This paper presents the applicability of artificial neural networks for 24 hour ahead solar power generation forecasting of a 20 kW photovoltaic system, the developed forecasting is suitable for a reliable Microgrid energy management. In total four neural networks were proposed, namely: multi-layred perceptron, radial basis function, recurrent and a neural network ensemble consisting in ensembl...

In this research is presented a method for technological capabilities assessment in a company in transformer industry. Used and discussed criteria in this technique are merely developed to assess technological capabilities in transformer industry. Based on literature, technological capabilities in transformer industry are divided into three main categories: production capability, development an...

The paper discusses the strategic planning of transition to sixth technological structure economy; object article is order in national aim increase effectiveness development achieve this goal following tasks: a concept "technological system"; describes methodological principles scientific theory structures; developed data grid synthesized tables properties table formed animation technologies ne...

natural hazards in the form of floods, quakes, cyclones, and the like have existed since the earth has come to being. in recent decades, in spite of scientific and technological developments in forecasting incidents, building construction and crisis management have imposed heavy expenses on human societies. the importance of many natural hazards is so great that to predict the very occurrence a...

Long term power load has a big impact on the development of industry of power. The forecasting models of linear systems even a single forecasting model of the nonlinear systems can not forecast the long term power load greatly. In the study, the combined forecasting model of nonlinear systems including chaos and fractal was established to improve the accuracy of the forecast. First, the charact...

Combination forecasting takes all characters of each single forecasting method into consideration, and combines them to form a composite, which increases forecasting accuracy. The existing researches on combination forecasting select single model randomly, neglecting the internal characters of the forecasting object. After discussing the function of cointegration test and encompassing test in t...

Fuzzy time series model has been developed to either improve forecasting accuracy or reduce computation time, whereas a residul analysis in order to improve its forecasting performance is still lack of consideration. In this paper, we propose a novel Fourier method to revise the analysis of residual terms, and then we illustrate it to forecast the Japanese tourists visiting in Taiwan per year. ...

Building a time series forecasting model by independent component analysis mechanism presents in the paper. Different from using the time series directly with the traditional ARIMA forecasting model, the underlying factors extracted from time series is the forecasting base in our model. Within component ambiguity, correlation approximation and mean difference problems, independent component ana...

As an important part of power system planning and the basis of economic operation of power systems, the main work of power load forecasting is to predict the time distribution and spatial distribution of future power loads. The accuracy of load forecasting will directly influence the reliability of the power system. In this paper, a novel short-term Empirical Mode Decomposition-Grey Relational ...