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Development of a mathematical programming model for the optimal allocation of batteries in electrical distribution systems based on spatial and temporal analysis techniques

Grant number: 21/06251-1
Support Opportunities:Scholarships in Brazil - Doctorate
Effective date (Start): April 01, 2022
Field of knowledge:Engineering - Electrical Engineering - Power Systems
Principal Investigator:John Fredy Franco Baquero
Grantee:Norberto Abrante Martinez
Host Institution: Faculdade de Engenharia (FEIS). Universidade Estadual Paulista (UNESP). Campus de Ilha Solteira. Ilha Solteira , SP, Brazil
Associated scholarship(s):23/02389-4 - Machine learning combined with spatio-temporal analysis technics for battery sizing and allocation in electrical distribution systems, BE.EP.DR


The constant development of battery technologies motivates the interest in their adoption in the Electrical Distribution System (EDS). Despite the benefits they can provide to the EDS, investments in battery systems are still high; therefore, the planning of its allocation (at which node of the electrical network it will be connected), sizing (module capacity and inverter power) and operation (energy absorption and injection times) must be carefully evaluated. Although several methods have been applied in battery planning in the EDS, important aspects not previously considered such as changes in renewable generation (e.g., the increased connection of distributed generators to the grid) and load (e.g., increased consumption and/or profile change due to socioeconomic factors) can be incorporated into the decision process with the application of spatial-temporal analysis techniques. The concepts of technical and economic elasticity involved in the relations between the presence of batteries, the integration of DG, and the load can also be considered, since the effects of this elastic relation can influence the allocation and sizing of batteries. In this context, this research project proposes the development of a mathematical programming model for the optimal allocation, sizing, and operation of batteries in the EDS based on spatio-temporal analysis techniques and elasticity concepts. The research should lead to a holistic decision support method that takes into account the elastic relations and the spatio-temporal dynamics associated with the interaction between batteries, integration of renewable generation, and increased demand, which is useful in the EDS planning. (AU)

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