A Method for Predicting Charging Load Demand of Electric Vehicles Based on Random Forest
Author:
Affiliation:
1. Economic Research Institute of State Grid Zhejiang Electric Power Company, China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3674225.3674347
Reference10 articles.
1. Online EV Charge Scheduling Based on Time-of-Use Pricing and Peak Load Minimization;WU W.;Properties and Efficient Algorithms.,2022
2. AKIL MURAT DOKUR EMRAH BAYINDIR RAMAZAN. 2022. Smart coordination of predictive load balancing for residential electric vehicles based on EMD-Bayesian optimised LSTM. IET renewable power generation 16(15): 3216-3232.
3. A novel resilient state of charge balancing method for distributed storage systems based autonomous microgrids;OUOBA DE V;Journal of Energy Storage, 55(Nov. Pt.A),2022
4. Clustering Prediction of Electric Vehicle Charging Load Considering Similar Days and Meteorological Factors;X.;Electric Power Construction,2021
5. AKIL MURAT DOKUR EMRAH BAYINDIR RAMAZAN. 2022. Smart coordination of predictive load balancing for residential electric vehicles based on EMD-Bayesian optimised LSTM. IET renewable power generation 16(15): 3216-3232.
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