Modeling and Forecasting Daily Electricity Load Curves: A Hybrid Approach
نویسندگان
چکیده
منابع مشابه
Modeling and Forecasting Daily Electricity Load Curves: A Hybrid Approach
Modeling and Forecasting Daily Electricity Load Curves: A Hybrid Approach Haeran Cho a , Yannig Goude b , Xavier Brossat b & Qiwei Yao c d a Department of Statistics, London School of Economics, UK b Electricité de France, R&D, Clamart, France c Department of Statistics, London School of Economics, Houghton Street, London, WC2A 2AE, U.K. d Guanghua School of Management, Peking University, China...
متن کاملForecasting Daily Electricity Load Curves
Short term electricity load forecasting is a well-known problem, and many neural computing approaches for solving it have been proposed in recent years. In this paper, we argue in favour of its decomposition into two subproblems, and propose a solution for one of them: the prediction, en bloc, of the daily load profile, or configuration, for the different hours of a particular future date. From...
متن کاملModeling and Forecasting Intraday Electricity Load
This paper aims models electricity load curves for short-term forecasting purposes. A broad class of multivariate dynamic regression model is proposed to model hourly electricity load. Alternative forecasting models, special cases of our general model, include separate time series regressions for each hour and week day. All the models developed include components that represent trends, seasons ...
متن کاملA Practical Approach for Electricity Load Forecasting
This paper is a continuation of our daily energy peak load forecasting approach using our modified network which is part of the recurrent networks family and is called feed forward and feed back multi context artificial neural network (FFFB-MCANN). The inputs to the network were exogenous variables such as the previous and current change in the weather components, the previous and current statu...
متن کاملElectricity Load Forecasting: A Weekday-Based Approach
We present a new approach for building weekday-based prediction models for electricity load forecasting. The key idea is to conduct a local feature selection using autocorrelation analysis for each day of the week and build a separate prediction model using linear regression and backpropagation neural networks. We used two years of 5-minute electricity load data for the state of New South Wales...
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: Journal of the American Statistical Association
سال: 2013
ISSN: 0162-1459,1537-274X
DOI: 10.1080/01621459.2012.722900