Title :
Forecast of Power Generation for Grid-Connected Photovoltaic System Based on Markov Chain
Author :
Li, Ying-zi ; Niu, Jin-cang
Author_Institution :
Coll. of Inf. & Electr. Eng., Beijing Univ. of Civil Eng. & Archit., Beijing
Abstract :
A grid-connected photovoltaic system has the characteristics of time-varying and random. A Markov chain model of the power generation forecast was built based on the Markov decision theory according to the 6 kW PV system operating data. The initial formation probability matrix and transition matrix for power generation forecast have been obtained. After considering the weather conditions, solar radiation and other specific factors, if the statistical sample is large enough, the theoretical calculations are very close to the actual results. The results show forecast of power generation for grid-connected photovoltaic system based on Markov chain is feasible, correct and effective. The initial state and termination status have the character of good correlation between the transfer matrix and the results are more relatively reliable.
Keywords :
Markov processes; matrix algebra; photovoltaic power systems; power grids; probability; Markov chain model; Markov decision theory; grid-connected photovoltaic system; power 6 kW; power generation forecast; probability matrix; solar radiation; time-varying characteristics; Decision theory; Photovoltaic systems; Power system modeling; Power system reliability; Predictive models; Probability; Solar power generation; Solar radiation; Time varying systems; Weather forecasting;
Conference_Titel :
Power and Energy Engineering Conference, 2009. APPEEC 2009. Asia-Pacific
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-2486-3
Electronic_ISBN :
978-1-4244-2487-0
DOI :
10.1109/APPEEC.2009.4918386
