scholarly journals A meteorological information mining-based wind speed model for adequacy assessment of power systems with wind power

2017 ◽  
Vol 93 ◽  
pp. 406-413 ◽  
Author(s):  
Yifei Guo ◽  
Houlei Gao ◽  
Qiuwei Wu
Keyword(s):  
Wind Speed ◽  
Power Systems ◽  
Wind Power ◽  
Information Mining ◽  
Adequacy Assessment

Wind Speed Forecasting Based on FNN in Wind Farm

2014 ◽  
Vol 651-653 ◽  
pp. 1117-1122
Author(s):  
Zheng Ning Fu ◽  
Hong Wen Xie
Keyword(s):  
Neural Network ◽  
Wind Speed ◽  
Power Systems ◽  
Wind Power ◽  
Power Plants ◽  
Fuzzy Neural Network ◽  
Negative Impact ◽  
Wind Speed Forecasting ◽  
Wind Power Plants ◽  
Fuzzy Neural

Wind speed forecasting plays a significant role to the operation of wind power plants and power systems. An accurate forecasting on wind power can effectively relieve or avoid the negative impact of wind power plants on power systems and enhance the competition of wind power plants in electric power market. Based on a fuzzy neural network (FNN), a method of wind speed forecasting is presented in this paper. By mining historical data as the learning stylebook, the fuzzy neural network (FNN) forecasts the wind speed. The simulation results show that this method can improve the accuracy of wind speed forecasting effectively.

Four-Dimensional Wind Speed Model for Adequacy Assessment of Power Systems With Wind Farms

2013 ◽  
Vol 28 (3) ◽  
pp. 2978-2985 ◽  
Author(s):  
Xiaoqing Han ◽  
Ying Qu ◽  
Peng Wang ◽  
Junhu Yang
Keyword(s):  
Wind Speed ◽  
Power Systems ◽  
Wind Farms ◽  
Adequacy Assessment

Short-Term Power Fluctuations of Large Wind Power Plants*

2002 ◽  
Vol 124 (4) ◽  
pp. 427-431 ◽  
Author(s):  
Yih-huei Wan ◽  
Demy Bucaneg,
Keyword(s):  
Wind Speed ◽  
Power Systems ◽  
Wind Power ◽  
Power Plants ◽  
Power Level ◽  
Short Term ◽  
Wind Power Plants ◽  
Weather Events ◽  
Power Fluctuations ◽  
Large Wind

To evaluate short-term wind power fluctuations and their impact on electric power systems, the National Renewable Energy Laboratory, in cooperation with Enron Wind, has started a project to record output power from several large commercial wind power plants at the 1-Hertz rate. This paper presents statistical properties of the data collected so far and discusses the results of data analysis. From the available data, we can already conclude that despite the stochastic nature of wind power fluctuations, the magnitudes and rates of wind power changes caused by wind speed variations are seldom extreme, nor are they totally random. Their values are bounded in narrow ranges. Power output data also show significant spatial variations within a large wind power plant. The data also offer encouraging evidence that accurate wind power forecasting is feasible. To the utility system, large wind power plants are not really random burdens. The narrow range of power level step changes provides a lot of information with which system operators can make short-term predictions of wind power. Large swings of wind power do occur, but those infrequent large changes (caused by wind speed changes) are always related to well-defined weather events, most of which can be accurately predicted in advance.

Short Term Wind Speed Forecast Revision Method Based on Volatility Characteristics and Confidence Level

2013 ◽  
Vol 816-817 ◽  
pp. 1260-1264
Author(s):  
Shi Qian Wang ◽  
Li Di ◽  
Jing Hui Huang ◽  
Chun Zheng Tian
Keyword(s):  
Wind Speed ◽  
Power Systems ◽  
Wind Power ◽  
Confidence Level ◽  
Power Markets ◽  
Short Term ◽  
Forecasting Method ◽  
Forecast Revision ◽  
Forecasting Errors ◽  
Positive Effect

Accurately forecasting short-term wind speed can effectively reduce the adverse effects of wind power in power systems and improve the competition of wind power in power markets. Because of the wind randomness, there are huge forecasting errors existing in those commonly used forecasting methods at wind mutation points, and through improving the forecasting method itself can merely provide positive effect. From the angle of revision, a new method is going to be proposed and applied to revise the forecasted wind speed in this paper, which is based on the historical data fluctuation characteristics and confidence level. Under this method, we can turn the original forecasted wind speed into the optimized wind speed. The revision method can be applied on all short-term wind forecast methods. The validity and feasibility of this method are going to be verified through a wind speed forecasting method based on the Grey model GM(1,1).

Power System Adequacy Exploration Based on UC Simulation Model

2015 ◽  
Vol 734 ◽  
pp. 744-747
Author(s):  
Zhen Bin Li ◽  
Xiao Lei Zhai
Keyword(s):  
Power Systems ◽  
Power System ◽  
Simulation Model ◽  
Wind Power ◽  
Large Scale ◽  
Unit Commitment ◽  
System Operation ◽  
Short Run ◽  
Adequacy Assessment ◽  
Random Fluctuations

This paper takes Unit Commitment with Wind Power Electric Systems for instance and studies the application of relevant indicators in the short run adequacy decisions. It first conducted running adequacy assessment of the RBTS system, and then given unit combination solutions in the ample index constraints. The results show that the relevant indicators can be more accurately to depict the influence of random factors on system operation adequacy, and Unit Commitment decisions based adequacy index is able to give a unit commitment program at different adequacy levels. The research results provide a set of assessment indicators and assessment methods for short running adequacy problems of random fluctuations power accessing to large-scale power systems..

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