ScholarWorks@성균관대학교

초록

Power sales companies formulate their management strategies and investment plans according to the sales volume; therefore, accurate forecasting is essential. For instance, failure in facility investment planning may lead to a decline in power system stability due to insufficient power supply or revenue loss from overinvestment in power infrastructure. This study analyzes the correlation between power sales volume and various influencing factors, such as economic indicators and weather data, to improve the prediction accuracy of short- and medium-term power sales volumes by reflecting regional characteristics. The developed power sales forecasting technology applies automatic data acquisition and preprocessing techniques and provides user-friendly forecast results by classifying data on the basis of power sales regions, contract types, and power usage through an analysis of the correlation between key influencing factors and power sales volume to implement a highly accurate forecasting system.

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