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...

with the development of restructured power systems and increase of prices in some hours of day and increase fuel price, demand response programs were noticed more by customers. demand response consists of a series of activities that governments or utilities design to change the amount or time of electric energy consumption, to achieve better social welfare or some times for maximizing the benef...

Short-term load forecasting (STLF) plays an important role in the operational planning security functions of an energy management system. The short term load forecasting is aimed at predicting electric loads for a period of minutes, hours, days or week for the purpose of providing fundamental load profiles to the system. The work presented in this paper makes use of PSO based local linear wavel...

in this paper, load and buckling mode of a smart column are presented. the theoretical model is a three-layer piezoelectric composite beam that behaves as an axial actuating mechanism. this actuator consists of an elastic core sandwiched between two piezoelectric active outer layers. the piezoelectric layers are polarized transversely, i.e., the polarization vector is parallel to the applied el...

In most power system studies, a major part of the problem is the finding of the voltages needed to meet a given schedule of loads and generation. Until now, iteration methods have been used to calculate the respective load flows. This paper presents a study to compare Newton method and sparse matrices with artificial neural networks regarding a load flow problem in electric distribution lines. ...

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...