Program Overview
This one-day intensive program delves into the emerging intersection of wind energy and quantum computing, focusing on how quantum algorithms can model complex multi-turbine interactions far beyond the capacity of classical methods. Led by an expert with over 25 years in renewable energy innovation, the course provides a clear understanding of quantum simulation principles, showcases global case studies, and enables participants to explore strategic applications within their own wind farm environments. Through a blend of conceptual grounding, real-world insights, and hands-on exercises, the program helps professionals identify how to unlock optimization opportunities and improve wind flow efficiency using next-gen computation.
Features
- Grasp the fundamentals of quantum computing in the context of wind energy simulation
- Understand the aerodynamic complexities in multi-turbine environments
- Evaluate real-world quantum applications for wind farm layout optimization
- Explore how to apply quantum tools to enhance energy yield and reduce wake loss
Target audiences
- Simulation Engineers
- Renewable Energy Professionals
- Innovation & Strategy Leads
- Energy Project Managers
Curriculum
- 4 Sections
- 15 Lessons
- 1 Day
Expand all sectionsCollapse all sections
- Foundations of Turbine Interactions & Limitations of Classical Simulations4
- 1.1Basics of wake effects, turbine interference, and farm layout inefficiencies
- 1.2Computational Fluid Dynamics (CFD) vs emerging simulation techniques
- 1.3Quantum computing: principles, qubits, superposition, entanglement
- 1.4Key Terms: Wake loss, vortex shedding, wind shear, interference modeling, classical vs quantum optimization, decoherence
- Quantum Computing in Wind Simulation — What’s Possible Today5
- 2.1Current state of quantum computing (hardware & software platforms)
- 2.2How quantum algorithms like QAOA and VQE model multi-variable interdependencies
- 2.3Case studies of simulation in aerospace & energy domains
- 2.4What makes wind turbine layout a high-potential use case
- 2.5Key Terms: Qiskit, QAOA (Quantum Approximate Optimization Algorithm), VQE (Variational Quantum Eigensolver), hybrid quantum-classical algorithms, IBM Q, Google Sycamore, quantum supremacy
- Real-World Deployments & Industry Experiments3
- Interactive Simulation3
Instructor
