A Study on the Local Power Demand Prediction through the ARIMA Model for VCG Auction Based Peer-to-Peer Power Transaction 


Vol. 47,  No. 6, pp. 845-854, Jun.  2022
10.7840/kics.2022.47.6.845


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  Abstract

With the improvement of renewable energy productivity and development of ESS (Energy Storage System) technology, the concept of an energy prosumer has emerged. Therefore, in addition to the existing centralized power supply method, the Peer-to-Peer transaction scheme is required. In this study, We investigated the power transaction scheme through the prediction based Vickrey-Clarke-Groves (VCG) Auction in peer-to-peer power transaction system and the ARIMA model-based time series demand data analysis technique. Experimental results using KPX public data verified that the actual data and prediction data have a mean absolute percentage error of 2.213%, and that the ARIMA model-based regional power demand prediction technique is suitable for power demand time series data.

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  Cite this article

[IEEE Style]

J. Lee, C. Lee, S. Cho, "A Study on the Local Power Demand Prediction through the ARIMA Model for VCG Auction Based Peer-to-Peer Power Transaction," The Journal of Korean Institute of Communications and Information Sciences, vol. 47, no. 6, pp. 845-854, 2022. DOI: 10.7840/kics.2022.47.6.845.

[ACM Style]

Jeonghwa Lee, Chunghyun Lee, and Sungrae Cho. 2022. A Study on the Local Power Demand Prediction through the ARIMA Model for VCG Auction Based Peer-to-Peer Power Transaction. The Journal of Korean Institute of Communications and Information Sciences, 47, 6, (2022), 845-854. DOI: 10.7840/kics.2022.47.6.845.

[KICS Style]

Jeonghwa Lee, Chunghyun Lee, Sungrae Cho, "A Study on the Local Power Demand Prediction through the ARIMA Model for VCG Auction Based Peer-to-Peer Power Transaction," The Journal of Korean Institute of Communications and Information Sciences, vol. 47, no. 6, pp. 845-854, 6. 2022. (https://doi.org/10.7840/kics.2022.47.6.845)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880