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

Abstract:

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.

• Periodical: Applied Mechanics and Materials (Volumes 448-453)
• Pages: 2762-2768
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.448-453.2762
• Online since: October 2013
• Authors: Zhi Jian Liu, Rong Huang, Zhi Hua Yang
• Keywords: Comprehensive Model, Electricity Market, Run-of-River Small Hydropower Station

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