The problem of short-term electric load forecasting (STLF) is considered. A modified architecture of Elman-type recurrent neural network is proposed. It utilizes a special fuzzification layer to deal with quantitative as well as ordinal and nominal data. The second hidden layer of the network consists of standard Rosenblatt-type neurons with sigmoidal activation functions. The context layer is ...

In this paper, a new model, core vector regression (CVR) optimized by memetic algorithm (MA), is presented to predict electric daily load. Support vector regression (SVR) has obtained wide focus in recent years to solve nonlinear regression problems in many fields. However, it is limited on large scale dataset problem because of its high time and space complexity. Hence, CVR is proposed to impr...

The power world is sauntering towards ecofriendly distributed generation (DG), their integration into the distribution network postures challenges to existing load flow techniques. This paper is concerned with developing models of various types of wind turbine generating systems (WTGSs) used as distributed generation (DG) sources and demonstrating their application for steady state analysis. As...

Hydrostatic power transmission between the rotor of a wind turbine and generator, which can be placed on ground, is way to reduce cost installing turbine, reducing mass at height. The article shows ability hydrostatic cope with disturbance due change in air flow that drives rotor. When increasing flow, would normally lead an increase drive speed electric by adjusting geometric volume hydraulic ...