Irradiance changes caused by clouds movement are the main factors, which lead to mutation of photovoltaic power. In order to increase the accuracy of the ultra-short-term photovoltaic power prediction, based on of clo...
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Irradiance changes caused by clouds movement are the main factors, which lead to mutation of photovoltaic power. In order to increase the accuracy of the ultra-short-term photovoltaic power prediction, based on of clouds images, the cloud identification for sky images is one of the primary aspects for improving photovoltaic power accuracy. A cloud identification model for sky images is established based on Otsu. Firstly, a series of sky images are collected by Total Sky Imager (TSI) with the regions of clouds and sky are distinguished. Secondly, the color features (based on RGB values) of pixels in sample images and the spectral and texture features of the whole image are extracted; Finally, we established a cloud identification model for sky images based on Otsu according to the clouds' and sky areas' division and the general characteristics featured by pixels and images. The simulated results show that the model in this paper can identify the clouds in a sky images effectively.
Minimum entropy control has been proven to be an effective method in control of non-Gaussian stochastic systems. In this case, the entropy is proposed as a generalization of the variance measure to characterize the ra...
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Minimum entropy control has been proven to be an effective method in control of non-Gaussian stochastic systems. In this case, the entropy is proposed as a generalization of the variance measure to characterize the randomness of the process. Minimum entropy corresponds to small uncertainty (or derivation), but it cannot guarantee the tracking error approaching to zero. Therefore, mean square error also should be added in the criterion. In this paper, by using a simple example, the method of generating a representative approximation of the Pareto optimal control set is investigated in both analytical and numerical ways. And simulation results show the feasibility of the proposed double-objective optimal control method.
With the increasing number of wind farms in powersystems, the scheduling of a single wind farm needs to be improved. For this end, this paper proposes an optimal short-term load dispatch strategy for a single wind fa...
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With the increasing number of wind farms in powersystems, the scheduling of a single wind farm needs to be improved. For this end, this paper proposes an optimal short-term load dispatch strategy for a single wind farm. Firstly, considering the large number of wind units and the high dimensionality of the scheduling solutions, we analyze the unit load characteristics, from which we extract the unit load characteristic matrix, and then classify the wind power units with the FCM fuzzy clustering algorithm. Secondly, we define the running loss indicator and action loss indicator. Based on the prediction of wind power and the load instructions, we establish a unit commitment model in wind farm, and solve the model using a combination of the fuzzy clustering algorithm and genetic algorithm, which overcomes the difficulty of the high dimensionality of the solution in the wind farm scheduling problem, to obtain the optimal scheduling strategy. Finally, through the simulation of the scheduling strategy for a 45 MW wind farm, we demonstrate the feasibility and effectiveness of the proposed strategy.
In this paper, we examine a resonant capacitor current feedback (RCCF) self-oscillating resonant inverter from nonlinear point of view. By adopting a four-stage equivalent model, we derive the soft-switching dead time...
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