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Optimization of BOS size in photovoltaic plants

Grant number: 19/10684-0
Support type:Scholarships in Brazil - Scientific Initiation
Effective date (Start): August 01, 2019
Effective date (End): July 31, 2020
Field of knowledge:Engineering - Electrical Engineering - Power Systems
Principal Investigator:Marcos Julio Rider Flores
Grantee:Madson Daniel Magalhães Pena
Home Institution: Faculdade de Engenharia Elétrica e de Computação (FEEC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil

Abstract

After defining the layout of a photovoltaic power plant (PPP), with the location of the photovoltaic modules (panels), from the restrictions of the terrain area, topography, type of the structure (fixed or tracker type) and geographic location of the PPP, the design of the electrical network and its components is carried out, known as Balance of System (BOS), whose objective is to determine the number, power and geo-referenced position of the inverters / transformers, using or not external stringboxes for the protection and parallelization on the Continuous Current (DC) side (between the photovoltaic modules and up to the inverters entrance), as well as the configuration and dimensioning of the DC and Alternating Current (AC) (from the inverters up to the substation transformer) electrical networks, minimizing the investment costs and the electrical losses, keeping the operation of the electrical network within the actual norm techniques. The work of scientific initiation aims to develop a methodology based on optimization to solve the problem of BOS location. The proposed methodology uses linearizations techniques to obtain a mathematical model of mixed integer linear programming (MILP) with a good approximation of the original mixed integer nonlinear programming model. The MILP model has the following benefits: (a) a robust mathematical model, general and flexible; (b) an efficient computational solution with conventional solvers; and (c) convergence to the optimal solutions is guaranteed using classical optimization techniques. A real photovoltaic power plant will be used as study case. The model will be implemented in the mathematical model language AMPL and solved using the solver CPLEX.