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The increased integration of wind power into the electric grid, as it occurs today in Portugal, poses new challenges due to its intermittency and volatility. Wind power forecasting plays a key role in tackling these challenges. A novel hybrid approach, combining wavelet transform, particle swarm optimization, and an adaptive-network-based fuzzy inference system, is proposed in this paper for short-term...
Short-term prediction of wind speed is important to the power system operation. Generation schedules in a wind farm could be efficiently assigned by means of precise prediction of wind speed to alleviate the impact of instable wind power on power grids. Back-propagation neural network (BPNN) is a main approach for short-term wind speed prediction. The method, using the improved particle swarm optimization...
The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. A novel hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, is proposed in this paper for short-term wind power prediction...
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