Posters
Come meet the poster presenters to ask them questions and discuss their work
We would like to invite you to come and see the posters at our upcoming conference. The posters will showcase a diverse range of research topics, and will give delegates an opportunity to engage with the authors and learn more about their work. Whether you are a seasoned researcher or simply curious about the latest developments in your field, we believe that the posters will offer something of interest to everyone. So please join us at the conference and take advantage of this opportunity to learn and engage with your peers in industry and the academic community.
PO472: LASSIE: Lightning Risk Management for Wind Farms
Fernando Nicolás Naon, Full Stack Software Developer, Wind Power LAB
Abstract
Operation and maintenance (OPEX) remain a significant cost factor for wind energy, with unplanned repairs representing a major share of expenses. As turbines age and blade lengths increase, exposure to lightning grows, amplifying the risk of costly repairs and downtime. To address this challenge, the LASSIE lightning surveillance platform provides wind farm operators with a framework to monitor, plan, and document inspections and repairs, with a particular focus on lightning-induced damages. LASSIE combines data from national and global lightning detection networks to calculate the probability of attachment for each strike at the turbine level, factoring in turbine height, terrain, and strike location uncertainty. Strikes are grouped into flashes in accordance with the IEC 61400-24 standard, while operators receive tailored alerts based on probability, distance, turbine model, and lightning characteristics. Historical data is aggregated to identify turbines most exposed since their last inspection, and all actions are logged in a digital “logbook” to demonstrate prudent management. Use cases demonstrate tangible financial and operational benefits. In a U.S. case, LASSIE enabled early detection of nine lightning-damaged turbines, with estimated annual cost savings of USD 260,000. In a Norwegian wind farm, the platform helped optimize the annual inspection campaign by reducing the scope from 44 to 15 turbines, saving around EUR 80,000. These examples highlight how risk-based monitoring enables more efficient resource allocation and helps with early damage detection, consequently reducing the repair costs. Delegates will learn how to apply lightning surveillance to reduce unplanned repair costs and improve inspection planning. The framework can also be extended to integrate drone inspection data and other monitoring tools, enabling operators of all sizes to embed proactive, data-driven strategies into their workflows. By doing so, the industry can strengthen competitiveness, reduce OPEX, and support more cost-effective renewable energy production.
No recording available for this poster.
