Research On Intelligent Control And Management Technology For Home Appliances

With the rapid development of new industries and application technologies such as networking, cloud computing and triple-play bundling, it is an imperative work to improve the quality of life of residents by building a smart city and an intelligent life. Smart home appliance can also contribute to the development of the smart home industry. Smart home enriches our life and makes it more intelligent. However, the smart home system gives people more intelligent, comfortable and convenient living with the sacrifice of higher household energy consumption. Users are faced with much more household appliances and higher household energy consumption inevitably. Urbanization process exacerbates the problem. Users put forward more requirements for smart home. Therefore, these have become the huge challenge for intelligent household enterprises to meet the user’s intelligent life, control and manage independent of household equipment, maximize the usage of resources and save energy.The main contribution of this thesis provides a comprehensive management plan based on the control modes and operation characteristics of household equipment. The plan solves the problem of the isolated household equipment management which means the lacking of an overall level power management and cost control.The research contents of this thesis are divided into three parts. First, it designs a centralized distributed control framework and completes the corresponding demand analysis and summary design. On this basis, it selects a hardware platform for building an operating environment, and develops relevant control management software for the platform and tests its functionality, reliability and power consumption.Secondly, this thesis proposes the price-aware scheduling algorithm to save energy of smart home appliances based on the status of household applications and electricity pricing model. The results can prove the availability of the algorithm after comparing with the energy consumption of smart home system that do not use the scheduling algorithm.Finally, based on battery, we do research on the scheduling algorithm of cost control for household equipment. It can achieve lower cost by the detection of remaining battery power, the judgement of dynamic electricity price and a dynamic programming based optimization algorithm for scheduling management of home devices. Simulation experiment results show the advantages of the proposed algorithm.