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- W2747035712 abstract "Solar Photovoltaics is a source of energy very sensitive to climate variations. Therefore, it is very important to apply a forecasting method to a PV system. Solar forecasting provides extremely useful information for tasks such as management of electricity grids and solar energy trading, where good accuracy and good performance are desirable goals for a very short term forecasting model. In this paper, we propose the use of fuzzy time series (FTS) techniques to this problem. Specifically, Chen's first order and high-order FTS methods and the Weighted FTS method are compared with other forecasting models widely used to approach solar irradiance forecasting. We evaluate the performance of FTS methods and different forecasting techniques to solve very short-term solar forecasting problems. The results show that FTS methods are able to achieve significant improvements in forecasting accuracy and performance if compared to other forecasting methods. A discussion on how to improve the forecasting performance of FTS models is also provided." @default.
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- W2747035712 date "2017-07-01" @default.
- W2747035712 modified "2023-09-30" @default.
- W2747035712 title "Very short-term solar forecasting using fuzzy time series" @default.
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- W2747035712 doi "https://doi.org/10.1109/fuzz-ieee.2017.8015732" @default.
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