Study On Optimal Strategies For User-Side Intelligent Power Consumption Considering Electric Vehicles

As the crucial component of smart grid,smart power consumption technology realizes flexible interaction between the grid and users,and completely changes the traditional single power consumption mode on the user side.With the popularization of electric vehicles in the whole society,their charging and discharging behaviors are uncertain in time and space,and different users have great differences in electrical characteristics after considering the access of electric vehicles.Therefore,in this paper,the study on intelligent energy optimization strategy considering electric vehicles is carried out under different user environment.For residential users,the intelligent energy optimization problem considering electric vehicle user types is studied.Firstly,an intelligent energy management framework is proposed for residential users,and the working characteristics of power adjustable equipment,time adjustable equipment and intelligent power generation equipment are analyzed successively.Then,an intelligent energy optimization management model aiming at minimizing the total cost of residential power consumption is constructed.Finally,according to the different travel characteristics of electric vehicles,residents are divided into early going and late returning type,normal working type and night shift type.Through the case study of different user types,the economy and effectiveness of the residential intelligent energy optimization strategy are analyzed.For commercial users,the intelligent energy optimization problem considering the uncertainty of electric vehicle travel is studied.Firstly,the intelligent energy management architecture for commercial users is proposed,and the working characteristics of power equipment,auxiliary equipment,energy storage equipment and load equipment are analyzed.Then,the paper introduces the visual comfort index based on indoor lighting level,and constructs a multi-objective intelligent energy optimization management model to minimize the total energy cost of commercial users and maximize the comfort of indoor office staff.Finally,on the basis of the uncertainty of starting power,arrival time and departure time of electric vehicles,the economy and effectiveness of commercial intelligent energy optimization strategy are analyzed through the case study of a commercial comprehensive energy office building.For industrial users,the intelligent energy optimization problem based on shift system is studied.Firstly,an intelligent energy management framework with demand response capability was proposed for industrial users.The framework consists of multiple components,including industrial processes modeled by the state task network method,thermostatically controlled loads like the heating,ventilation and air conditioning system with chilled water storage,renewable generation like photovoltaic arrays and electric vehicles.These components were firstly modeled and the factors that affect several components at the same time,e.g.the number of workers,are considered.Then,an intelligent energy management model aiming at minimizing the total power consumption cost of industrial users is constructed.Finally,based on the fixed arrival time,departure time and uncertain starting power of shift electric vehicles,a general tire manufacturing facility was investigated as the case study to analyze the economy and effectiveness of industrial intelligent energy optimization strategy.