Short-Term Load Forecasting Using Radial Basis Function Neural Network
نویسندگان
چکیده
منابع مشابه
Short-Term Load Forecasting Using Radial Basis Function Neural Network (RBFN) in PJM Electricity Market
A precise short-term load forecasting technique is required for the economic and reliable operation of power system. Modern load forecasting techniques especially ANN methods are attractive as they have the ability to handle the non-linear relationships between load, weather temperature and the factors affecting it directly. In this paper, an investigation on the use of ANN for short term load ...
متن کاملIntegration of Fuzzy Inference Engine with Radial Basis Function Neural Network for Short Term Load Forecasting
This paper proposes a fuzzy inference based neural network for the forecasting of short term loads. The forecasting model is the integration of fuzzy inference engine and the neural network, known as Fuzzy Inference Neural Network (FINN). A FINN initially creates a rule base from existing historical load data. The parameters of the rule base are then tuned through a training process, so that th...
متن کاملLong-Term Peak Demand Forecasting by Using Radial Basis Function Neural Networks
Prediction of peak loads in Iran up to year 2011 is discussed using the Radial Basis Function Networks (RBFNs). In this study, total system load forecast reflecting the current and future trends is carried out for global grid of Iran. Predictions were done for target years 2007 to 2011 respectively. Unlike short-term load forecasting, long-term load forecasting is mainly affected by economy...
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 کاملShort Term Load Forecasting by Using ESN Neural Network Hamedan Province Case Study
Abstract Forecasting electrical energy demand and consumption is one of the important decision-making tools in distributing companies for making contracts scheduling and purchasing electrical energy. This paper studies load consumption modeling in Hamedan city province distribution network by applying ESN neural network. Weather forecasting data such as minimum day temperature, average day temp...
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 Computer and Communications
سال: 2015
ISSN: 2327-5219,2327-5227
DOI: 10.4236/jcc.2015.311007