Triple seasonal methods for short-term electricity demand forecasting
نویسندگان
چکیده
منابع مشابه
Triple seasonal methods for short-term electricity demand forecasting
Online short-term load forecasting is needed for the real-time scheduling of electricity generation. Univariate methods have been developed that model the intraweek and intraday seasonal cycles in intraday load data. Three such methods, shown to be competitive in recent empirical studies, are double seasonal ARMA, an adaptation of Holt-Winters exponential smoothing for double seasonality, and a...
متن کاملShort-term electricity demand forecasting using double seasonal exponential smoothing
This paper considers univariate online electricity demand forecasting for lead times from a half-hour-ahead to a day-ahead. A time series of demand recorded at half-hourly intervals contains more than one seasonal pattern. A within-day seasonal cycle is apparent from the similarity of the demand profile from one day to the next, and a within-week seasonal cycle is evident when one compares the ...
متن کاملDemand Forecasting for Electricity
Introduction Forecasting demand is both a science and an art. Econometric methods of forecasting, in the context of energy demand forecasting, can be described as ‘the science and art of specification, estimation, testing and evaluation of models of economic processes’ that drive the demand for fuels. The need and relevance of forecasting demand for an electric utility has become a much-discuss...
متن کاملEfficient Short-Term Electricity Load Forecasting Using Recurrent Neural Networks
Short term load forecasting (STLF) plays an important role in the economic and reliable operation ofpower systems. Electric load demand has a complex profile with many multivariable and nonlineardependencies. In this study, recurrent neural network (RNN) architecture is presented for STLF. Theproposed model is capable of forecasting next 24-hour load profile. The main feature in this networkis ...
متن کاملRandom vector functional link network for short-term electricity load demand forecasting
Short-term electricity load forecasting plays an important role in the energy market as accurate forecasting is beneficial for power dispatching, unit commitment, fuel allocation and so on. This paper reviews a few single hidden layer network configurations with random weights (RWSLFN). The RWSLFN was extended to eight variants based on the presence or absence of input layer bias, hidden layer ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: European Journal of Operational Research
سال: 2010
ISSN: 0377-2217
DOI: 10.1016/j.ejor.2009.10.003