Using probabilistic networks to allocate resources in a power distribution system

• Grant number: 23/07634-7
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate (Direct)
• Start date: November 13, 2023
• End date: October 30, 2024
• Field of knowledge: Engineering - Electrical Engineering - Power Systems
• Principal Investigator: Carlos Dias Maciel
• Grantee: Henrique de Oliveira Caetano
• Supervisor: Marco Aiello
• Host Institution: Escola de Engenharia de São Carlos (EESC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
• Institution abroad: University of Stuttgart, Germany
• Associated to the scholarship: 21/12220-1 - Resilience analysis of distribution systems using probabilistic networks, BP.DD

Abstract

Power distribution systems are critical infrastructures that play a vital role in providing reliable electricity to society. Assessing the resilience of these systems is crucial for maintaining their stability in the face of disruptive events. Probabilistic frameworks, such as Bayesian Networks, have emerged as valuable tools for evaluating the resilience of critical infrastructures. However, there is a need to improve current literature regarding the allocation of distributed generation and electric vehicles, considering the probabilistic nature of these elements and their impact on system resilience and carbon emissions. This research project aims to fill this gap by leveraging probabilistic graph models to enhance resource allocation strategies in power distribution systems. By accurately modeling uncertainties and interactions, informed decision-making and optimal allocation strategies can be developed to enhance efficiency, reliability, and resilience while incorporating sustainable solutions. The integration of environmental aspects, such as carbon emissions, enables a comprehensive assessment of resilience in terms of both energy supply and environmental impact. The interdisciplinary approach, combining probability theory, power systems engineering, and environmental sustainability, holds great potential for advancing resource allocation practices and building a sustainable and robust energy future. (AU)