Introduction
Wind energy has become a key player in the global transition toward renewable sources. The efficiency and costeffectiveness of wind farms are critical factors influencing their widespread adoption. Traditional control strategies often optimize turbines individually, overlooking wake interactions that can lower power output and increase mechanical loads. Recent approaches use centralized systems to optimize collective turbine behavior, improving power output and reducing structural stress. By integrating these advanced controllers with advancedComputational Fluid Dynamics (CFD) tools, wind farm performance can be simulated and optimized more effectively. This thesis explores the integration of wind plant controllers into an advanced open-source CFD tool to enhance wind farm control strategies.
Motivation
The cost of energy (CoE) from wind power can be reduced by improving the total power output and reducing turbine loads through effective control systems. The interactions between turbines, primarily through their wakes (characterized by turbulent airflow behind turbines) play a crucial role in the wind farm’s overall efficiency. Traditional models, which often operate on “greedy” principles focusing on individual turbine performance, neglecting inter-turbine wake effects, and resulting in suboptimal overall performance. Centralized control strategies, considering the collective behavior of turbines, can significantly improve total power output and efficiency. Advanced CFD tools with integrated wind plant control capabilities can provide a more realistic and effective approach to manage turbines interactions, leading to better performance and longer operational lifespans of turbines.
Goal
The primary goal of this MSc thesis is to integrate advanced wind plant controllers into an open-source Computational Fluid Dynamics (CFD) tool to simulate, evaluate, and optimize wind farm performance. This integration aims to develop a robust framework that accounts for complex wake dynamics and inter-turbine interactions, facilitating the creation of centralized control strategies that enhance overall wind farm efficiency and reduce operational costs.
Expected Outcomes
Upon successful integration and validation of the wind plant controller into the CFD tool, the expected outcomes are:
• Integrated Control-CFD Framework: A functional framework that integrates advanced wind plant
controllers with an open-source CFD tool. This framework will enable high-fidelity simulations of wind farms under various control strategies, accounting for dynamic wake interactions and turbine interactions.
• Optimized Wind Plant Performance: Demonstration of increased total power output and reduced mechanical loads across the wind plant through effective real-time control adjustments.
Special entry requirements
Advanced proficiency in C++ and Python programming, Good proficiency in Linux, Experiences with open-source CFD simulation tools such as OpenFOAM, Basic knowledge of control systems theory.
Supervisor
Hamidreza Abedi, Associate Professor, Div. of Safety and Transport, Dept. of Electrification and Reliability, Unit Renewable Energy Systems, RISE Research Institutes of Sweden (hamidreza.abedi@ri.se)
Educational area
Computer engineering, Mechanical and Industrial design engineering, Physics, Mathematics and Environment
Location
Gothenburg
Credits
30-60 hp (1-2 students). The compensation will be 30 000 SEK upon completion of a high-quality thesis.
Welcome with your application
Candidates are encouraged to send in their application as soon as possible. Suitable applicants will be interviewed as applications are received. Last day of application is November 12, 2024.
