SWELL: An open-access experimental dataset for arrays of wave energy conversion systems

FAEDO, NICOLÁS; PEÑA-SANCHEZ, YERAI; PASTA, EDOARDO; PAPINI, GUGLIELMO; MOSQUERA, FACUNDO D.; FERRI, FRANCESCO

RENEWABLE ENERGY

PERGAMON-ELSEVIER SCIENCE LTD

Año: 2023

0960-1481

Achieving large-scale commercial exploitation of ocean wave energy inherently encompasses the design and deployment of arrays of wave energy converters (WECs), in an effort to reduce the associated levelised cost of energy. In this context, understanding the interactions between devices in a controlled WEC array is hence essential to achieve optimal layout configurations, as well as to provide guidance on the area required for array installation, reliability, life-time, and overall cost of the farm. Successful achievement of these vital objectives for the wave energy industry has been constantly aided by the use of appropriate numerical models. Regardless of the specific modelling approach adopted, model reliability is always a major concern: Numerical models need to able be to represent reality to be useful in supporting the different stages of development, hence providing significant results for decision making. To test reliability of a model, experimental results are an invaluable asset for validation.Recognising the striking absence of real-world data concerning arrays of WEC systems, and its inherent value for model validation and data-based modelling purposes, we present, in this paper, an experimental campaign fully conducted with the sole objective of generating and providing an open-access dataset on WEC farms: SWELL (Standardised Wave Energy converter array Learning Library). The generated dataset, included alongside this manuscript, comprises an approximate total of ∼ 3000 variables and more than ∼108 datapoints, for up to 5 devices in 9 diverse WEC array layouts with different levels of interaction, and 19 carefully selected operating conditions. Four different categories of tests are considered, providing measures of key variables required for model validation and data-based modelling tasks. As such, SWELL provides a crucial resource to achieve confidence in numerical modelling, helping towards creating reliable tools for decision making in the WEC field, hence effectively supporting the pathway towards effective commercialisation of ocean wave energy.