Economic Dispatch Optimization of a grid with Wind & Storage

About Economic Dispatch Optimization of a grid with Wind & Storage

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BIOGRAPHY

I hold a PhD in Energy Economics from Imperial College London, specializing in machine learning, optimization, and data science applied to the energy sector. My LinkedIn is: /in/spyrosgnl

WHAT THIS COURSE IS ABOUT:

This course provides a comprehensive exploration of economic dispatch in power systems, with a particular emphasis on electricity grids incorporating storage. It offers a deep dive into the intricacies of defining input data, building models, formulating mathematical representations, and solving these models using Python/Pyomo and GAMS. The curriculum also covers practical debugging techniques and the application of the per-unit system, equipping students with essential skills for real-world scenarios.

As the course progresses, it introduces more complex scenarios, including the integration of CO2 constraints and the incorporation of renewable energy sources. This progression reflects the evolving challenges in modern power systems and prepares students for the complexities of sustainable energy management.

A key feature of the course is the hands-on experience it offers in modelling and solving economic dispatch problems, both with and without storage. Students gain a thorough understanding of the convexity of objective functions, a crucial concept in optimization. The course applies economic dispatch principles to both simple 1-bus grids and more complex 24-bus grids, providing a broad spectrum of practical applications.

This comprehensive approach makes the course suitable for a diverse audience, including students, researchers, and industry professionals. Importantly, no prerequisites are required, making it accessible to those new to the field as well as experienced practitioners looking to update their knowledge.

The regular updates to the course content ensure that the material remains current and relevant in the rapidly evolving field of power systems and economic dispatch. This commitment to ongoing improvement provides long-term value to students, encouraging them to revisit the material every 6-12 months to stay abreast of the latest developments and techniques in the field.