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.
On 9 April at 17:15, we’ll also hold the main poster session and distinguish the 7 best posters of this year’s edition with our traditional Poster Awards Ceremony. Join us at the poster area to cheer and meet the laureates, and enjoy some drinks with all poster presenters!
We look forward to seeing you there!
PO092: Development of a methodology for precise prediction of electrical performance and losses in wind energy systems using PandaPower.
Jan Ackermann, Junior Wind & Site Assessment, PAVANA GmbH
Abstract
Wind energy plays a pivotal role in the transition to renewable energy. Developing a wind farm requires meticulous planning, where site conditions significantly influence energy yield. Key factors include wind conditions and other variables that affect the turbines power output. Using wind farm planning software like windPRO, energy production time series for each turbine are generated based on site conditions and power curves. These time series are crucial, providing essential data for Power Purchase Agreements, where buyers need to know when and how much energy they will receive. Additionally, the time series approach is vital for Power-to-X applications, where precise energy delivery is key. Since energy is remunerated at the grid connection point, internal electrical losses must be subtracted from these series. This study presents and validates a methodology for time-specific electric loss calculation using the Python library PandaPower. Unlike previous models, this approach accounts for all site conditions and the wind farm's topology, ensuring more accurate electric loss estimates. A graphical user interface was also developed to improve the model's usability. The model showed strong agreement with measured electric losses and provided clear advantages over standard assumptions. Validation was conducted in two ways: first, by comparing measured electric loss time series from eight wind farms with the calculated series, and second, by comparing results with those from PowerFactory software. Additionally, the study examines the impact of reactive power and cable temperature on electrical losses. Results indicate that reactive power feed-in and cable temperature generally do not significantly affect losses for the studied wind farms. However, with an anticipated increase in reactive power demand, these losses could become more significant and should be factored into future yield assessment. The influence of cable temperature is also topology-dependent: higher loads and longer cables increase the impact.
No recording available for this poster.
