Electric distribution network optimization

This thesis primarily investigates the electric distribution network reconfiguration problem, which is crucial for enhancing the operational efficiency and reliability of power distribution systems amidst an evolving energy landscape. The increasing integration of fluctuating renewable energy sources and the rise in electrification of end-use sectors underscore the growing importance of this problem. In addition to network reconfiguration, this research explores other pivotal network optimization challenges, including the integration of renewables into power systems, providing a comprehensive examination of various operational complexities. The series of scholarly papers presented herein detail innovative solutions to these multifaceted issues. The core contribution of the thesis is the development of a math-heuristic algorithm, named the "corridor-method," designed for rapid and efficient network reconfiguration. This algorithm not only minimizes computational demands but also preserves the integrity of solutions and has been successfully implemented in the MV network of areti, the Distribution System Operator (DSO) of Rome, resulting in significant improvements in the network's balancing KPIs. Furthermore, this thesis introduces an innovative approach to formulating radiality constraints, incorporating a lazy-constraints separation method into mixed-integer linear programming to address optimization in large-scale network instances. Expanding the investigation further, the thesis delves into the pure combinatorial properties of radial operation in electricity distribution networks, uncovering a profound connection with matroid theory that exposes a wealth of combinatorial properties. These findings have been utilized to develop robust formulations of radiality. The cumulative contributions of this research not only advance the theoretical boundaries of electrical network optimization but also furnish practical, actionable strategies for real-world applications. These advancements significantly enhance network adaptability, efficiency, and reliability, thereby impacting both academic research and industry practices. Additionally, the thesis presents optimization studies related to broader power system dynamics. Particularly, the final chapters focus on examining aspects of a fully renewable power system. Readers interested in a deeper understanding of power system dynamics are encouraged to refer to these sections for a more comprehensive perspective.