Research On Energy Efficiency Optimization Management Of Smart Home System

As the increasingly serious world energy problems become prominent,how to improve energy utilization and improve user-side energy efficiency optimization strategies have become a key part of solving energy problems.With the rapid development of smart grid construction,smart homes,which are used to achieve efficient use of energy and are an important component of smart grids,are receiving more and more attention from scholars.Therefore,constructing a smart home load model,analyzing user-side power consumption habits,and formulating control strategies for electrical equipment will have important significance for the energy optimization management of the smart home system.This paper first gives a detailed description of the three aspects of the structure of the smart home system,the communication method and the smart gateway.Select the Zig Bee module of the CC2530 chip,and use the Zig Bee communication method for internal networking of the home equipment,select the Wi Fi module of the ESP8266 chip,and use the Wi Fi communication method to communicate with the terminal device externally,and propose the application of Zig Bee and Wi Fi combined network data transmission Way to build a Zig Bee-Wi Fi smart gateway.Secondly,it analyzes the working characteristics of several typical loads in the home environment,and divides the household loads into rigid loads and flexible loads according to their working characteristics.Models and analyzes them respectively,and aims at the user’s electrical comfort and the time characteristics of environmental comfort and household load priority are studied.Then,it analyzes the market electricity price mechanism,proposes a control strategy targeting the air-conditioning equipment in the household load,sets the objective function and constraint conditions,based on this,proposes an improved particle swarm algorithm for optimization,and studies the feasibility of this control strategy.Finally,through the MATLAB simulation platform,the improved particle swarm algorithm is programmed and simulated and verified.For the air-conditioning control strategy,on the basis of the time-of-use electricity price,the user’s environmental comfort and the goal of reducing electricity costs were considered.The particle swarm algorithm control and the air conditioner controlled by the improved particle swarm algorithm are simulated and compared.The final result shows that the air conditioner operation energy consumption after the optimization of the improved particle swarm algorithm control strategy has been significantly reduced,reducing household electricity costs.The temperature change range is small,meeting the user’s comfort requirements.Figure[33] table[9] reference[84]...