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Forecasting hourly electricity load of Korea using multi-seasonal exponential smoothing
![m electricity demands in Korea by introducing an exponential smoothing method
with multi-seasonality as the latest demand forecast technique - The short-term in this study implies a week of hourly data. - The seasonality implies repeated patterns with a regular cycle, or periodicity more precisely. The Significance of the Study • Introducing and reviewing the latest multi-seasonal exponential smoothing method, and to apply the method domestic load forecasting for the first time. • Proposing a bottom-up method as one of the solutions to improve forecasting accuracy with multi-seasonal exponential smoothing. - The bottom-up method estimates the electricity demands by dividing the raw(hourly) data into two
Korea Energy Economics Institute
1
daily and one hourly data, and then combines them later for forecasting load in original unit.
[Fig. 2-1] Methodologies for the short-term electricity demand forecast
Statistical methodologies Exponential Strength：Interpretation of the variables of Smoothing the models and the analysis results is intuitive. Method Regression Analysis Weakness：The non-linear relationship Time Series between variables cannot be easily Analysis modeled Artificial Intelligence Methodologies Strength：The non-linear relationship Fuzzy theory between variables is easily modeled. Expert systems Artificial Weakness：Special relationships between Neural variables are hardly integrable Networks
Ⅱ. Forecast of Electricity Demands Using Exponential Smoothing
Methodolog](/image.do?type=idas&timeFile=/asset/2016/02/23/DOC/PREVIEW/04201602230143486034975.jpg "m electricity demands in Korea by introducing an exponential smoothing method
with multi-seasonality as the latest demand forecast technique - The short-term in this study implies a week of hourly data. - The seasonality implies repeated patterns with a regular cycle, or periodicity more precisely. The Significance of the Study • Introducing and reviewing the latest multi-seasonal exponential smoothing method, and to apply the method domestic load forecasting for the first time. • Proposing a bottom-up method as one of the solutions to improve forecasting accuracy with multi-seasonal exponential smoothing. - The bottom-up method estimates the electricity demands by dividing the raw(hourly) data into two
Korea Energy Economics Institute
1
daily and one hourly data, and then combines them later for forecasting load in original unit.
[Fig. 2-1] Methodologies for the short-term electricity demand forecast
Statistical methodologies Exponential Strength：Interpretation of the variables of Smoothing the models and the analysis results is intuitive. Method Regression Analysis Weakness：The non-linear relationship Time Series between variables cannot be easily Analysis modeled Artificial Intelligence Methodologies Strength：The non-linear relationship Fuzzy theory between variables is easily modeled. Expert systems Artificial Weakness：Special relationships between Neural variables are hardly integrable Networks
Ⅱ. Forecast of Electricity Demands Using Exponential Smoothing
Methodolog")
| Title |
Forecasting hourly electricity load of Korea using multi-seasonal exponential smoothing
Similar Titles
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|---|---|
| Material Type | Reports |
| Author(English) |
Kim, Cherl-Hyun |
| Publisher |
Ulsan : Korea Energy Economics Institute |
| Date | 2015-06 |
| Series Title; No | Policy Issue Paper / 13-06 |
| Pages | 12 |
| Subject Country | South Korea(Asia and Pacific) |
| Language | English |
| File Type | Documents |
| Original Format | |
| Subject | Industry and Technology < Energy |
| Holding | Korea Energy Economics Institute |
| License |  |
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