Generation of synthetic flow scenarios by means of multivariate sampling of contemporaneous ARMA model outputs

Abstract

This work constitutes one of the outcomes of the “Evaluation of hydrological scenario generation models” activity initiated by the Hydrological Scenario Representation Working Group (GT CH) and coordinated by ONS and CCEE. We introduce the LYNX-Series model, a contemporaneous non-periodic and multivariate variation of the autoregressive moving average model (CARMA) for generating synthetic time series of average inflow discharges to reservoirs in the Brazilian National Interconnected System (SIN). Notably, LYNX-Series couples the synthetic series generator with a multivariate sampling process to select a group of synthetic hydrological scenarios based on a similarity criterion with recent historical data. In addition to reducing the computational burden of the hydrothermal dispatch optimization process, the solution aims to enhance the representativeness of synthetic hydrological scenarios. The paper expounds on the theoretical aspects of the model and presents numerical simulations that validate its ability to replicate hydrological behaviors in various Brazilian basins.

A framework to evaluate and compare synthetic streamflow scenario generation models

“…The fifth model is the LYNX-Series model, which is based on the Contemporaneous Autoregressive Moving Average -CARMA (Detzel et al, 2023). It represents a non-periodic and multivariate version of the Box & Jenkins or ARIMA family of stochastic models (Box et al, 2008).…”