The Power of Wind Turbine Generators Prediction Model Based on Time Series

Guan Jia Huang; Shao Mei Fang; Si Tu Qiaojun

doi:10.4028/www.scientific.net/AMR.860-863.394

Paper Titles

Analysis on Low-Carbon Comprehensive Benefit of Wind Power
p.368

Analysis on the Policies of Wind Power Generation Industry in China - In the Perspective of Externality Theory
p.375

Research on Preventive Maintenance Cycle Decision of Wind Turbine
p.383

Study on Automatic Active Power Control System of Wind Farms
p.389

The Power of Wind Turbine Generators Prediction Model Based on Time Series
p.394

Security and Economy Analysis of Power Grid Considering the Uncertainty of Demand Side and Generation Side
p.398

Regional Wind Power Forecasting Based on Cloud Model and Wind Rate Vector
p.405

Considering Wind Power Abortively Based on Petri Net Research on Optimization of Hydropower
p.409

An Multi-Objective Optimization Model for Wind-Storage Combined Operation
p.414

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 860-863The Power of Wind Turbine Generators Prediction...

The Power of Wind Turbine Generators Prediction Model Based on Time Series

Abstract:

Author constructed ARIMA model and GARCH model to predict the output power of the 4 wind turbine generators (A, B, C, D) and the total output power of the 4 and 58 wind turbine generators. Whats more, by comparing the results of two methods, it shows that the result of GARCH model is more accurate than ARIMA model in short-term prediction.