The present thesis focuses on the study of algorithms for solving the Optimal Power Flow (OPF), a critical problem in the management of electrical networks. The main objective of this work is an in-depth analysis and comparison of some of the most relevant metaheuristic methodologies available in the literature, known for their ability to tackle complex and nonlinear problems. Following the theoretical analysis, two metaheuristic algorithms (DE and PSO) were implemented to address the OPF problem on different types of electrical networks: a small-scale network, a regional network, and a national network.
Il presente lavoro di tesi si concentra sullo studio di algoritmi per la risoluzione dell'Optimal Power Flow (OPF), un problema cruciale nella gestione delle reti elettriche. L'obiettivo principale della trattazione è lo studio approfondito e la comparazione di alcune delle più rilevanti metodologie metaeuristiche presenti in letteratura, strumenti noti per la loro capacità di affrontare problemi complessi e non lineari. In seguito all'analisi teorica, sono stati implementati due algoritmi metaeuristici (DE e PSO) per affrontare il problema OPF su diverse tipologie di reti elettriche: una rete di scala ridotta, una rete regionale e una rete nazionale.
Algoritmi metaeuristici per lo studio dell'Optimal Power Flow: un'analisi comparativa e applicazioni computazionali
GALLO, LEONARDO
2024/2025
Abstract
The present thesis focuses on the study of algorithms for solving the Optimal Power Flow (OPF), a critical problem in the management of electrical networks. The main objective of this work is an in-depth analysis and comparison of some of the most relevant metaheuristic methodologies available in the literature, known for their ability to tackle complex and nonlinear problems. Following the theoretical analysis, two metaheuristic algorithms (DE and PSO) were implemented to address the OPF problem on different types of electrical networks: a small-scale network, a regional network, and a national network.| File | Dimensione | Formato | |
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Gallo_Leonardo.pdf
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https://hdl.handle.net/20.500.12608/85233