Open AccessRandom Forest-Based Method for Micro Grid System in Energy Consumption Prediction
Author(s) -
Murugananth Gopal Raj,
C. Pradip,
N Saju,
S. Sangeetha
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1964/5/052002
Subject(s) - microgrid , random forest , energy consumption , computer science , energy (signal processing) , consumption (sociology) , grid , estimation , statistics , engineering , artificial intelligence , mathematics , electrical engineering , systems engineering , social science , geometry , control (management) , sociology
As a solution to mitigating rising energy needs, microgrids (MG) have arisen. But instead of microgrids are focused mainly on unconventional sources of energy. In their service, there is significant variability. Energy users will not know if their estimated load is long or short related to historical records. This paper aims to formulate a robust energy prediction of consumption in the microgrid system that uses random forest (RF) method theory as the mathematical framework. Effective MG energy forecast plays an essential role in power improvement MG efficacy. Comparing RF models with various parameter configurations and examining the parameters setting affects the model’s estimation efficiency.