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Ultra-short-term wind speed prediction can assist the operation and scheduling of wind turbines in the short term and further reduce the adverse effects of wind power integration. However, as wind is irregular, nonlinear, and nonstationary, to accurately predict wind speed is a difficult task. To this end, researchers have made many attempts; however, they often use only point forecasting or interval forecasting, resulting in imperfect prediction results. Therefore, in this paper, we developed a prediction system integrating an advanced data preprocessing strategy, a novel optimization model, and multiple prediction algorithms. This combined forecasting system can overcome the inherent disadvantages of the traditional forecasting methods and further improve the prediction performance. To test the effectiveness of the forecasting system, the 10-min and one-hour wind speed sequences from the Sotavento wind farm in Spain were applied for conducting comparison experiments. The results of both the interval forecasting and point forecasting indicated that, in terms of the forecasting capability and stability, the proposed system was better than the compared models. Therefore, because of the minimum prediction error and excellent generalization ability, we consider this forecasting system to be an effective tool to assist smart grid programming.

Based on the eminent characteristics of the ice-storage systems, which can shift cooling electrical demand from peak time to off peak time, this paper describes the ice storage air-conditioning system that is now used much frequently. The authors develop the operating cost model by simplification and introduce a neural network model and lay to solve the optimal cost problem of operation by using this neural network model. In calculation, any trajectory of the neural network converges to its solution in finite time, which is consistent with result by simplex method. Comparing with different methods, the neural network is more effective, which can be alternative to simplex method in calculating the optimal cost model for ice storage air-conditioning systems.

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