Open AccessA Multi Fusion Data Mining Algorithm for Solar Energy Efficiency
Author(s) -
Lin Yue,
Zhan Shuo,
Jing Bai,
Shunshoku Kanae
Publication year - 2020
Publication title -
international journal of circuits, systems and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.156
H-Index - 13
ISSN - 1998-4464
DOI - 10.46300/9106.2020.14.65
Subject(s) - renewable energy , photovoltaic system , solar energy , solar power , computer science , position (finance) , power (physics) , algorithm , engineering , electrical engineering , physics , finance , quantum mechanics , economics
The output power of renewable energy has thecharacteristics of random fluctuation, which have the harmfuleffect on stability of renewable power grid and causes the problemof low utilization ratio on renewable energy output power. Thus,this paper proposed a method to predict the output power ofrenewable energy based on data mining technology. Data miningis performed using linear regression algorithm, decision tree, andrandom forest. The simulation experiment results show thevariation of solar radiation size and inclination angle, whichimproves solar panel position control accuracy and solar energyutilization in solar photovoltaic power generation systems. Andthis provides the scientific basis for theory and application of theefficiency of utilizing solar energy.