Simulation Research on Power Grid Investment Demand Forecasting Model Based on Grey Clustering Algorithm

Author:

Tang Yimin1,Bai Yang1,Hu Jian2,Liu Shiyang2,Chen Xiaotian2

Affiliation:

1. Shanghai Electric Power Engineering Construction Consulting branch,Shanghai,China,200000

2. Beijing Jinghang Telek Technology Co., Ltd,Beijing,China,100000

Publisher

IEEE

Reference10 articles.

1. Hybrid ANN and Artificial Cooperative Search Algorithm to Forecast Short-Term Electricity Price in De-Regulated Electricity Market

2. General Regression Neural Network and Artificial-BeeColony Based General Regression Neural Network Approaches to the Number of End-of-Life Vehicles in China;Fang;IEEE Access,2018

3. Prediction of Grid-Connected Photovoltaic Power Generation Based on Multivariate Statistics;Xu;Nonlinear Optics, Quantum Optics,2019

4. A Hybrid Method Based on Empirical Mode Decomposition and Random Forest Regression for Wind Power Forecasting;Kaya;Journal of multiple-valued logic and soft computing,2018

5. Temperature Droop-Based Dynamic Reactive Power Sharing Technique to Improve the Lifetime of Power Electronic Converter

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