Periodic Reporting for period 2 - FLOATECH (Optimization of floating wind turbines using innovative control techniques and fully coupled open source engineering tool)
Berichtszeitraum: 2022-07-01 bis 2023-12-31
Wind is one of the most important sources of renewable energy contributing to the EU's energy mix. Its development is key to meeting future environmental and energy policy objectives. Due to the limited availability of onshore sites, offshore wind is becoming increasingly important to ensure the continued growth of the sector. In this scenario, exploiting the vast wind resources in deeper waters using floating wind farms and developing the necessary technology will boost the EU economy and contribute to achieving its green energy goals. The FLOATECH project aimed to advance the technical maturity and cost competitiveness of floating offshore wind energy. This was achieved through two types of actions. First, a fully coupled aero-hydro-servo-elastic design and simulation environment (called QBlade-Ocean) was developed (A1). The more advanced modeling approaches will lead to a reduction of uncertainties in the design process and subsequently to more efficient, reliable and cost-effective floating wind turbines (WTs). In addition, two innovative control techniques (active wave-based feedforward and active wake mixing strategies) are introduced (A2). Both will increase the energy yield of floating wind farms and, in the case of the wave-based control, could also provide beneficial services to the energy grid.
Work Package 1 focuses on the development of the open-source simulation tool (ST) QBlade-Ocean (QB). More specifically, the simulation software was expanded by the capability to model offshore WTs (floating and bottom fixed). Additionally, a higher order aerodynamic solver was implemented into the software tool and the ST NEMOH was extended with the capability to generate QTFs. An interface between QB and NEMOH was created. A project partner training was carried out to convey all the knowledge needed to run simulations in QB to its fullest capability.
The objective of WP2 was to validate the new capabilities of QB and to quantify the achieved reduction of uncertainties. Thereby, differing floater concepts are simulated in QB and compared to experimental results and/or state-of-the-art (SOTA) STs. The validation is performed on a variety of load cases. The second task revealed that the use of higher fidelity simulation reduced fatigue loads and thus indicate a potential to reduce the cost of FOWTs.
WP3 focuses on the development of the novel feed forward wave-based controller to minimize oscillations and thus fatigue loads over the lifetime of a WT (A2). The necessary interface of the controller with QB was achieved in the first period. The wave control logic was tested in an experimental environment during the second reporting period. A key finding was that even though platform motion could be achieved only minor influence on loads could be obtained. A different objective with the same control logic applied led to a more constant power output of the WT, possibly leading to benefits on a grid level. Furthermore, a radar was under operation for multiple months mounted on the Floatgen turbine to validate the capability to predict wave amplitudes and subsequently wave forces. As this information is a requirement to implement the feed forward strategy. The radar amplitude measurements could be validated with a buoy that was positioned on site.
The second innovative control method in A2 is the application of wake mixing control strategies on floating offshore WTs in WP4. To understand how and at which frequency the wake can be excited most efficiently, an investigation to better understand the physical phenomenon of the wake breakdown has been undertaken. Additionally, the effects of platform motion and atmospheric conditions on the breakdown were investigated. Based on these results, a design optimization of various floating platforms for wind turbines with the objective to maximize the wake recovery with minimal control inputs has been carried out. Furthermore, the control techniques have been tested in an experimental set up using PIV to get a better understanding of the physical phenomenon of the wake breakdown and further improve computational tools.
Within WP5 a spread-sheet based tool was developed in order to allow for a flexible way to estimate LCOE reductions based on the novel control methods developed in A2 were. The cost analysis tool was release in open-source and an overall cost-reduction potential of up to 6% was seen.
In WP6, several communication efforts towards the broader public were made, including the set up of a project website, LinkedIn and Twitter profiles. Interviews on radio broadcasts, an easy to understand motion design video and publications in general public oriented journals were produced. Moreover, the industry was targeted with a publication on WindTech Internatioal presenting the novel technologies developed within FLOATECH. More dissemination actions were carried out through participation at two WindEurope events, one including the co-organization of a side event. Aside from the above, the project was presented to peers through presentations at multiple scientific conferences (Torque 2022, WESC 2023, OMAE 2023, etc.). Two webinars were organized and finally, the key outcomes of the project were presented during an infoday event in berlin that was attended by researches, policymakers, engineers and students.
WP7 focused on the project management and the communication with the EC.
The objective of WP2 was to validate the new capabilities of QB and to quantify the achieved reduction of uncertainties. Thereby, differing floater concepts are simulated in QB and compared to experimental results and/or state-of-the-art (SOTA) STs. The validation is performed on a variety of load cases. The second task revealed that the use of higher fidelity simulation reduced fatigue loads and thus indicate a potential to reduce the cost of FOWTs.
WP3 focuses on the development of the novel feed forward wave-based controller to minimize oscillations and thus fatigue loads over the lifetime of a WT (A2). The necessary interface of the controller with QB was achieved in the first period. The wave control logic was tested in an experimental environment during the second reporting period. A key finding was that even though platform motion could be achieved only minor influence on loads could be obtained. A different objective with the same control logic applied led to a more constant power output of the WT, possibly leading to benefits on a grid level. Furthermore, a radar was under operation for multiple months mounted on the Floatgen turbine to validate the capability to predict wave amplitudes and subsequently wave forces. As this information is a requirement to implement the feed forward strategy. The radar amplitude measurements could be validated with a buoy that was positioned on site.
The second innovative control method in A2 is the application of wake mixing control strategies on floating offshore WTs in WP4. To understand how and at which frequency the wake can be excited most efficiently, an investigation to better understand the physical phenomenon of the wake breakdown has been undertaken. Additionally, the effects of platform motion and atmospheric conditions on the breakdown were investigated. Based on these results, a design optimization of various floating platforms for wind turbines with the objective to maximize the wake recovery with minimal control inputs has been carried out. Furthermore, the control techniques have been tested in an experimental set up using PIV to get a better understanding of the physical phenomenon of the wake breakdown and further improve computational tools.
Within WP5 a spread-sheet based tool was developed in order to allow for a flexible way to estimate LCOE reductions based on the novel control methods developed in A2 were. The cost analysis tool was release in open-source and an overall cost-reduction potential of up to 6% was seen.
In WP6, several communication efforts towards the broader public were made, including the set up of a project website, LinkedIn and Twitter profiles. Interviews on radio broadcasts, an easy to understand motion design video and publications in general public oriented journals were produced. Moreover, the industry was targeted with a publication on WindTech Internatioal presenting the novel technologies developed within FLOATECH. More dissemination actions were carried out through participation at two WindEurope events, one including the co-organization of a side event. Aside from the above, the project was presented to peers through presentations at multiple scientific conferences (Torque 2022, WESC 2023, OMAE 2023, etc.). Two webinars were organized and finally, the key outcomes of the project were presented during an infoday event in berlin that was attended by researches, policymakers, engineers and students.
WP7 focused on the project management and the communication with the EC.
Both of the first two actions exceed the current SOTA in the simulation (A1) and control (A2) of floating offshore wind turbines. Focusing first on A1, QB already matches SOTA. In some cases, it even surpasses it due to its ability to combine a variety of hydrodynamic force modeling approaches with a medium-fidelity, lift line-based aerodynamic solver and a nonlinear structural solver. The SOTA has been further enhanced by coupling QB with the open-source software HOS-Ocean, making QBlade the first wind turbine ST capable of simulating higher-order spectral wave loads. The impact of such an accurate ST could significantly influence the way floating WTs are designed by reducing the required safety margins.
A2 includes two control strategies, both of which aim to outperform the current SOTA through innovative solutions. Both technologies have been successfully developed and applied in this project. The active wave-based control allows the wave-excited oscillations to be mitigated, but at the cost of adding non-negligible fatigue loads over the life cycle of the turbine. However, in an additional control mode, the power fluctuations due to the oscillatory motion could be mitigated, resulting in cost savings at the grid level. The second control strategy uses the innovative pulse and helix concepts to apply wake mixing to the turbine wake. Both concepts excite the wake of a turbine, thereby accelerating its collapse. This results in a faster recovery of the wake velocity, allowing a downwind turbine to generate more power. The application of this concept, especially the Helix, to floating WTs increases efficiency, as cost analyses have shown a potential reduction in LCOE of up to 6% on a farm level.
A2 includes two control strategies, both of which aim to outperform the current SOTA through innovative solutions. Both technologies have been successfully developed and applied in this project. The active wave-based control allows the wave-excited oscillations to be mitigated, but at the cost of adding non-negligible fatigue loads over the life cycle of the turbine. However, in an additional control mode, the power fluctuations due to the oscillatory motion could be mitigated, resulting in cost savings at the grid level. The second control strategy uses the innovative pulse and helix concepts to apply wake mixing to the turbine wake. Both concepts excite the wake of a turbine, thereby accelerating its collapse. This results in a faster recovery of the wake velocity, allowing a downwind turbine to generate more power. The application of this concept, especially the Helix, to floating WTs increases efficiency, as cost analyses have shown a potential reduction in LCOE of up to 6% on a farm level.