Tuesday, 13:45 - 14:10 h, Room: MA 550


Raphael Gonçalves
Analyzing multistage stochastic optimization methods to solve the operation planning problem of hydrothermal systems

Coauthors: Edson L. da Silva, Erlon C. Finardi


The operation planning of hydrothermal systems is, in general, divided into coordinate steps which have different horizons and prioritizes distinct details of the modeling. The medium-term operation planning (MTOP) problem, one of the operation planning steps of hydrothermal systems and the focus of this work, aims to define the weekly generation for each plant, regarding the uncertainties related to water inflows to reservoirs, to obtain the minimum expected operational cost over a specific period. Solving this problem requires a high computational effort and, consequently, the use of multistage stochastic programming algorithms. Therefore, the main purpose of this work is to present a comparative study about the performance of different multistage stochastic optimization methods applied to the MTOP: Nested decomposition (ND) and the progressive hedging (PH) method. With respect to PH method, the algorithm properties and the problem features are studied to assess suitable decomposition schemes to obtain lower CPU time. To evaluate the performance of the both algorithm regarding its particularities, the Brazilian hydrothermal system is studied.


Talk 2 of the invited session Tue.2.MA 550
"Stochastic programming models for electricity generation planning" [...]
Cluster 18
"Optimization in energy systems" [...]


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