Photovoltaic Power Forecast and Strategic Maintenance Using Bi-directional LSTM with Multi-Regional Weather Data 


Vol. 14,  No. 10, pp. 850-854, Oct.  2025
https://doi.org/10.3745/TKIPS.2025.14.10.850


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  Abstract

We propose a model to forecast photovoltaic(PV) power generation using PV plant status data and regional weather data from the Korea Meteorological Administration. However, the Korea Meteorological Administration data has limitations because it uses weather information far from the PV power plant area. To overcome this limitation, this study explored a method for utilizing regional meteorological data from multiple regions. Through the proposed method, we confirmed that the proposed prediction model exhibits an nMAE error rate of approximately 3-4%.

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[IEEE Style]

H. K. Ahn, S. Yang, N. Park, "Photovoltaic Power Forecast and Strategic Maintenance Using Bi-directional LSTM with Multi-Regional Weather Data," The Transactions of the Korea Information Processing Society, vol. 14, no. 10, pp. 850-854, 2025. DOI: https://doi.org/10.3745/TKIPS.2025.14.10.850.

[ACM Style]

Hyung Keun Ahn, Sumi Yang, and Neungsoo Park. 2025. Photovoltaic Power Forecast and Strategic Maintenance Using Bi-directional LSTM with Multi-Regional Weather Data. The Transactions of the Korea Information Processing Society, 14, 10, (2025), 850-854. DOI: https://doi.org/10.3745/TKIPS.2025.14.10.850.

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