论文信息 - A Comprehensive Model for Monthly Prediction of Energy Output of Run-of-River Small Hydropower Station in Electricity Market Environment

A Comprehensive Model for Monthly Prediction of Energy Output of Run-of-River Small Hydropower Station in Electricity Market Environment

According to generated output characteristics of run-of-river hydropower station in electricity market environment,a comprehensive model for monthly prediction of energy output based on Partial Least-Square (PLS) and improved Grey Model (GM) is established.The PLS model takes full advantage of the relationship between monthly energy output and its correlation affecting factors,and then using improved grey model to forecast its main factors to get final predictive results further.The comprehensive model not only can effectively use the limited sample,but also can weaken the random impact.The actual prediction results shows that the effect is better than common methods.

Rong Huang | Zhi Jian Liu | Zhi Hua Yang

[1] Li Jiu. Grey prediction model for annual energy output of a hydropower station without storage , 2001 .

[2] Yao Jiangang. Bus Load Forecasting Based on Improved Grey Model and Meteorological Elements , 2011 .

[3] Huang Shan. Medium- and Long-Term Load Forecasting Based on Partial Least Squares Regression Analysis , 2008 .

[4] Zhang Xiao-hui. A Double-fit Gray Modle of Mid-long Term Power Load Forecasting , 2005 .

[5] Sun Ke. Application of Two-Phase Reduction Method in Load Forecasting for Regions with Abundant Small Hydropower , 2009 .

[6] Zhang Xin. Prediction of Annual Precipitation Based on Improved Grey Markov Model , 2011 .