Posters

Abstract

The natural world (e.g., birds, fish, etc.) moves collectively to achieve higher efficiency together. The already tested and deployed Swarm IoT platform enables collective behavior by connecting the turbines in the wind farm, allowing them to communicate with one another to identify optimal yaw control strategies to increase efficiency. The data coming from all the turbines is leveraged in this closed-loop system to run multiple control applications in parallel: 1. Wind turbine level yaw optimization through online static yaw misalignment correction: Regular monitoring and correction of the turbine nacelle positioning to reduce the loads and optimize the power production. 2. Wind farm level yaw optimization through collective yaw solution: Turbine yaw activity is governed by a consensus estimate of wind direction, which is determined using all available wind direction information from across the wind plant. Collective yaw provides a more accurate estimate of the global wind direction and prevents the turbines from chasing turbulence, thereby reducing total yaw activity. 3. Wind farm wake mitigation through wake steering: Off-yawing upwind turbines to reduce the downstream wake impact and increase the overall efficiency of the wind farm. Although the production of the upwind turbine will be slightly reduced, the significantly higher production of the downwind turbine leads to a net production benefit. 4. Wind farm level resilience through predictive yaw: Predicting wind direction changes using data from upstream turbines allows downstream turbines to proactively yaw to increase energy capture and build resilience. In addition to these four applications, the IoT platform allows the possibility of layering on additional applications focused on sensing and data monitoring, like blade icing detection or lightning detection, where the information of an event detected in one turbine can be used to protect or optimize the rest of the turbines in the wind farm.