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Guangzeng You

As seen in: Nature, Frontiers, MDPI
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Articles

Photovoltaic power interval prediction with conditional error dependency using Bayesian optimized deep learning - Scientific Reports

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By Guangzeng You
| Nature Verified
Abstract Accurate photovoltaic (PV) power forecasting serves as a critical foundation for economic dispatch and reliable grid operation. To address the inherent uncertainty in PV power generation, this study proposes a short-term PV power interval prediction method based on Bayesian-optimized CNN-BiLSTM-attention (BO-CNN-BiLSTM-attention) that accounts for conditional dependencies in prediction errors.
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Zonal Planning for a Large-Scale Distribution Network Considering Reliability

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By Zhiwei Shi, Guangzeng You, Ning Sun, Linfu Miu
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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Virtual Inertia Parameter Design for Low-Voltage Distribution System Based on Feasible Region

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By Guangzeng You, Shuming Zhou, Qiang Yu, Xueshen Zhao
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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