특수일 최대 전력 수요 예측을 위한 결정계수를 사용한 데이터 마이닝 : Data Mining Technique Using the Coefficient of Determination in Holiday Load Forecasting
Data Mining Technique Using the Coefficient of Determination in Holiday Load Forecasting
- 주제(키워드) Load forecasting , Polynomial regression , Coefficient of determination
- 발행기관 대한전기학회
- 발행년도 2009
- 총서유형 Journal
- UCI G704-000119.2009.58.1.028
- KCI ID ART001307201
- 본문언어 한국어
초록/요약
Short-term load forecasting (STLF) is an important task in power system planning and operation. Its accuracy affects the reliability and economic operation of power systems. STLF is to be classified into load forecasting for weekdays, weekends, and holidays. Due to the limited historical data available, it is more difficult to accurately forecast load for holidays than to forecast load for weekdays and weekends. It has been recognized that the forecasting errors for holidays are large compared with those for weekdays in Korea. This paper presents a polynomial regression with data mining technique to forecast load for holidays. In statistics, a polynomial is widely used in situations where the response is curvilinear, because even complex nonlinear relationships can be adequately modeled by polynomials over a reasonably small range of the dependent variables. In the paper, the coefficient of determination is proposed as a selection criterion for screening weekday data used in holiday load forecasting. A numerical example is presented to validate the effectiveness of the proposed holiday load forecasting method.
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