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Development of Optimization Methods for the Sizing of a Hybrid Microgrid for an Autonomous Charging Station of Electric Vehicles

Grant number: 21/14389-3
Support Opportunities:Scholarships in Brazil - Master
Effective date (Start): November 01, 2022
Effective date (End): August 31, 2024
Field of knowledge:Engineering - Electrical Engineering - Power Systems
Principal Investigator:John Fredy Franco Baquero
Grantee:Dayara Pereira Basso
Host Institution: Faculdade de Engenharia (FEIS). Universidade Estadual Paulista (UNESP). Campus de Ilha Solteira. Ilha Solteira , SP, Brazil
Associated scholarship(s):23/02583-5 - 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, BE.EP.MS

Abstract

Providing services with electric vehicles (EVs), e.g., delivery of goods, periodic technical maintenance, and medical visits can be a challenging task when performed in remote communities. These communities, characterized by being far from large metropolitan centers and not having a reliable supply of resources, particularly electricity, face difficulties in providing services offered with EVs due to their relatively low autonomy and difficulties for charging. In this context, the implementation of charging stations in the remote community would offer greater energy security, allows the use of EVs, promote sustainability in these communities, and contribute to the reduction of greenhouse gas emissions. Thus, this research proposes the development of optimization methods for the sizing of a hybrid microgrid based on renewable energy to supply an autonomous charging station for EVs that provide services in remote communities. First, a Mixed Integer Linear Programming model will be formulated, which must be implemented in the mathematical modeling language AMPL and solved using commercial solvers. Next, an optimization algorithm based on the Iterated Local Search meta-heuristic will be developed, using the C programming language. Finally, the performance of the methods will be analyzed considering the associated costs, the environmental benefit, as well as the computational effort required to find the solution.

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