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Marlyn Dayana Cuadrado Guevara
2020
Multistage Scenario Trees Generation for Renewable Energy Systems Optimization
Dept. of Statistics and Operations Research. Prof. F.-Javier Heredia, advisor.
Barcelona
Universitat Politècnica de Catalunya-BarcelonaTech
194
research
Battery energy storage systems
Electricity markets
Ancillary services market
Wind power generation
Virtual power plants
Multistage Stochastic programming
phd thesis
The presence of renewables in energy systems optimization have generated a high level of uncertainty in the data, which has led to a need for applying stochastic optimization to modelling problems with this characteristic. The method followed in this thesis is Multistage Stochastic Programming (MSP). Central to MSP is the idea of representing uncertainty (which, in this case, is modelled with a stochastic process) using scenario trees. In this thesis, we developed a methodology that starts with available historical data; generates a set of scenarios for each random variable of the MSP model; defines individual scenarios that are used to build the initial stochastic process (as a fan or an initial scenario tree); and builds the final scenario trees that are the approximation of the stochastic process.
http://hdl.handle.net/2117/334943