A Short-Term Prediction Method for PV Power Generation Based on SVM Weather Classification and PSO-BP Neural Network
Author:
Affiliation:
1. School of Electrical Engineering, Chongqing University,Chongqing,China
2. School of Eletrical Engineering, Xi'an Jiaotong University,Xi'an,China
Funder
Xi'an Jiaotong University
National Natural Science Foundation of China
State Key Laboratory of Power System Operation and Control
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10394673/10394683/10394800.pdf?arnumber=10394800
Reference13 articles.
1. Sustainable electric power systems in the 21st century: requirements, challenges and the role of new technologies
2. Revisiting Grid-Forming and Grid-Following Inverters: A Duality Theory
3. Capacity and output power estimation approach of individual behind-the-meter distributed photovoltaic system for demand response baseline estimation
4. Multiple-Input Deep Convolutional Neural Network Model for Short-Term Photovoltaic Power Forecasting
5. A Weather-Based Hybrid Method for 1-Day Ahead Hourly Forecasting of PV Power Output
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