Short-term load forecast using trend information and process reconstruction
نویسندگان
چکیده
منابع مشابه
Short term load forecast by using Locally Linear Embedding manifold learning and a hybrid RBF-Fuzzy network
The aim of the short term load forecasting is to forecast the electric power load for unit commitment, evaluating the reliability of the system, economic dispatch, and so on. Short term load forecasting obviously plays an important role in traditional non-cooperative power systems. Moreover, in a restructured power system a generator company (GENCO) should predict the system demand and its corr...
متن کاملShort-Term Electric Load Forecasting Using Multiple Gaussian Process Models
This paper presents a Gaussian process model-based short-term electric load forecasting. The Gaussian process model is a nonparametric model and the output of the model has Gaussian distribution with mean and variance. The multiple Gaussian process models as every hour ahead predictors are used to forecast future electric load demands up to 24 hours ahead in accordance with the direct forecasti...
متن کاملShort Term Load Forecasting Using Gaussian Process Models
The electrical deregulated market increases the need for short-term load forecast algorithms in order to assist electrical utilities in activities such as planning, operating and controlling electric energy systems. Methodologies based on regression methods have been widely used with satisfactory results. However, this type of approach has some shortcomings. This paper proposes a short-term loa...
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 forecast using fuzzy logic and wavelet transform integrated generalized neural network
Application of Artificial Neural Networks (ANNs) for electrical load forecasting has been proposed in the literature. ANNs have some inherent drawbacks and limitations, such as difficulty in deciding the structure of ANN, selection of type of neuron, large training time, sticking to local minima, etc. To overcome the drawbacks of ANN, a Generalized Neural Network (GNN) has been proposed in the ...
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: International Journal of Energy Research
سال: 2006
ISSN: 0363-907X,1099-114X
DOI: 10.1002/er.1187