Wind-Power Estimating Model Based on the Experimental Data in Laboratory
Planning long-term generation resource is always with many unknown and uncertain factors. As wind generation does not create any harmful emissions, it becomes a means to reduce a country’s national emissions levels. However, the characteristics of wind-power (WP) generation are fundamentally different from those of conventional ones. These characteristics must be fully recognized within planning assessments. For example, transmission system operators (TSOs) must adapt their grid codes, as active power, frequency, and voltage controls, reactive power compensation, or voltage sag immunity etc., to enable wind generation and ensure the system security. On the other hand, difficulties mentioned above make WP generation in estimating energy production more challenge. WP estimation is necessary for power system in several operations, which are as the optimal power flow between conventional units and wind farms, generators scheduling, and electricity market bidding. Estimating the output power of a wind energy conversion unit (WEC) mainly bases on the incident wind speed at the unit site by using the power characteristic curve. In addition, several time-series models have been using in wind speed forecasting. These models are characterized with requiring a large set of data. In order to prevent from the wind speed measurement and the need of a precise wind turbine model, an novel method basing on neural network and the grey predictor model GM (1,1) is proposed. Though the method, the estimating model can be built only by using the experimental data, which are obtained from the WP system in laboratory. The effectiveness of the estimating model is confirmed by the simulation results.
wind-power estimating model neural network grey predictor model
C. N. Huang H. P. Wang L.Y. Kang G.H. Wu
Graduate Institute of Mechatronic System Engineering, National University of Tainan, 33, Sec. 2, Shu Guangdong key laboratory of Clean energy technology, School of Electric Power, South China Universit Department of Electrical Engineering and Information Technology, Faculty of Engineering, Tohoku Gaku
国际会议
The International Conference on Electrical Engineering 2009(2009 电机工程国际会议)
沈阳
英文
1-6
2009-07-05（万方平台首次上网日期，不代表论文的发表时间）