Major dependency on fossil energy resources and emission of greenhouse gases are common problems that have a very harmful impact on human communities. Thus, the use of renewable energy resources, such as wind power, has become a strong alternative to solve this problem. Nevertheless, because of the intermittence and unpredictability of the wind energy, an accurate wind speed forecasting is a very challenging research subject. This paper addresses a short-term wind speed forecasting based on Seasonal Autoregressive Integrated Moving Average (SARIMA) model. The forecasting performances of the model were conducted using the same dataset under different evaluation metrics in terms of Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) performance evaluation metrics. The obtained results denote that the used model achieves excellent forecasting accuracy.
Abstract-In this paper, we present a single phase 5 levels HBridge multilevel inverter (CHMLI) with battery balancing technique. Each single full bridge is directly connected to a battery inside the power bank. The different combinations and batteries wiring sets offer the possibility to control the batteries discharge. The cascaded H-Bridge multilevel inverter is first described and the discharge is studied in normal conditions under different stress scenarios. State of charge (SOC) balancing technique is then achieved using an equalization algorithm controlling the different switching combination inside the power bank. Results of the simulation model with and without the SOC balancing is presented using Matlab.
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