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Predicting solar power output using complex fuzzy logic

机译:使用复杂的模糊逻辑预测太阳能输出

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Photovoltaic (PV) power is one of the most promising renewable energy sources. However, it is also intermittent, and thus short-term forecasts of PV power generation are needed to integrate PV power into the electricity grid. This article compares two existing machine-learning approaches for forecasting (ANFIS and radial basis function networks) against a new approach based on complex fuzzy logic (ANCFIS). The proposed approach was more accurate in predicting power output one minute in advance on a simulated solar cell.
机译:光伏(PV)电源是最有前途的可再生能源之一。但是,它也是断断续续的,因此需要将PV发电的短期预测整合到电网中。本文将现有的两种机器学习预测方法(ANFIS和径向基函数网络)与一种基于复杂模糊逻辑的新方法(ANCFIS)进行了比较。所提出的方法在模拟太阳能电池上提前一分钟预测功率输出时更加准确。

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