Mathematical Programming for Power Systems Operation: From Theory to Applications in Python (IEEE Press) - Hardcover

Über die Autorin bzw. den Autor

Alejandro Garcés, PhD, is a Professor at Universidad Tecnológica de Pereira in Colombia. Previously, he was a research fellow at the Norwegian University of Science and Technology in Trondheim-Norway, and an External Consultant for the Latin-American Organization of Energy and the Inter-American Development Bank. He is also Senior member of the IEEE, and Associate Editor of different IEEE and IET journals. In 2021 he was awarded with the Georg Forster Research fellow at the Alexander von Humboldt Foundation in Germany to continue his research in collaboration with TU-Dortmund.

Von der hinteren Coverseite

Explore the theoretical foundations and real-world power system applications of convex programming

In Mathematical Programming for Power Systems Operation: From Theory to Applications in Python, Professor Alejandro Garcés delivers a comprehensive overview of power system operations models with a focus on convex optimization models and their implementation in Python. Divided into two parts, the book begins with a theoretical analysis of convex optimization models before moving on to related applications in power systems operations.

The author eschews concepts of topology and functional analysis found in more mathematically oriented books in favor of a more natural approach. Using this perspective, he presents recent applications of convex optimization in power system operations problems.

Mathematical Programming for Power System Operation with Applications in Python uses Python and CVXPY as tools to solve power system optimization problems and includes models that can be solved with the presented framework. The book also includes:

• A thorough introduction to power system operation, including economic and environmental dispatch, optimal power flow, and hosting capacity
• Comprehensive explorations of the mathematical background of power system operation, including quadratic forms and norms and the basic theory of optimization
• Practical discussions of convex functions and convex sets, including affine and linear spaces, politopes, balls, and ellipsoids
• In-depth examinations of convex optimization, including global optimums, and first and second order conditions

Perfect for undergraduate students with some knowledge in power systems analysis, generation, or distribution, Mathematical Programming for Power System Operation with Applications in Python is also an ideal resource for graduate students and engineers practicing in the area of power system optimization.

Aus dem Klappentext

Explore the theoretical foundations and real-world power system applications of convex programming

In Mathematical Programming for Power Systems Operation: From Theory to Applications in Python, Professor Alejandro Garcés delivers a comprehensive overview of power system operations models with a focus on convex optimization models and their implementation in Python. Divided into two parts, the book begins with a theoretical analysis of convex optimization models before moving on to related applications in power systems operations.

The author eschews concepts of topology and functional analysis found in more mathematically oriented books in favor of a more natural approach. Using this perspective, he presents recent applications of convex optimization in power system operations problems.

Mathematical Programming for Power System Operation with Applications in Python uses Python and CVXPY as tools to solve power system optimization problems and includes models that can be solved with the presented framework. The book also includes:

• A thorough introduction to power system operation, including economic and environmental dispatch, optimal power flow, and hosting capacity
• Comprehensive explorations of the mathematical background of power system operation, including quadratic forms and norms and the basic theory of optimization
• Practical discussions of convex functions and convex sets, including affine and linear spaces, politopes, balls, and ellipsoids
• In-depth examinations of convex optimization, including global optimums, and first and second order conditions

Perfect for undergraduate students with some knowledge in power systems analysis, generation, or distribution, Mathematical Programming for Power System Operation with Applications in Python is also an ideal resource for graduate students and engineers practicing in the area of power system optimization.