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Two-dimensional data expansion and LSTNet for residential PV generation forecasting
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Yuanyuan Wang1, Youpeng Yin1, Hongzhen Ji1, Lizhi Zhang2, Chengjun Cao1, Yuxuan Ye1
Renewable Energy Resources | 2025, 43(1) : 45 - 53
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Renewable Energy Resources | 2025, 43(1): 45-53
Two-dimensional data expansion and LSTNet for residential PV generation forecasting
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Yuanyuan Wang1, Youpeng Yin1, Hongzhen Ji1, Lizhi Zhang2, Chengjun Cao1, Yuxuan Ye1
Affiliations
  • 1 State Key Laboratory of Disaster Prevention & Reduction for Power Grid Changsha University of Science & Technology Changsha 410114 China
  • 2 State Grid Hunan Extra High Voltage Substation Company Changsha 410004 China
Published: 2025-01-20
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China's "Whole County PV" programme has been dramatically expanding the use of solar power in rural areas, by building on government, comnmercial, industrial and residential rooftops. However, a large number of dispersed residential PV will have an impact on the power system, and accurately predicting the shortterm power generation of residential PV is a prerequisite for addressing the impact. However, in addition to its original volatility, residential rooftop PV also has the characteristics of small capacity, decentralized and offline operation, together with the lack of accurate meteorological data, making PV power prediction exceptionally complex. Therefore, under the limited data, this paper longitudinally detects similar samples from the previous power data of the residential PV to be predicted,and horizontally collects similar samples from the power data of neighboring residential PV, ultimately jointly realizing two dimensional data expansion, which overcomes the dependence of PV power generation prediction on some key input features to a certain extent. And then a residential PV generation prediction method is proposed based on LSTNet neural network, which has the functions of shortterm local features capture, longterm time series information reinforcement, and cyclical linear component extraction.

whole county PV  /  PV generation  /  short-term power prediction  /  two-dimensional data expansion  /  neural network
Yuanyuan Wang, Youpeng Yin, Hongzhen Ji, Lizhi Zhang, Chengjun Cao, Yuxuan Ye. Two-dimensional data expansion and LSTNet for residential PV generation forecasting[J]. Renewable Energy Resources, 2025 , 43 (1) : 45 -53 .
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Article Info
  • Receive Date：2023-10-25
  • Online Date：2025-07-18
  • Published：2025-01-20
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  • Received：2023-10-25
Funding
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    1 State Key Laboratory of Disaster Prevention & Reduction for Power Grid Changsha University of Science & Technology Changsha 410114 China
    2 State Grid Hunan Extra High Voltage Substation Company Changsha 410004 China
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小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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