Presentations

Abstract

This paper presents the Software- and Hardware-in-the-Loop (SiL/HiL) validation of an online wake-steering control system designed for real-time wind farm operation. Building on previous work focused on control design and SiL assessment, the present study targets a full real-time validation architecture based on two interconnected real-time platforms: one hosting the wake-steering control system and the other emulating a virtual wind farm. The objective is to bridge the gap between algorithmic development and experimental deployment by validating both control performance and real-time implementation aspects under realistic execution constraints. The proposed HiL setup relies on two Speedgoat real-time target machines communicating through an Ethernet-based User Datagram Protocol (UDP). The first target runs the online wake-steering controller, including wind condition estimation, supervisory logic, actuator management, and either look-up-table-based or online model-based yaw optimization. The second target implements a virtual wind farm, providing turbine-level measurements and accepting yaw setpoints in real time. This separation mirrors a realistic control architecture in which the wind farm controller interacts with an external physical system through a constrained communication interface, thereby enabling the assessment of timing, synchronization, latency, and data integrity effects. The virtual wind farm currently embeds a steady-state wind farm flow model coupled with a virtual SCADA layer generating realistic turbine measurements, including turbulent 1 Hz signals and non-ideal yaw actuator dynamics. The HiL configuration allows the controller to be executed with the same compiled code and fixed-step real-time constraints as would be used in field experiments, while interacting with a fully independent real-time simulation of the controlled system. This enables systematic testing of control update rates, communication delays, packet loss sensitivity, and actuator limitations, which cannot be reliably assessed in pure SiL environments. In addition, the paper discusses ongoing work toward the integration of a medium-fidelity dynamic wind farm flow model within the virtual farm real-time target. Such an extension would allow the HiL framework to capture wake advection, transient flow effects, and dynamic turbine–wake interactions, further increasing the representativeness of the validation environment for closed-loop wind farm control strategies. Results obtained on a representative offshore wind farm configuration demonstrate the feasibility and robustness of the proposed HiL architecture for online wake-steering validation. The presented framework provides a scalable and flexible basis for the progressive qualification of advanced wind farm control strategies, from algorithmic prototyping to real-time hardware testing, prior to full-scale experimental deployment.