Mathematical Programming for Power Systems Operation

<p><b>Explore the theoretical foundations and real-world power system applications of convex programming</b></p> <p>In <i>Mathematical Programming for Power System Operation with Applications in Python</i>, Professor Alejandro Garces 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.</p> <p>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.</p> <p><i>Mathematical Programming for Power System Operation with Applications in Python</i> 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:</p> <ul> <li>A thorough introduction to power system operation, including economic and environmental dispatch, optimal power flow, and hosting capacity</li> <li>Comprehensive explorations of the mathematical background of power system operation, including quadratic forms and norms and the basic theory of optimization</li> <li>Practical discussions of convex functions and convex sets, including affine and linear spaces, politopes, balls, and ellipsoids</li> <li>In-depth examinations of convex optimization, including global optimums, and first and second order conditions</li> </ul> <p>&nbsp;Perfect for undergraduate students with some knowledge in power systems analysis, generation, or distribution, <i>Mathematical Programming for Power System Operation with Applications in Python</i> is also an ideal resource for graduate students and engineers practicing in the area of power system optimization.</p>