Proceedings of the Annual Conference of JSAI
Online ISSN : 2758-7347
37th (2023)
Session ID : 2K6-GS-2-01
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A study of electricity demand forecasting with wide-area meteorological data using dimensionality reduction
*Masaya NAKAYAMAShoichi URANO
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Abstract

It is known that electricity demand is closely related to people's behavior and is particularly affected by weather data. For this reason, conventional studies of electricity demand forecasting by electric power companies using meteorological data often use only information on meteorological observation points corresponding to the demand points to be forecasted. Therefore, this paper aims to improve the accuracy of electricity demand forecasts for the following day by using meteorological data not only for demand points but also for the entire country, taking into account that in Japan the weather tends to change from west to east, driven by the prevailing westerly winds, while forecasting electricity demand for the region.

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© 2023 The Japanese Society for Artificial Intelligence
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