Open AccessMarkov model in home energy management system
Author(s) -
Jiayuan Bai
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 - 10.1088/1742-6596/1871/1/012043
Subject(s) - energy management system , energy management , markov decision process , markov chain , energy (signal processing) , computer science , work (physics) , markov model , reinforcement learning , state (computer science) , control (management) , markov process , management system , operations research , simulation , artificial intelligence , engineering , operations management , machine learning , mechanical engineering , statistics , mathematics , algorithm
An intelligent home energy management system was proposed. Reinforcement learning and a markov prediction model were used to help the system make decisions. The Markov model predicted the future state of users or the weather, and the intelligent decisionmaking support system sent signals to local controllers to control furniture. This work benefits energy management because if the system knows the user’s next state, it can control a specific appliance to save energy. Meanwhile, if the system can predict the weather, the house can use green energy rationally. The proposed energy management system could be applied in an intelligent house, city energy management systems, and building energy management. The state prediction helped the decision-making system make accurate and rational decisions.