Multistate risk averse stochastic problems

• Grant number: 22/00443-9
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Start date: April 01, 2022
• End date: March 31, 2024
• Field of knowledge: Physical Sciences and Mathematics - Mathematics - Applied Mathematics
• Principal Investigator: Paulo José da Silva e Silva
• Grantee: Williams Jesus Lopez Yanez
• Host Institution: Instituto de Matemática, Estatística e Computação Científica (IMECC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Associated research grant: 18/24293-0 - Computational methods in optimization, AP.TEM

Abstract

The energy operation planning problem can be modeled as a very large multistage stochastic linear program. Dual dynamic stochastic programming is a standard technique for solving such problems. A characteristic of the uncertainties in the problem is their periodic behavior, typically, the inflows to the reservoirs follow the annual rainfall regime. The project proposes to analyze multistage stochastic optimization methods that explore periodic structures, based on recent works by A. Shapiro, in order to reduce the computational effort. The theoretical analysis will be validated by computer experiments, carried out in collaboration with CEPEL, in real cases of planning the operation of the Brazilian hydrothermal system.