Offshore Digitalisation and hybrid energy INtegration (ODIN)

Accelerating offshore wind energy deployment is crucial to meet European and Belgian energy targets. To overcome the high investment and operational costs, it is necessary to explore new grid concepts, technologies, and services. The hybrid combination of large-scale energy storage with wind farms enhances energy flexibility and their overall economic operation. The future offshore grid will connect diverse assets operated by different stakeholders to form a hybrid offshore energy system. Digitalization plays a pivotal role in integrating these assets, facilitating system-of-system control, and achieving efficient operation. Therefore, Offshore Digitalisation and hybrid energy INtegration (ODIN) are integral parts of the offshore grid. To accelerate offshore development, increase reliability, and ensure economical operation, our research project focuses on innovating automated testing, system-of-system asset management, and hybrid asset scheduling. Respectfully achieving virtualised automated testing concepts for offshore substations, a multi-variate traffic light system for new system-based health indicators, and flexible condition-based control of hybrid assets.

This VLAIO Icon research project aims to bring systems processes and services to the next level of integration by taking fundamental knowledge steps in terms of digitalisation:

• We will use higher-level modelling language for representing substations to virtualize the functionality of components and systems. By using new combinatorial screening methods we will define a generic and systematic test procedure for complex multi-component systems based on their digital communication interfaces, and leverage modular testing procedures (i.e. base functionality + specific extensions). This will enable automated offshore testing of substations.
• Making use of the functional models and screening methods we will calculate health indicators relevant to asset management (of a system-of-systems). The components and subsystems will be defined as stochastic processes from which we will realize a multi-variate traffic light system. Based on a weighted combinations of individual performances and asset conditions health indicators are elevated to a system level. Providing easy to interpret assessment on the operational status of a system to guide decision making, enabling us to draft new data-driven predictive maintenance strategies.
• The health indicators will next be used to progress dynamic hybrid operation envelopes. We aim for a co-optimal market and risk-aware dispatching to energy and ancillary services of different units. This will allow performing condition-based flexibility scheduling of hybrid assets.

The project will progress Offshore Digitalization and hybrid energy Integration (ODIN) through innovative research that can reduce the costs of wind farm development and operation, measured by the Levelled Cost of Energy (LCOE). To achieve this the project defines three sub-objectives, which include:

• Accelerating the deployment of offshore energy by automation of testing services. Concretely, by creating a modular virtualised test concept with screening algorithms we aim to decrease the overall time testing in substations, specifically on the Protection, Automation and Control (PAC) by an initial 25% with estimated costs related to the man-hours following the same trend. Per example, and depending on various project-specific factors, an offshore substations’ HV system and auxiliaries may take around 4000 test hours. Scaling from 15 GW to over 100 GW by 2030, with 500 MW per project and an hourly wage of 50 EUR/h, would yield savings of 8.5 MEUR.
• Increase system reliability through reduced outages of offshore energy with a system-of-system asset management. Concretely newly derived maintenance strategies will decrease preventive actions and unforeseen downtimes, leading to a decrease of the associated operation cost by 10% in a benchmark offshore system. A 500 MW offshore wind farm costs 2-3 billion EUR[1], with operation and maintenance making up 39% of costs. With a market potential of 100 GW by 2030, a 0.1% cost reduction translates to approximately 250 MEUR in savings.
• Increasing overall economical operation by providing more flexibility to the grid through dynamic hybrid operation envelopes, which increases remuneration of energy production through ancillary services. Concretely the condition-based scheduling targets a 1 % reduction in abandoned wind. Again, considering 100 GW in future capacity, a 50% capacity factor, with 20-year lifespan, and 20 €/MWh electricity, a 0.1% curtailing cut means about 175 MEUR more income.

At the end of the project we aim to move each of the research solutions above from their concept base to an experimental (proof-of-concept), which is successfully evaluated in a laboratory environment under the above criteria, including the impact on the LCOE.

[1] WindEurope statistics [Online], Available: windeurope.org/intelligence-platform/

Partners

• EnergyVille/KU Leuven
• Tractebel
• e-Bo Enterprises
• ENGIE Laborelec
• Siemens
• Parkwind

With the support of:

• VLAIO
• Flux50