2023
DOI: 10.1109/tpwrs.2022.3170992
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Conditional Style-Based Generative Adversarial Networks for Renewable Scenario Generation

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Cited by 50 publications
(14 citation statements)
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“…confidence(X ⇒ Y) = P(Y|X) = support(XUY) support(X) (13) For mining between PV-load-meteorological factors, only the correlation rules between meteorological factors and PV-load daily operating scenarios need to be obtained. The correlation rules between meteorological factors are then useless information for forming PV-load typical scenarios.…”
Section: Frequent Itemset Mining and Improvementmentioning
confidence: 99%
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“…confidence(X ⇒ Y) = P(Y|X) = support(XUY) support(X) (13) For mining between PV-load-meteorological factors, only the correlation rules between meteorological factors and PV-load daily operating scenarios need to be obtained. The correlation rules between meteorological factors are then useless information for forming PV-load typical scenarios.…”
Section: Frequent Itemset Mining and Improvementmentioning
confidence: 99%
“…Ref. [13] used conditional generation adversarial networks to generate accurate and reliable day-ahead scenarios using meteorological information as conditions and historical PV data as input. The day-ahead pattern and seasonal variability of PV output are fully considered.…”
Section: Introductionmentioning
confidence: 99%
“…In the pre-training phase of the diffusion model, a standard division ratio of 80%/20% [22], [33] is employed to construct 1) Correlation between single meteorological factor and renewable power: The correlation between a single common condtion and renewable power is examined in the datasets involved. Fig.…”
Section: A Dataset Descriptionmentioning
confidence: 99%
“…Owing to the neglect of EWEs, such methods are inappropriate for EWEspecific renewable scenario generation. Ref [22], [32] and [33] have made significant strides in weather-conditional renewable scenario generation, employing conditional GAN and stylebased GAN to integrate weather information as conditions. Nevertheless, only a limited number of typical weather are considered.…”
Section: Introductionmentioning
confidence: 99%
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