Smart meter-driven construction of electrical low voltage network models for hosting capacity studies

• Grant number: 24/21082-0
• Support Opportunities: Scholarships abroad - Research Internship - Master's degree
• Start date: February 15, 2025
• End date: August 14, 2025
• Field of knowledge: Engineering - Electrical Engineering - Power Systems
• Principal Investigator: Walmir de Freitas Filho
• Grantee: Augusto Janssen Harger da Silva
• Supervisor: Luis Fernando Ochoa Pizzali
• Host Institution: Faculdade de Engenharia Elétrica e de Computação (FEEC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Institution abroad: University of Melbourne, Australia
• Associated to the scholarship: 23/07072-9 - Data analytics-based methods to estimate the rooftop-PV hosting capacity in distribution systems using smart meters, BP.MS

Abstract

Efficient management of rooftop photovoltaic (PV) interconnection is a key challenge for power distribution utilities worldwide. In Brazilian utilities, the workload has excessively increased due to the amount of connection requests and to current regulation practices requiring utilities to present detailed studies to customers for each connection request. Additionally, accurate low voltage (LV) networks electrical models necessary for interconnection studies are often unavailable, since utilities' databases contain multiple errors due to wrong data registration, absence of data, and outdated information, resulting in unreliable interconnection studies. In this context, the M.Sc. project associated with this Research Internship Abroad Project (BEPE-MS) aims to construct reliable LV networks electrical models and develop a hosting capacity estimation method to expedite the assessment of PV connection requests. First, a multiple linear regression is applied to smart meter data to construct the LV network electrical model. Then, the hosting capacity of all customers' connection points are calculated simultaneously in a single matrix operation based on sensitivity coefficients. This procedure helps utilities quickly assess new rooftop PV connection requests without relying on imprecise databases. This BEPE project proposes a visit to The University of Melbourne, supervised by Prof. Ochoa. The candidate will interact with highly qualified researchers and data from industrial projects. In addition, given the expertise of Prof. Ochoa's research group on analysis of distribution systems, data-analytics, and others, the candidate will benefit from learning new tools and approaches that will enhance the proposed procedure.