Strategy Research For Household Electricity Loads Considering Electric Vehicles

Recently,the application of advanced metering infrastructure(AMI) in the smart grid makes the user more closely contacted with it. At the same time, the development of energy internet also has promoted the user a more reasonable energy consumption styles. Currently, the research in consumption and scheduling energy is mainly aimed at large-scale power loads, less in the individual home users scheduling optimization. Thus, for the users, how to make the user voluntarily adjust their energy structure of household under the time-of-use-price(TOUP), how to make them become more reasonably in intelligent electricity and access to economic benefits, has great significance.This article is for the household user, in this article, a optimization strategy is designed based on intelligent power, combined with electric vehicles, analyzed the impact on V2G(Vehicle to Grid) technology in household electricity optimization strategy. Users can reasonably allocate the working time of the electrical equipment to improve the power quality and save the electricity consumption. Firstly, the paper introduces the smart home power system configuration, the energy Internet and the V2 G technology of electric vehicle, and then, the BP neural network is used to predict price information to get the TOUP model within the tolerance scope. When the price is known, household electricity load model and the electric vehicle model are established, with a minimum difference algorithm and dynamic programming algorithm to solve this problem, at last the multi-objective scheduling policy is proved to meet consumption and satisfaction.In the family load modeling, the load is classified, only the load can be controlled is discussed in this paper, the working hours of electricity load can be reasonable optimization according to the adjustable space of the load. Modeling of electric vehicles, the effects of different charging modes of electric vehicles is discussed, also the paper establish the electric vehicles V2 G operation mode based on the family taking into account the daily habits of car users. Finally, this paper builds the whole system model with the scheduling time of equipment, power limitations and use’s habits of electric vehicles as the constraints, with user’s minimum electricity consumption and satisfaction as the multi-objective function. Under the TOUP electricity pricing, we solve the problem with a minimum difference algorithm and dynamic programming algorithm. The article also analyzes the user’s intelligent electricity satisfaction, the simulation results verify the correctness of the established model. This article indicates that with a reasonable choice to optimize scheduling power load, allows users to better smart power.