scholarly journals Wind power prediction system software performance analysis and optimization research

2019 ◽  
Author(s):  
Xuewei Bai
Keyword(s):  
Performance Analysis ◽  
Wind Power ◽  
Software Performance ◽  
Prediction System ◽  
System Software ◽  
Power Prediction ◽  
Wind Power Prediction

Research on Wind Power Prediction Based on Distributed Wind Farms Siting

2013 ◽  
Vol 805-806 ◽  
pp. 312-315 ◽  
Author(s):  
Jun Yang ◽  
Zhao Qiang Zeng ◽  
Xu Huang ◽  
Qiu Ye Sun
Keyword(s):  
Wind Speed ◽  
Wind Power ◽  
Wind Farms ◽  
New Method ◽  
Prediction System ◽  
Power Prediction ◽  
Roughness Model ◽  
Wind Power Prediction

This paper proposes a new method to predict the wind power of the distributed wind farms, considering the models such as the roughness model, the orography model. In order to predict the wind power accurately, this method calculates the loss of the wind speed directly, caused by the roughness model and the orography model. At the same time, this paper proposed the structure of the wind power prediction system, which provides the reference for the prediction of the wind power of distributed wind farms.

Real-time Wind Power Prediction System Based on Smart-Grid in Jeju, Korea

2012 ◽  
Vol 2 (2) ◽  
pp. 194-200 ◽  
Author(s):  
Kwon Kim ◽  
Young-Jun Seo ◽  
Kyoung-Seob Moon ◽  
Young-Mi Lee
Keyword(s):  
Smart Grid ◽  
Real Time ◽  
Wind Power ◽  
Prediction System ◽  
Power Prediction ◽  
Wind Power Prediction

Algorithm and Realization of Wind Power Prediction System

2013 ◽  
Vol 748 ◽  
pp. 439-443
Author(s):  
L. Zhou ◽  
E.W. He ◽  
J.C. Wang ◽  
D.H. Chen ◽  
Q.Z. Chen
Keyword(s):  
Time Series ◽  
Prediction Model ◽  
Wind Power ◽  
Wind Farm ◽  
Stable Operation ◽  
Prediction System ◽  
Power Prediction ◽  
Model Based ◽  
Term Prediction ◽  
Wind Power Prediction

The application of wind power prediction system (WPPS) contributes to security economic dispatching of power grid and stable operation of wind farm. This paper established short-term prediction model based on BP neural network and ultrashort-term prediction model based on improved time-series algorithm according to Xichang Wind Farm Phase I Project. A new probability model using two consecutive power points before prediction time was built to improve the traditional time-series algorithm. The system framework was designed. C# Language and SQL Server 2008 were taken to develop the system on the Microsoft .net platform. The WPPS uses distributed architecture, realizing seamless connection with the energy management system (EMS) of Xichang dispatching department.

Simple Wind Power Prediction System Using Self-Tuning Fuzzy Reasoning and Error Persistent Model

2009 ◽  
Vol 129 (5) ◽  
pp. 614-620 ◽  
Author(s):  
Naoto Fujimura ◽  
Takashi Yasuno ◽  
Ryota Yakushiji ◽  
Kiyoshi Takigawa ◽  
Kensuke Kawasaki
Keyword(s):  
Wind Power ◽  
Fuzzy Reasoning ◽  
Prediction System ◽  
Power Prediction ◽  
Wind Power Prediction ◽  
Self Tuning
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