A Forecasting Method of Peak-Cut of Power Demand Using LSTM at A Clinic

Energy prices are rising due to the changing global situation. Rising energy prices have also led to higher electricity prices in Japan. Electricity prices is determined by the contracted power for the past year. Hospitals and clinics would like to reduce electricity costs with decreasing contracted...

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Bibliographic Details
Published in2023 12th International Conference on Renewable Energy Research and Applications (ICRERA) pp. 1 - 6
Main Authors Inagata, Tomoya, Mizuno, Yuji, Matsunaga, Keita, Kurokawa, Fujio, Tanaka, Masaharu, Matsui, Nobumasa
Format Conference Proceeding
LanguageEnglish
Published IEEE 29.08.2023
Subjects
clinic
Correlation
Costs
Hospitals
load forecast
Load forecasting
LSTM
Power demand
Predictive models
Renewable energy sources
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Summary:Energy prices are rising due to the changing global situation. Rising energy prices have also led to higher electricity prices in Japan. Electricity prices is determined by the contracted power for the past year. Hospitals and clinics would like to reduce electricity costs with decreasing contracted power. They recently have a combination of diesel generators (DGs) and PV for their power systems. DGs and PV can be used for peak-cut. Therefore, DGs and PV has an important role for peak-cut operations. This paper proposes a forecasting method of peak-cut of power demand using LSTM at a clinic. Four cases based on the correlation of the demand data are defined as input data for LSTM in this paper. The results show that Case 3 and Case 4 is a better model on the point of forecasting peak demand. Power demand data for last three months produced better results than using five years of power demand data.
ISSN:2572-6013
DOI:10.1109/ICRERA59003.2023.10269447