the wave prediction may be unpractical in a wave farm, since many measurement systems would be required. As a part of a prediction system, this paper presents an estimator of the instantaneous sea surface elevation in an open-field sea area for potential wave farm deployment based on a single measurement point. The approach is based on a time delay artificial neural network and the paper explores the performance of the estimation for a given field and the sensitivity to different sea characteristics. The proposed realisation of the artificial neural network is found to be accurate and robust, resulting in a useful tool for a wave prediction system in a farm for control purposes.
[+]

Keywords

AccuracyArraysArtificial neural networkControl strategiesData modelsDelay control systemsEstimationForecastingIdentificationLow-pass filtersNetwork-based approachNeural networksNeural-networksPowerPower convertersPredictionPrediction systemsPredictive modelsRecurrent neural networksSea measurementsSea surfaceSea surface elevationSurface watersSurface wavesTime delayTime delay neural networkTime delay neural networksTiming circuitsWave energy conversionWave energy converterWave energy convertersWave estimationWave farmWave farmsWave powerWave predictions

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal IEEE Access due to its progression and the good impact it has achieved in recent years, according to the agency Scopus (SJR), it has become a reference in its field. In the year of publication of the work, 2025, it was in position , thus managing to position itself as a Q1 (Primer Cuartil), in the category Engineering (Miscellaneous).

[+]

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2026-04-25:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 1 (PlumX).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.
  • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: https://oa.upm.es/93540/

As a result of the publication of the work in the institutional repository, statistical usage data has been obtained that reflects its impact. In terms of dissemination, we can state that, as of

  • Views: 23
  • Downloads: 20
[+]

Leadership analysis of institutional authors

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (ROCHA MENDONCA, HUGO) and Last Author (CASTRO FERNANDEZ, ROSA MARIA DE).

the author responsible for correspondence tasks has been ROCHA MENDONCA, HUGO.

[+]

Project objectives

La aportación persigue los siguientes objetivos: analizar la viabilidad de un estimador instantáneo de la elevación de la superficie marina en un área abierta para parques de olas; desarrollar un método basado en redes neuronales artificiales con retardo temporal para dicha estimación; evaluar el desempeño del estimador en un campo específico y su sensibilidad a distintas características marinas; determinar la precisión y robustez del enfoque propuesto; y caracterizar su utilidad como herramienta para sistemas de predicción de olas orientados al control en parques de energía undimotriz.
[+]

Most relevant results

El estudio presenta un método basado en redes neuronales artificiales para estimar de forma instantánea la elevación de la superficie marina en un parque de olas, utilizando un único punto de medición. Los resultados más relevantes son: la red neuronal con retardo temporal demostró alta precisión en la estimación de la elevación del mar; la técnica mostró robustez frente a diversas características marítimas; se validó en un área de campo abierto con condiciones reales; y se confirmó su utilidad como herramienta para sistemas de predicción y control en parques de energía undimotriz. Estos hallazgos evidencian la viabilidad del método para mejorar la gestión energética en parques de olas.
[+]

Awards linked to the item

This work was supported in part by Spanish Ministry of Economy and Competitivity under Grant ENE2012-36981, and in part by the OPSMaster Plan for Spanish Ports is co-financed by the Connecting Europe Facility (CEF) for the Building of European Union's TEN-T under Project 2015-EU-TM-0417.
[+]