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Stanford sky images and PV power generation dataset for solar forecasting related research and applications

License: MIT License

Jupyter Notebook 99.98% Python 0.02%
sky-image computer-vision deep-learning solar-forecasting cloud-detection convolutional-neural-networks cloud-movement-prediction fish-eye-camera pv-power-generation sun-tracking

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stanford-solar-forecasting-dataset's Issues

The dataset for SUNSET-forecast

Thanks for your great work. However, I have some trobule when I try to reproduce the SUNSET-forecast model. I cann't find the file 'forecast_dataset.h5py' for this model. I also cannot find the files 'all_times_highfreq.npy' 'all_images_highfreq.npy' and 'pv_output_valid.pkl'. How can I get these files?

Cloudiness Information

H @yuhao-nie and @ascott-20, in your paper table 5.1 you evaluate your models separately on cloudy and sunny days. However, this information is not natively included in your dataset to be downloaded. There is information in the preprocessing jupyter notebooks about cloudy and sunny days. However, when I do the following for the forecast task:

sunny_day = [(2017,9,15),(2017,10,6),(2017,10,22),(2018,2,16),(2018,6,12),(2018,6,23),(2019,1,25),(2019,6,23),(2019,7,14),(2019,10,14)]
cloudy_day = [(2017,6,24),(2017,9,20),(2017,10,11),(2018,1,25),(2018,3,9),(2018,10,4),(2019,5,27),(2019,6,28),(2019,8,10),(2019,10,19)]

sunny_datetime = [datetime.datetime(day[0],day[1],day[2]) for day in sunny_day]
cloudy_datetime = [datetime.datetime(day[0],day[1],day[2]) for day in cloudy_day]

arr = np.load("times_test_forecast.npy", allow_pickle=True)
date_arr = [val.date() for val in arr]
sunny_arr = [val.date() for val in sunny_datetime]
cloudy_arr = [val.date() for val in cloudy_datetime]

print(set(date_arr).intersection(set(sunny_arr)))
print(set(date_arr).intersection(set(cloudy_arr)))

The intersection with test forecasting dates and sunny dates is empty, suggesting there are no sunny test dates, only cloudy ones. However, you are reporting values for those in your paper.

For the nowcasting task, the above snippet yields, that the number of cloudy and sunny examples is about equal which is to be expected I guess. Could you help me out what I am missing?

Edit:
The times_test_forecast.npy file is generated from running my script in #3

About Research Equipment.

Hello, I would like to ask if you have used the Hikvision DS-2CD6362F-IV2, a 6-megapixel camera, in your paper. However, in my country, it seems that only 5-megapixel cameras are available,Hikvision DS-zXA3956F.Can I use the data captured by such a camera with your code?Can it withstand outdoor environments?

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