SAS | The Power to Know
cq5dam.thumbnail.319.319
White Paper

When One Size No Longer Fits All - Electric Load Forecasting with a Geographic Hierarchy

About this paper

Utility forecasters cannot assume that one methodology will provide the best forecast from one year to the next. To improve forecast performance, reduce uncertainties and generate value in the new data-intensive environment, they must be able to decide which models, or combinations of models, are best. And they must be able to determine more indicators of the factors that affect load. This paper uses a case study to illustrate how utility forecasters can take advantage of hourly or sub-hourly data from millions of smart meters by using new types of forecasting methodologies. It investigates how a number of approaches using geographic hierarchy and weather station data can improve the predictive analytics used to determine future electric usage. It also demonstrates why utilities need to use geographic hierarchies, and why their solutions should allow them to retrain models multiple times each year.

About SAS 

SAS는 분석 부문의 선두 기업입니다. SAS는 8만여 곳 이상의 기업에 혁신적인 분석, 비즈니스 인텔리전스(BI), 데이터 관리 소프트웨어와 서비스를 제공함으로써, 고객사가 신속하고 정확한 의사결정을 내릴 수 있도록 지원합니다. SAS는 1976년부터 전 세계 고객사에게 ‘THE POWER TO KNOW’에 입각한 서비스를 제공하고 있습니다. THE POWER TO KNOW®.

SAS Profile이 있으십니까? 이 양식을 자동으로 완성하려면 로그인

*
*
*
*
 
*
*
*
 예
 아니오
*
 예
 아니오
 
 

Back to Top