Development of a mixed-integer linear programming model for the sizing of a microgrid based on renewable energy and batteries to power a smart building and electric vehicles

• Grant number: 23/02583-5
• Support Opportunities: Scholarships abroad - Research Internship - Master's degree
• Start date: September 01, 2023
• End date: February 29, 2024
• Field of knowledge: Engineering - Electrical Engineering - Power Systems
• Principal Investigator: John Fredy Franco Baquero
• Grantee: Dayara Pereira Basso
• Supervisor: José Manuel Arroyo Sánchez
• Host Institution: Faculdade de Engenharia (FEIS). Universidade Estadual Paulista (UNESP). Campus de Ilha Solteira. Ilha Solteira , SP, Brazil
• Institution abroad: Universidad de Castilla-La Mancha, Ciudad Real (UCLM), Spain
• Associated to the scholarship: 21/14389-3 - Development of Optimization Methods for the Sizing of a Hybrid Microgrid for an Autonomous Charging Station of Electric Vehicles, BP.MS

Abstract

The energy sector and the transport sector are responsible for most of the pollutant emissions. An alternative to mitigate the climate crisis is the use of electric vehicles (EVs) to perform services and deliver goods, e.g., passenger transport, couriers and food delivery. However, there are communities that are far from urban centers and that have a non-reliable energy supply, which often hinders the adoption of EVs, as their autonomy may be insufficient to serve customers further away. Thus, aiming to plan an efficient energy infrastructure, a smart building could house a microgrid composed of renewable energy and batteries, capable of recharging EVs that provide services in the region and supplying internal loads of the building, promoting the modernization of the system and contributing to a more sustainable community. Thus, this project proposes the development of a mixed-integer linear programming model for the sizing of a microgrid with photovoltaic energy and batteries allocated in a smart building in a remote community, which is capable of feeding loads and recharging EVs that provide services in the region. The model will be implemented in the AMPL language and solved using the commercial solver CPLEX, to obtain a solution composed by the optimal EV route, the optimal number of photovoltaic panels and battery units to compose the microgrid. In addition, EV constraints will be considered in the model to satisfy battery status along the route, as well as energy consumption and navigation time. Finally, it is proposed to analyze the corresponding environmental impact, i.e., the amount of pollutants emitted in the environment that would be avoided by adopting EVs to provide services in these communities. (AU)