Abstract

The complex processes involved in the determination of the availability of power from renewable energy sources, such as wind power, impose great challenges in the forecasting processes carried out by transmission system operators (TSOs). Nowadays, many of these TSOs use operation planning tools that take into account the uncertainty of the wind-power. However, most of these methods typically require strict assumptions about the probabilistic behavior of the forecast error, and usually ignore the dynamic nature of the forecasting process.In this paper a methodological framework to obtain Robust Unit Commitment (UC) policies is presented; such methodology considers a novel scenario-based uncertainty model for wind power applications. The proposed method is composed by three main phases. The first two phases generate a sound wind-power forecast using a bootstrap predictive inference approach. The third phase corresponds to modeling and solving a one-day ahead Robust UC considering the output of the first phase.The performance of proposed approach is evaluated using as case study a new wind farm to be incorporated into the Northern Interconnected System (NIS) of Chile. A projection of wind-based power installation, as well as different characteristic of the uncertain data, are considered in this study.

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