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Predicting the Power Generation from Renewable Energy Sources by using ANN

机译:通过使用ANN预测可再生能源的发电

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This paper proposes power generation forecasting for photovoltaic power plants by using Adaptive Neuro-Fuzzy Inference Systems library in MATLAB and considering meteorological factors. Renewable energy sources (RES) introduce compensation instability problems in the grid hence forecasting methods are considered. Especially important for grid operators is a day ahead forecasting as it can reduce negative imbalance price. Means of ensuring the balance reliability of the power system in terms of RES integration are presented. The installation of charging stations for electric vehicles or use of hydrogen technologies and modern storage systems can provide grid balance. In addition, decreasing the deviation of the current (real) value from the predicted value of power generation is a way to compensate for power unbalance.
机译:本文提出了利用Matlab中的自适应神经模糊推理系统库和考虑气象因素来提出了对光伏发电厂的发电预测。 可再生能源(RES)在栅格中引入补偿不稳定问题,因此考虑了预测方法。 对于网格运营商特别重要,是预测的一天预测,因为它可以降低负面不平衡价格。 提出了在res集成方面确保电力系统平衡可靠性的方法。 用于电动汽车的充电站或使用氢气技术和现代存储系统的安装可以提供网格平衡。 另外,从发电量的预测值下减少电流(实际)值的偏差是一种补偿功率不平衡的方式。

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