Kai Chen, Han Zhou, Yan Jiang, et al. ENSO impacts on low wind power events: A long-term data-driven analysis using TabNet[J]. Energy Conversion and Economics, 2026, 7(4).
DOI:
Kai Chen, Han Zhou, Yan Jiang, et al. ENSO impacts on low wind power events: A long-term data-driven analysis using TabNet[J]. Energy Conversion and Economics, 2026, 7(4).DOI: 10.1049/enc2.70047.
ENSO impacts on low wind power events: A long-term data-driven analysis using TabNet
摘要
Abstract
As power systems transition towards decarbonised energy mixes with increasing wind penetration
prolonged low-wind-power (LWP) events have emerged as a critical source of adequacy risk. However
a comprehensive analysis of LWP events remains constrained by the scarcity of long-term historical wind-power generation records in regions with high renewable penetration. To address this limitation
this study proposes a TabNet-based wind power modelling framework for 90 wind farms in Guangxi
China
leveraging historical meteorological records and measured operational data. ERA5 reanalysis data are used to reconstruct hourly wind-power generation over a 43-year period (1980–2022). An adaptive mean-below-threshold method featuring a tolerance mechanism is proposed to identify LWP events over the 43-year period. Based on this
the intra-annual and inter-annual characteristics of LWP events are analysed
and their relationship with the El Niño–Southern Oscillation and the Eastern Pacific (EP) index is investigated. The results indicate that both the annual duration and frequency of LWP events exhibit upward trends over the study period
with the upward trends becoming more pronounced after 2000. Furthermore
the EP index demonstrates a lagged association with LWP duration and frequency in Guangxi
with decaying La Niña years exhibiting the clearest positive anomalies in LWP duration and frequency among the investigated ENSO categories. These findings offer climate-informed insights for wind power adequacy assessment and renewable integration planning.