In this paper, a model predictive control (MPC)-based coordinated scheduling framework for variable wind generation and battery energy storage systems (BESSs) is presented. On the basis of the short-term forecast of available wind generation and price information, a joint look-ahead optimization is performed by the wind farm and storage system to determine their net power injection to the elect...

We study the problem of short term wind speed prediction, which is a critical factor for effective wind power generation. This is a challenging task due to the complex and stochastic behavior of the wind environment. Observing various periods in the wind speed time series present different patterns, we suggest a nonlinear adaptive framework to model various hidden dynamic processes. The model i...

In recent years, wind energy has a remarkable growth in the world, but one of the important problems of power generated from wind is its uncertainty and corresponding power. For solving this problem, some approaches have been presented. Recently, the Artificial Neural Networks (ANN) as a heuristic method has more applications for this propose. In this paper, short-term (1 hour) and mid-term (24...

as renewable energy increasingly penetrates into power grid systems, new challenges arise for system operators to keep the systems reliable under uncertain circumstances, while ensuring high utilization of renewable energy. this paper presents unit commitment (uc) which takes into account the volatility of wind power generation. the uc problem is solved with the forecasted intermittent wind pow...

 Abstract—Short-term probabilistic wind power forecasting can provide critical quantified uncertainty information of wind generation for power system operation and control. As the complicated characteristics of wind power prediction error, it would be difficult to develop a universal forecasting model dominating over other alternative models. Therefore, a novel multi-model combination (MMC) ap...

in this research paper, a 10 minute period measured wind speed data at 10 m, 30 m, and 40 m heights are presented for one of the major provinces of iran. four stations in khuzestan- abadan, hosseyneh, mahshahr, and shushtar- are analyzed to determine the potential of wind power generation in this province. from the primary evaluation and by determining mean wind speed and also the weibull funct...

The accuracy of short-term wind speed prediction is very important for wind power generation. In this paper, a hybrid method combining ensemble empirical mode decomposition (EEMD), adaptive neural network based fuzzy inference system (ANFIS) and seasonal auto-regression integrated moving average (SARIMA) is presented for short-term wind speed forecasting. The original wind speed series is decom...