Research On Household Electricity Consumption Optimization Based On User Habit Analysis

With the rapid development of the national economy and the continuous advancement of urbanization,people’s living standards continue to improve.The demand for electricity consumption in family life has risen sharply,and the structure of electricity consumption has gradually become more complicated.The optimization of household electricity consumption has become an important research issue of residential building energy conservation.In the process of optimizing electricity consumption,the different lifestyles of users and their preferences for various electrical appliances can have a significant impact on the optimization results.In view of the fact that the current home electricity consumption optimization research does not fully explore the user’s habits and preset the user’s electricity consumption behavior,this thesis analyzes the electricity consumption based on the analysis of user habits.In this way,the electricity consumption optimization plan that best meets the needs of users can be formulated to help users realize intelligent management of household electricity consumption with improvement of the efficiency.The research content of this thesis is as follows:(1)The framework system and related technologies of home energy management system are briefly described.The scheduling types of household’s loads are also classified and modeled according to their different characteristics.(2)The electricity consumption behavior of household users is analyzed,and a circular coordinate fitting method is proposed to reflect the daily electricity consumption habits of users in the form of data points on circular coordinates.The pre-processed data is then judged by the Elbow Rule to determine the number of users’ habits,followed by an improved K-mean clustering algorithm,which is applied to the cluster analysis of a collection of electricity data points,while statistical analysis is performed to fully explore the personalized needs and usage preferences of the user for various home appliances.(3)A multi-objective intelligent electricity consumption optimization model considering electricity expenditure,customer satisfaction and peak-to-average ratio of electricity consumption is established.Aiming at the shortcomings of the standard artificial bee colony algorithm in solving practical application problems,an improved artificial bee colony algorithm is proposed to solve the optimization model.(4)Simulation experiments are performed with MATLAB platform by using real household electricity data sets.Conduct a detailed analysis of user habits and generate working parameters for each load under the household’s electricity consumption habits.Based on this,the MATLAB simulation of the multi-objective function optimization model proposed in this thesis is carried out,and the improved artificial bee colony algorithm is used to optimize electricity consumption based on the time-of-use electricity price environment,and the optimization effect is compared with other well-known optimization algorithms.The validity and feasibility of the proposed method are verified by simulation analysis of examples.The strategy in this thesis can be customized according to the electricity consumption needs of different households,so as to truly implement policies for each household and comprehensively improve the convenience and comfort of users in using electricity.In addition,users can also actively participate in the electricity plan.It adjust and improve personal habits to achieve a more reasonable and energy-efficient electricity consumption.