A Novel Framework Short-Term Load Forecasting for Micro-grid Energy Management System

Short-term Electricity Load forecasting (STLF) is one of the most important technologies for Energy Management System (EMS) in various aspects, such as peak-load shaving application, demand response, or net-zero energy technology. This paper presented a novel Short-term Electricity Load forecasting...

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Bibliographic Details
Published in2018 IEEE International Conference on Smart Energy Grid Engineering (SEGE) pp. 279 - 283
Main Authors Kuo, Wen-Chi, Hsieh, Ting-Yen, Chen, Hsing-Chih, Chi, Chang-Liang, Huang, Yung-Fu
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2018
Subjects
Energy management
energy management system
Forecasting
Load forecasting
Load modeling
microgrid
Microgrids
Predictive models
short-term load forecasting
Temperature
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Summary:Short-term Electricity Load forecasting (STLF) is one of the most important technologies for Energy Management System (EMS) in various aspects, such as peak-load shaving application, demand response, or net-zero energy technology. This paper presented a novel Short-term Electricity Load forecasting (STLF) framework with four strategies-a Variable selection of input parameters processing method, Modified Time Series - Exponential Smoothing model, Peak-load, and Temperature correction factors. The testing results showed that the proposed framework of forecasting indeed improves the accuracy of day-ahead STLF, especially on the cases with limited historical information and data loss conditions.
ISSN:2575-2693
DOI:10.1109/SEGE.2018.8499492