The Optimal Spinning Reserve Considering Wind Power Prediction Deviation

2013 ◽  
Vol 860-863 ◽  
pp. 299-304
Author(s):  
Xiao Ming Jin ◽  
Dong Mei Zhao ◽  
Long Long Li ◽  
Dong Hui Zhang
Keyword(s):  
Power System ◽  
Wind Power ◽  
Power Prediction ◽  
Spinning Reserve ◽  
Load Duration ◽  
Power Characteristics ◽  
Wind Power Prediction ◽  
Equivalent Load ◽  
The Impact ◽  
Complete Optimization

With the capacity of wind power into power system increasing year by year, the impact of wind power characteristics (random and intermittent) on the system stable equilibrium is outstanding. To configure spinning reserve properly, this paper establishes a relatively complete optimization model of spinning reserve for power system with wind integrated. Using the similar samples to train prediction model, the precision of prediction is improved. The equivalent load duration curve (ELDC) considering load fluctuations and unit outage, is revised by analyzing the probability density of wind power prediction deviation. And the last, this paper gives an example to verify the theory.

A state-of-the-art review on wind power deterministic prediction

2020 ◽  
pp. 0309524X2094120 ◽  
Author(s):  
Zhongda Tian
Keyword(s):  
Wind Power ◽  
Prediction Method ◽  
Scale Model ◽  
Ensemble Prediction ◽  
Prediction Methods ◽  
Power Prediction ◽  
Continuous Growth ◽  
Advantages And Disadvantages ◽  
Wind Power Prediction ◽  
The Impact

With the continuous growth of wind power access capacity, the impact of intermittent and volatile wind power generation on the grid is becoming more and more obvious, so the research of wind power prediction method has been widely concerned. Accurate wind power prediction can provide necessary support for the power grid dispatching, combined operation of generating units, operation, and maintenance of wind farms. According to the existing wind power prediction methods, the wind power prediction methods are systematically classified according to the time scale, model object, and model principle of prediction. The physical methods, statistical methods include single and ensemble prediction methods related to wind power prediction are introduced in detail. The error evaluation indicator of the prediction method is analyzed, and the advantages and disadvantages of each prediction method and its applicable occasions are given. At the same time, in view of the existing problems in the wind power prediction method, the corresponding improvement plan is put forward. Finally, this article points out that the research is needed for wind power prediction in the future.

Application of Portfolio Theory Based on CVaR in Determining Optimal Spinning Reserve with Consideration of Load and Wind Power Uncertainties

2013 ◽  
Vol 724-725 ◽  
pp. 649-654
Author(s):  
Jun Li Wu ◽  
Bu Han Zhang ◽  
Zhen Yin Xiao ◽  
Kui Wang
Keyword(s):  
Power System ◽  
Wind Power ◽  
Value At Risk ◽  
Efficient Frontier ◽  
Portfolio Theory ◽  
Conditional Value At Risk ◽  
Power Prediction ◽  
Spinning Reserve ◽  
The Cost ◽  
Installed Capacity

With the increased installed capacity of wind power in power system, determining optimal spinning reserve capacity is one of the most important problems in operation of electricity power system. CVaR (conditional value at risk) is introduced to calculate the risk of the cost associated with load shed and abandoning wind power with the consideration of load and wind power prediction uncertainties. Portfolio theory based on CVaR is used to build the Cost-CVaR model. Efficient frontier, which can support the system operators (SO) with the decision of optimal spinning reserve, can be obtained by solving the Cost-CVaR model. The analysis of RTS example can demonstrate the usefulness and efficiency of the model.

Research of Aggregated Wind Power Prediction Method for a Region

2013 ◽  
Vol 860-863 ◽  
pp. 262-266
Author(s):  
Jin Yao Zhu ◽  
Jing Ru Yan ◽  
Xue Shen ◽  
Ran Li
Keyword(s):  
Power Systems ◽  
Wind Power ◽  
Large Scale ◽  
Wind Farm ◽  
Prediction Method ◽  
Support Vector ◽  
Power Prediction ◽  
Power Characteristics ◽  
Wind Power Prediction ◽  
Grey Correlation Theory

Wind power is intermittent and volatility. Some new problems would arise to power system operation when Large-scale wind farm is connected with power systems. One of the most important effect is the influence on the grid dispatch. An aggregated wind power prediction method for a region is presented. By means of analyzing power characteristics and correlation, then the greater correlation is selected as model input. Based on grey correlation theory, a least squares support vector machine prediction model is established. Finally, this method is executed on a real case and integrated wind power prediction method can effectively improve the prediction accuracy and simplify the prediction step are proved.

scholarly journals Wind Power Prediction in View of Ramping Events Based on Classified Spatiotemporal Network

2022 ◽  
Vol 9 ◽  
Author(s):  
Bingbing Xia ◽  
Qiyue Huang ◽  
Hao Wang ◽  
Liheng Ying
Keyword(s):  
Power System ◽  
Prediction Model ◽  
Wind Power ◽  
Large Scale ◽  
Weather Prediction ◽  
Measurement Data ◽  
Stable Operation ◽  
Power Prediction ◽  
Actual Measurement ◽  
Wind Power Prediction

Wind energy has been connected to the power system on a large scale with the advantage of little pollution and large reserves. While ramping events under the influence of extreme weather will cause damage to the safe and stable operation of power system. It is significant to promote the consumption of renewable energy by improving the power prediction accuracy of ramping events. This paper presents a wind power prediction model of ramping events based on classified spatiotemporal network. Firstly, the spinning door algorithm builds parallelograms to identify ramping events from historical data. Due to the rarity of ramping events, the serious shortage of samples restricts the accuracy of the prediction model. By using generative adversarial network for training, simulated ramping data are generated to expand the database. After obtaining sufficient data, classification and type prediction of ramping events are carried out, and the type probability is calculated. Combined with the probability weight, the spatiotemporal neural network considering numerical weather prediction data is used to realize power prediction. Finally, the effectiveness of the model is verified by the actual measurement data of a wind farm in Northeast China.

Short-Term Wind Power Prediction Based on Phase Space Reconstruction Theory

2013 ◽  
Vol 364 ◽  
pp. 112-117
Author(s):  
Zhi Gang Li ◽  
Ling Ling Li ◽  
Jun Hao Li ◽  
Shi Nuan Zhang
Keyword(s):  
Phase Space ◽  
Wind Power ◽  
Large Scale ◽  
Phase Space Reconstruction ◽  
Model Parameters ◽  
Analytical Control ◽  
Power Prediction ◽  
Spinning Reserve ◽  
Forecast Precision ◽  
Wind Power Prediction

The accession of large scale wind power will impact the planning and construction, analytical control, operation of the economy, as well as power quality of the power grid. More accurate wind power prediction can help reduce the quantity of spinning reserve and provide the grid dispatching operation a reliable foundation. Wind power has chaotic characteristic. This paper proposed a method of chaotic time series prediction based on chaotic phase space reconstruction. The forecast precision depends largely on the choice of the model parameters. In order to improve the forecast precision and generalization ability of the prediction model, this article computed with the method of C-C to optimize the phase space reconstruction parameters comprehensive. Forecasting model used weighting first-order local field method. To test the approach, the data from a wind farm of Inner Mongolia were used. Practical examples showed that the integrated approach has a very good forecast precision and good practicability.

The Impact of Power System Frequency Regulation Caused by Wind Disturbance

2014 ◽  
Vol 644-650 ◽  
pp. 3840-3843
Author(s):  
San Ming Liu ◽  
Zhi Jie Wang ◽  
Xia Sun ◽  
Yi Teng Liang ◽  
Xiao Wei Zhu
Keyword(s):  
Power System ◽  
Wind Power ◽  
Wind Farms ◽  
Practical Method ◽  
Voltage Regulation ◽  
Frequency Regulation ◽  
Wind Disturbance ◽  
Spinning Reserve ◽  
Related Factors ◽  
The Impact

The impacts of wind disturbance on voltage regulation and frequency regulation of power system were studied. The opinion that the regulation of power flow on the tie lines between the grids constrains the integrated capacity of wind power was put forward. Based on the real condition of Inner Mongolia power grid, an engineering practical method was put forward to calculate the integrated capacity of wind power under this constraint. The relationship between wind power and spinning reserve and the impacts of other related factors on the capacity of wind power were studied as well. The impact of wind disturbance on voltage stability where the wind farms are located was studied.

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