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With the rapid increase of the capacity in photovoltaic (PV) generated systems, how to deal with the problem caused by the random output in the system becomes more significant. One possible solution could be the use of energy storage. The forecasting output can be obtained by the support vector regression model (SVR) introduced in this article, then the capacity of energy storage can be optimized...
Wind power forecasting has great significance to the connection of wind farms to the electric power system. This paper analyzes individual forecast models, such as the time series forecasting, Elman network forecasting that based on the chaos theory, grey neural network forecasting, and generalized regression neural network forecasting, etc., then puts forward an entropy weight combination prediction...
As wind power penetrations increase dramatically, wind power forecasting is increasingly becoming one of the fundamental strategies in hybrid power systems. In order to obtain higher accuracy, a new method-genetic algorithm neural network based on rough set theory is proposed in the paper. Considering many factors that influence wind speed forecasting, reduction algorithm of rough set theory is introduced...
Influenced by the economic cycle, power demand in china shows some cyclical fluctuations, which is unhealthy for the development of national economy and production efficiency of electric power industry. Correctly forecasting the fluctuation rule of power demand and the turning points in China is helpful to make the corresponding strategy complied with the cycle. With the full consideration of power...
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