Yunlei Zhang1, Ruifeng Cao1, Danhuang Dong2, Sha Peng3,*, Ruoyun Du3, Xiaomin Xu3
Energy Engineering, Vol.119, No.5, pp. 1829-1841, 2022, DOI:10.32604/ee.2022.020118
- 21 July 2022
Abstract In the electricity market, fluctuations in real-time prices are unstable, and changes in short-term load are
determined by many factors. By studying the timing of charging and discharging, as well as the economic benefits
of energy storage in the process of participating in the power market, this paper takes energy storage scheduling as
merely one factor affecting short-term power load, which affects short-term load time series along with time-of-use
price, holidays, and temperature. A deep learning network is used to predict the short-term load, a convolutional
neural network (CNN) is used to extract the features, More >
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