24-Hour Load Forecasting For Anomalous Weather Days Using Hourly Temperature시간별 기온을 이용한 예외 기상일의 24시간 평일 전력수요패턴 예측
- Other Titles
- 시간별 기온을 이용한 예외 기상일의 24시간 평일 전력수요패턴 예측
- Authors
- 강동호; 박정도; 송경빈
- Issue Date
- Jul-2016
- Publisher
- Korean Institute of Electrical Engineers
- Keywords
- Anomalous weather days; Hourly temperature; Short-term load forecasting; Similar day
- Citation
- Transactions of the Korean Institute of Electrical Engineers, v.65, no.7, pp.1144 - 1150
- Journal Title
- Transactions of the Korean Institute of Electrical Engineers
- Volume
- 65
- Number
- 7
- Start Page
- 1144
- End Page
- 1150
- URI
- http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/8278
- DOI
- 10.5370/KIEE.2016.65.7.1144
- ISSN
- 1975-8359
- Abstract
- Short-term load forecasting is essential to the electricity pricing and stable power system operations. The conventional weekday 24hour load forecasting algorithms consider the temperature model to forecast maximum load and minimum load. But 24hour load pattern forecasting models do not consider temperature effects, because hourly temperature forecasts were not present until the latest date. Recently, 3 hour temperature forecast is announced, therefore hourly temperature forecasts can be produced by mathematical techniques such as various interpolation methods. In this paper, a new 24hour load pattern forecasting method is proposed by using similar day search considering the hourly temperature. The proposed method searches similar day input data based on the anomalous weather features such as continuous temperature drop or rise, which can enhance 24hour load pattern forecasting performance, because it uses the past days having similar hourly temperature features as input data. In order to verify the effectiveness of the proposed method, it was applied to the case study. The case study results show high accuracy of 24-hour load pattern forecasting.
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