Research On Household Electricity Strategy And Demand Response Of Smart Residential Grid In Intelligent Electricity Environment

As an essential segment of electricity generation,transmission,distribution,transformation and consumption,intelligent electricity usage is the key to intelligent service of power grid.Through automatic control,advance measurement infrastructure,high-speed communication and other technologies,the intelligent electricity realizes real-time data collection,rapid market response and real-time interaction between the power grid and users’ energy flow and information flow,which has provided the foundation f the research on optimal scheduling of household electricity and demand response strategy of smart residential grid.In order to optimize the household electricity strategy,an optimal scheduling strategy for home energy management based on time-of-use price and real-time control of battery is proposed.Firstly,the frame of home intelligent electricity system is introduced.Meanwhile,according to the operating characteristics of the battery and the household load,the working model of the battery and the dispatchable loads is established.Secondly,taking the working states of the dispatchable loads and battery as the constraints,the optimal scheduling model of home energy management is built,while considering the objectives of minimizing the electricity consumption cost of household users and optimizing the net flatness of load curve,Then,with the battery dynamic control method,an optimal scheduling strategy for home energy management based on time-of-use price and real-time control of battery is proposed.This scheduling strategy takes into account the regulation effect of the time-of-use price and the real-time state of charge for the battery on the charging and discharging behaviors of the battery,which is helpful to reduce the electricity consumption cost of the household users and ensure the safe operation of the battery.Finally,the binary particle swarm optimization algorithm is used to solve the model.The case results verify the effectiveness and superiority of the proposed scheduling model and strategy.With the deepening of the marketing electricity side reform,there are multiple power retailers in the electricity market who provide electricity to power users through price competition.Therefore,the cooperative game,evolutionary game and Stackelberg game are introduced into the demand response problem,and a demand response strategy considering residential users’ load shifting and multi-level games is proposed for smart residential grid with multiple power retailers in this paper.Firstly,a load shifting scheme was designed for users to introduce incentive-based demand response into demand response process.Secondly,considering that users have the right to select power retailers freely and power retailers can achieve mutual benefits through cooperation while competing with each other,the selection process of the users was formulated as an evolutionary game,and the service competition of power retailers was formulated as a cooperative game.Then,considering the interactive process between the power retailers and the users,the process maximizing benefits of the retailers and the users respectively was formulated as a Stackelberg game.Finally,the equilibrium strategy,including the electricity price issued by retailers and the optimal selection strategy selected by users of the multi-level game,was solved with a parallel-distributed game model.Case study results show that the model and strategy proposed in this paper are feasible and effective,providing theoretical reference for demand response decision of smart residential grid with multiple power retailers.