A python framework for optimal sizing and allocation of distributed energy resources

• Grant number: 23/13121-2
• Support Opportunities: Scholarships abroad - Research Internship - Scientific Initiation
• Start date: December 01, 2023
• End date: February 29, 2024
• Field of knowledge: Engineering - Electrical Engineering - Power Systems
• Principal Investigator: Marcos Julio Rider Flores
• Grantee: Marcelo Montandon Magalhães
• Supervisor: João André Pinto Soares
• Host Institution: Faculdade de Engenharia Elétrica e de Computação (FEEC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Institution abroad: Instituto Superior de Engenharia do Porto (ISEP), Portugal
• Associated to the scholarship: 22/12677-4 - Optimal Sizing and Allocation of Distributed Energy Resources in Microgrids, BP.IC

Abstract

In the last years, the climate has become more extreme. Renewable energy generation could be sevearly affected due to its climate dependency. In this context, demand emerges for a decentralized renewable grid, contributing to decarbonization and increasing reliability. Renewable energy resources (RES) are fundamental to decarbonization, yet they are difficult to implement in small scale due to their stochastic nature. Microgrids emerge as a solution, by combining multiple technologies, such as distributed renewables (solar, wind, hidrogen, biogas), energy storage (batteries, flywheels) and demand management (energy efficiency, demand response) a microgrid is capable of using the clean renewable energy whilst taking into ac-count its stochastic nature. This research proposes the development of microgridsizing models that can both provide demanded energy and operate in unfavorable conditions. The development will take place by adapting the original AMPL developed model into a Python Framework and adding a second objective, minimum carbon emissions. The new Python Framework will be a multi-objective program, resulting in a Pareto curve, each solution can be chosen by the user depending on available resources. Alongside the development, the candidate will accompany Prof. Dr. Jo ao P. Soares research. (AU)