G1 - Fit-for-purpose approaches to environmental monitoring

Environmental (EIA/HRA) data collection can be a significant CAPEX cost and post-consent data collection can be a significant OPEX cost

Environmental monitoring is a high cost aspect of ORE project development and is needed during both environmental impact assessment and post consent. However, there is generally low confidence in the predictions of cumulative and population level environmental impacts. Better understanding of the models and the data needed for use in them will enable the development of a framework for monitoring data collection with environmental impact assessment and post consent guidelines.

The development of approaches to environmental monitoring that are fit for purpose will potentially lower costs of CAPEX and OPEX in ORE significantly. There is an opportunity to create new UK expertise for data collection and data base standards, and for bespoke monitoring equipment that can be exported worldwide.

Recognised by many researchers, developers (Royal HaskoningDHV) and regulators (MSS, MMO) that have been dealing with consent issues that changes are needed in policy for SEA, EIA/HRA and post-consent data collection, sharing of data products. The INSITE programme is helping to set up a roadmap to locations of data. However regulators are suggesting use of the existing national Marine Environmental Data and Information Network (MEDIN) database:

• Industry Evidence Programme (IEP)
• Review of environmental data associated with post-consent monitoring of licence conditions of offshore wind farms
• INSITE Data RoadMap
• MEDIN

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Supergen ORE Hub Flexible funding Research

• FORTUNE - Floating Offshore Wind Turbine Noise
  Lead Institution: Scottish Association of Marine Sciences
  This project will obtain, for the first time, systematic, long-term measurements of underwater noise generated by two operational floating offshore wind (FOW) turbines of different designs across a range of environmental conditions. Based on these measurements, cumulative noise levels and spatial footprints from turbine arrays, and potential impact ranges for noise sensitive wildlife under varying environmental conditions will be determined. The project will allow a comprehensive comparison between sound outputs from the two different commercial-scale turbines. This approach will be a first example for evaluation of FOW turbine acoustic signatures and allow assessment of differences in sound output resulting from particular turbine or mooring designs. This will be of significant use to both Offshore Renewable Energy (ORE) developers interested in optimising device operations, and regulators concerned with managing anthropogenic noise in the marine environment.
• Autonomous Biomimetic Robot-fish for Offshore Wind Farm Inspection
  Lead Institution: University of York
  The maintenance and monitoring of Offshore Wind Turbines (OWTs) and Floating Offshore Wind Turbines (FOWTs) present significant challenges. Underwater Remotely Operated Vehicles (ROVs) used to inspect them are limited in accessibility and manoeuvrability. This project will build a “Robo Fish” – a biometric Autonomous Underwater Vehicle (AUV) capable of continuously and autonomously locating and monitoring structural damage to OWTs or FOWTs. The Robo Fish mimics the movement of an eel, allowing it to greater agility in close proximity to structures and better energy efficiency of movement compared to conventional AUV designs.
• V-SCORES (Validating Surface Currents at Offshore Renewable Energy Sites)
  Lead Institution: University of the Highlands and Islands
  The aim of V-SCORES is comprehensive validation of unmanned aerial vehicle (UAV) techniques for surface current spatial mapping, demonstrated at tidal stream sites. Field campaigns will be conducted at contrasting commercial sites (Pentland Firth, Scotland & Ramsey Sound, Wales) under different environmental conditions (wave exposure, operational turbines installed, etc.).
• Satellite Climate Observation for Offshore Renewable Energy Cost Reduction (SCORE)
  Lead Institution: University of Edinburgh
  Satellite-based measurement has long been identified as having a potential role in enabling cost reduction of marine renewables, but applications have been largely limited to wind resource assessment and wake modelling. This project aims to take satellite data usage in offshore renewable energy (ORE) to the next level by better linking satellite data, models driven by such data, decisions driven by the model outputs, and quantifying this impact on a Levelised Cost of Energy. By mapping linkages between key decision horizons in ORE life cycle to satellite capability will produce a visual map of where satellite data can best impact ORE project decisions. This map will direct the data analysis activities towards the project decisions having the best potential for improvement and quantify any reductions in uncertainty. These improvements will then be captured and monetised in a range of cost models.