Research And Application Of M2M Communication In Intelligent Energy Management

With the shortage of fossil fuel resources and the growing demand for electricity in the society,a user-centric smart grid is gradually taking shape.The improper use of electricity on the residential side not only increases the cost of electricity but also increases the pressure of the grid.Therefore,the intelligent energy management as the last part of the smart grid is getting more and more attention.Due to the lack of data interaction in residential energy consumption and the lack of intelligent scheduling of household electrical equipment,energy consumption is unreasonable because of the improper energy consumption structure.In order to guide home users to better use electricity to improve the efficiency of residential side electricity,intelligent energy management based on M2 M technology is came into being.M2M communication is reliable,low-power,ubiquitous connection technology that can be established between a large number of devices.The core concept of M2 M is direct communication without human intervention.This paper takes M2 M communication in residential side intelligent energy management as the research object and combines demand response and real time price to schedule the working hours of the household flexible devices aiming to make M2 M communication provide a solution for intelligent energy management.The main research contents of this paper include the following aspects:(1)The development and research status of M2 M communication and intelligent energy management at home and abroad are introduced in this paper.According to the definition of M2 M by ETSI M2 M committee,the components of M2 M functional architecture and wireless M2 M communication are analyzed,and demand side management and real time prices related to intelligent energy management are expounded.Then the functional requirements of home energy management system(HEMS)and the M2 M network architecture in HEMS are explained explicitly.(2)To solve the problem of the lack of data interaction in intelligent energy management,ZigBee,Wifi and LTE are selected as the connection technologies of home area network(HAN),neighboring area network(NAN)and wide area network(WAN).Since M2 M data has the characteristics of small traffic and frequent transmission period,the dynamic planning algorithm is used to cluster the smart meter nodes by considering the maximum transmission distance of Wifi in NAN,so that the data traffic collected by smart meter is first uniformly transmitted to the concentrator and then transmitted to the base station by LTE.According to different priorities of M2 M data,the data traffic are classified and then the radio resources in WAN are allocated by using differentiated random access for bandwidth request and non-preemptive priority queuing method for bandwidth authorization.The data transmission between smart meter and control center is finally realized.The simulation result shows that clustering strategy in NAN can reduce the transmission cost between the smart meter and the base station and the radio resource management scheme based on the data traffic priority can effectively reduce transmission delay of the high priority data traffic.(3)To solve the problem of the irrational electricity structure of the residential side,the household energy consumption mode which takes the electricity cost and user satisfaction into account is analyzed on the premise of successful data traffic transmission.Short-term load forecasting for household hourly electricity consumption is performed by least squares support vector machine(LS-SVM).Combined with the real-time price of the day,the discrete binary particle swarm optimization algorithm(DBPSO)with improved sigmoid function optimizes the working hours of the home flexible devices achieving the goal of maximizing the user satisfaction and minimizing the electricity cost.The simulation result shows the proposed method can transfer some flexible devices’ working hours to lower price periods or more clean energy output periods,reducing the electricity cost while maintaining good user satisfaction.