Optimization Approaches for Enhanced Operation and Planning of Distribution Systems: A Multi-Objective Perspective
Name: RENATO SANTOS FREIRE FERRAZ
Publication date: 25/02/2025
Examining board:
Name |
Role |
|---|---|
| AUGUSTO CESAR RUEDA MEDINA | Presidente |
| CLAINER BRAVIN DONADEL | Examinador Externo |
| JOHN FREDY FRANCO BAQUERO | Examinador Externo |
| JUSSARA FARIAS FARDIN | Examinador Interno |
| OURESTE ELIAS BATISTA | Examinador Interno |
Summary: Efficient planning and operation strategies are essential for modern electric power networks to ensure cost-effective electricity delivery while maintaining reliable performance. However, the ongoing transformation of traditional centralized distribution systems, driven by the integration of distributed energy resources (DERs) and the growing adoption of electric vehicles (EVs), has
introduced new and complex challenges for distribution system operators (DSOs). To address these issues, this thesis proposes multi-objective optimization approaches aimed at enhancing the planning and operation of distribution networks from the system DSO’s perspective. The first approach focuses on the optimized allocation and sizing of DERs while ensuring recloserfuse
coordination to preserve the original network protection scheme. The second approach handles the static network reconfiguration problem, incorporating the allocation and sizing of DERs and capacitors. The third approach extends this to dynamic network reconfiguration, considering DERs, capacitors, and electric vehicle charging stations. Finally, the fourth approach explores the dynamic network reconfiguration, capacitors allocation, and on-load tap changer adjustment, while accounting for stochastic customer-owned DERs. The main objectives are to minimize investment and operational costs, improve the system’s performance indicators–such as power losses and voltage deviation–and ensure the proper operation of the distribution system. Stochastic variations in DER generation, load profiles, and EV distribution throughout the day are modeled using the Monte Carlo Method. The multi-objective optimization problems are solved using the Non-dominated Sorting Genetic Algorithm II and the Multi-objective Cuckoo Search, with the final solution selected through the Fuzzy Decision-making Method. The results demonstrate significant improvements in the performance indicators of the distribution system, achieved while meeting all operational constraints.
