Study Of Enery Scheduling Algorithm In Smart Home

With people’s living standards increasing, smart home is gradually coming into our daily life and gains the popularity in industry. The research about smart home technologies becomes a hot research field. Power consumption management software in the smart home energy management syetem combining internet of tings technologies and smart grid technologies becomes urgent need in smart home industries. As the core of the smart home energy management software, the smart home energy scheduling algorithm has improtant influence on grid operation, using of renewable energy, cost of electricity and users comfort. Therefore, considering above factors, it is quite essential to research the smart home energy scheduling algorithm during the power consumption management software development course.This thesis, based on the smart home energy management system and the enviroment of user side in smart grid, thinking about the users habit of using the home devices and features of power grid operation, analyzes the development needs and trends about the smart home energy scheduling algorithm. On the premise of protection users comfort, this paper separately proposes a multiple smart homes energy scheduling algorithm ensuring stability of an electrical power system and a energy scheduling algorithm in single smart home with increasing energy efficiency and decreasing the cost of the electricity. It makes the software close to the residents practical application and more suitable for intelligent and information domestic life that the algorithms proposed in this paper apply to the smart home energy management software The main work is divided into the following sections:(1) For the energy scheduling algorithms in smart home, the paper respectively states the development demands for the smart home energy scheduling algorithms on the user side and grid side in the smart grid. For the demands mentioned above, the paper summarizes the latest developments and the effectiveness of the already existing smart home energy scheduling algorithms, and proposes the major issues which energy scheduling algorithms face. Based on the research existed, the paper further discusses and analyzes the influences of the factors which are scheduling area, the form of providing the data for algorithms and the users participation levels for the energy scheduling algorithms. And reasonable design and application methods of the smart home energy scheduling algorithms are proposed. Finally, it gives the key research expectations in this field.(2) Aiming at the problems that the demand of smart grid stability was ignored in single house energy scheduling and the users comfort was not well guaranteed in multi-house energy scheduling, this paper proposes an energy scheduling algorithm in multiple smart homes. By analyzing features of appliances and demands of users, the periods of users using power and appliances types are classified, and then the dynamic priority is proposed. The energy scheduling algorithm designed on this basis is intended to guarantee the users comfort, decrease the cost of electricity and guarantee the smart grid stability. Finally, the feasibility and effectiveness of the algorithm are verified by simulation.(3) Considering a tradeoff between consumers comfort and energy efficiency, a multi-period joint energy scheduling algorithm(MPJ-ESA) based on prediction of residents energy consumption is proposed, which includes long-period preliminary scheduling, short-period preliminary scheduling, and real-time fine-tuning scheduling. First, by analyzing historical data of energy consumption, preferred usage profile of consumers is inferred, and the dynamic comfort level is presented. Then the paper uses the wavelet neural networks(WNNs) prediction algorithm to predict the operation of the appliances which are classified into appliances with not-schedulable mode and schedulable mode. Based on the energy consumption prediction and dynamic comfort level, home appliances running state are scheduled according to the prediction of renewable energy available amount and real-time pricing(RTP). The simulation results show that scheduling algorithm effectively improves the energy efficiency and enhances user satisfaction with the operation of scheduled appliances and let the consumers comfort and energy efficiency achieve a better tradeoff.