Optimal Scheduling Of Intelligent Building Load Based On Cloud Computing

Recently,with the development of smart grid technology,distributed power generation technology has become more and more widely used,and smart homes have also developed rapidly.The research on smart grid demand response mainly focuses on users such as large and medium-sized buildings and electric vehicle charging stations,and there are few studies on residential users.Therefore,in the cloud computing environment,this paper starts from the user side and takes into account the needs of the power grid side,and studies the optimization problem of building residential power consumption scheduling.The main research contents are as follows.First,the cloud computing platform is introduced,and the application of the cloud computing platform in the power system is analyzed.Building users are divided into four categories according to their electricity consumption habits and equipment operating characteristics,and household electrical loads are classified into uncontrollable loads,interruptible loads,and transferable loads.Secondly,considering the time-of-use electricity price information,consider the three electricity consumption targets of the user.The optimization objectives are to minimize user dissatisfaction,minimize electricity costs and minimize carbon emissions,and establish models for the three optimization objectives respectively.This article introduces Pareto theory,gives the mathematical description of multi-objective optimization problem and the definition of non-dominated solutions and non-dominated solution sets.Moreover,a solution method based on population distributed parallel genetic algorithm(PDPGA)is proposed.The computing task is distributed to multiple sub-node computers in the local area network to execute in parallel.Finally,this paper takes the electricity consumption of an intelligent user in summer as an example,and establishes and simulates the model in Matlab environment.Through comparative analysis,the multi-objective optimization strategy proposed in this paper can effectively achieve the user's power saving and comfort goals and reduce carbon emissions without affecting the user's electricity experience.At the same time,PDPGA optimization method can make full use of the computer resources of the cloud computing platform,effectively improve the quality of the solution and reduce the optimization calculation time.In addition,it enables residents to participate in demand response and assists in maintaining the stable operation of the power grid.It reflects the green and safe characteristics of smart buildings and the flexible and interactive characteristics of smart grids.