Abstract

For renewable ocean wave energy to support global energy demands, wave energy converters (WECs) will likely be deployed in large numbers (farms), which will necessarily change the nearshore environment. Wave farm induced changes can be both helpful (e.g., beneficial habitat and coastal protection) and potentially harmful (e.g., degraded habitat, recreational, and commercial use) to existing users of the coastal environment. It is essential to estimate this impact through modeling prior to the development of a farm, and to that end, many researchers have used spectral wave models, such as Simulating WAves Nearshore (SWAN), to assess wave farm impacts. However, the validity of the approaches used within SWAN have not been thoroughly verified or validated. Herein, a version of SWAN, called Sandia National Laboratories (SNL)-SWAN, which has a specialized WEC implementation, is verified by comparing its wave field outputs to those of linear wave interaction theory (LWIT), where LWIT is theoretically more appropriate for modeling wave-body interactions and wave field effects. The focus is on medium-sized arrays of 27 WECs, wave periods, and directional spreading representative of likely conditions, as well as the impact on the nearshore. A quantitative metric, the Mean Squared Skill Score, is used. Results show that the performance of SNL-SWAN as compared to LWIT is “Good” to “Excellent”.

Highlights

  • Renewable energy from ocean waves has the potential to play a large role in the world’s future energy supply; the theoretically available wave power resource is around 2.1 TW [1]

  • Is considered in terms of the Mean Squared Skill Score (MSSS), and, the performance of Sandia National Laboratories (SNL)-Simulating WAves Nearshore (SWAN) is considered in terms of the dimensional errors in wave height

  • The performance of SNL-SWAN for modeling wave energy converters (WECs) array impacts on the nearshore was assessed by comparing it to analogous results from Linear Wave Interaction Theory (LWIT), LWIT being more accurate at modeling wave-body interactions

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Summary

Introduction

Renewable energy from ocean waves has the potential to play a large role in the world’s future energy supply; the theoretically available wave power resource is around 2.1 TW [1]. For wave energy to be extracted economically at a large scale, wave energy converters (WECs) need to be deployed in arrays, or farms, consisting of many devices clustered together, facilitating operations and maintenance, and maximizing the use of infrastructure, like subsea cables. By the conservation of energy, extracting energy from the wave field means that there must be a net reduction of wave heights in the region of the array. It is well understood within the field of coastal engineering that variations in wave heights can result in wave-driven currents and sediment transport. Wave farm driven environmental changes have the potential to both positively (e.g., coastal resilience) and negatively (e.g., adverse habitat change) impact adjacent beaches and coastal ecosystems. Evaluation tools must be able to optimize array designs to balance energy generation with environmental impacts

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