Research Of Smart Home Energy Management Based On Demend Response

With the emergence of a lot of smart meters, sensors, and various control devices, smart grid promotes the power of control and management and realizes the interaction with the user. In the backdrop of the smart grid and demand response, home energy management as an important part of smart grid, provides new impetus to achieve energy conservation and emissions reduction, and to improve the efficiency of electricity. Home energy management how to provide users with an optimal household appliances management strategy and to reduce electricity costs and meet user requirements, so as to better guide the user to use electricity, has become a research hotspot. To solve above problems, this article from the following aspects, the main contents are as follows:Firstly, the Internet of things technology and the application of the Internet of things technology in the family are discussed in this paper. This paper analyses the intelligent family model, the paper introduces the intelligent family of related equipment, intelligent family physical architecture based on the technology of Internet of things and intelligent home energy management information flow. The basic concept of data mining and the commonly used method are overviewed.Then, the paper studies the rule of the use of household appliances, and proposes a prediction method of household appliances based on the theory of data mining. According to the characteristics of different household appliances, the paper gets the classifications of household appliances. Through the household electrical appliances related data analysis, the paper finds out the main factors influencing the household appliances used. The paper uses the data processing, correlation analysis and adaptive neural fuzzy inference system three steps to complete for the forecast of the usage of household appliances.Finally, according to the needs of users, the mathematical model of household appliances demand response is established, and different satisfaction quantization function is set up. Considering photovoltaic power generation and storage battery connected to the family, electricity expenses minimum and user satisfaction as optimization objective, the time interval optimization algorithm is proposed, and the paper applies multi-objective Bacterial Colony Chemotaxis optimization method to solve the multi-objective optimization problem. Due to the more uncertain factors of the use of household electrical appliances, the paper set up three different real-time adjustment scenarios, and put forward the real-time adjustment strategy, so as to effectively help users to participate in network interaction, guiding the user to save electricity and money.