Investigation on Energy Data Prediction and Optimization Methods Based on Deep Learning
Author:
Affiliation:
1. State Grid Info-Telecom Great Power Science and Technology Co.Ltd,Fuzhou,Fujian,China,350003
2. Fuzhou Power Supply Company of State Grid Fujian Electric Power Company,Fuzhou,China,350009
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10405420/10405394/10405611.pdf?arnumber=10405611
Reference20 articles.
1. Analysis of new energy power prediction characteristics and measures to improve accuracy [J];Deng;Southern Power Grid Technology,2023
2. Short-term multivariate load prediction of integrated energy system driven by data [J];Wang;Computer Engineering and Design,2022
3. Design of short-term load prediction algorithm for high-permeability new energy power grids [J];Wang;Electronic Design Engineering,2023
4. Electricity load forecasting using clustering and ARIMA model for energy management in buildings
5. Energy forecasting in smart grid systems: recent advancements in probabilistic deep learning
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