A Learning-Based Methodology to Optimally Fit Short-Term Wind-Energy Bands

The increasing rate of penetration of non-conventional renewable energies is affecting the traditional assumption of controllability over energy sources. Power dispatch scheduling methods need to integrate the intrinsic randomness of some new sources, among which, wind energy is particularly difficu...

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Bibliographic Details
Main Authors: Claudio Risso, Gustavo Guerberoff
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/11/11/5137
Description
Summary:The increasing rate of penetration of non-conventional renewable energies is affecting the traditional assumption of controllability over energy sources. Power dispatch scheduling methods need to integrate the intrinsic randomness of some new sources, among which, wind energy is particularly difficult to treat. This work aims at the optimal construction of energy bands around wind energy forecasts. Complementarily, a remarkable fact of the proposed technique is that it can be extended to integrate multiple forecasts into a single one, whose band width is narrower at the same level of confidence. The work is based upon a real-world application case, developed for the Uruguayan Electricity Market, a world leader in the penetration of renewable energies.
ISSN:2076-3417