Research And Realization Of Energy Optimized Scheduling For Residential Micro-grid Based On Real-time Pricing

With the construction of smart grid,micro-grids develop rapidly in distribution network acts as an Unique resource.It helps to alleviate the pressure of peak load while developing the efficiency of new energy.In recent years,with the distributed generation(DG),e.g.small scaled wind turbines and photovoltaic panels,installed at the domestic scope,and the development of battery performance,as well as flexible loads’ increasing proportion in household electric appliances,residential micro-grid appear in public view acts as one of the many forms for network.With the schedule’s optimizing of residential micro-grid,the states of the flexible loads and the battery are planed and controled,making the energy allocation comprehensivly optimized for residential micro-grid,which contributes to improving the utilization of new energy and reducing the family electricity cost.The method has significant theoretical value and broad market prospect.From the perspective of user side and based on the generalized demand side resources,this paper proposes an optimization method for residential micro-grid considering users’ experience,based on real-time electricity price mechanism.Firstly,the load resource is classified according to the working pattern and function feature of loads,and the flexible loads’ models are established by linear inequality constraint at the same time.Secondly,in order to satisfy the requirement of users’ comfort and reduce the conflict between optimizd scheduling scheme and the actual energy demand caused by the uncertainty of the user’s energy behavior in the household microgrid,this paper proposes a concept called User Experience Degree(UEO),and the quantitative analysis models of UEO are established based on the classification of flexible loads.Then the optimization model for the residential micro-grid facing the users’ experience is established.The objective function is based on the goal of reducing electricity consumption and promoting new energy consumption.The load experience indexs are taken as constraint items.And an improved genetic algorithm is used to optimize the operation of different types of load and battery.Finally,the energy optimization scheduling model of the residential micro-grid is built in the MATLAB simulation platform.The simulation verifies the effectiveness of the load experience index and the economy and robustness of the model based on the load experience index.The model can provide theoretical support and application reference for the application and popularization of household micro-grid energy management.In the aspect of system development,this paper designs a three-tier intelligent home energy management system,including device sensing layer,interactive process layer and service control layer,and the detailed design is given for each layer.The device sensing layer is used to collect the electrical information and control of the household electrical appliances,and the equipment networking scheme,the data transmission mode and the communication protocol are designed.The interaction process layer is used as the link between the device sensing layer and the service control layer,offering comprehensive communication service.And the platform and database are designed as the core components of the communication.Srvice control layer providing energy management service,through the C/S mode,provide users with energy system monitoring,energy efficiency assessment and energy optimization scheduling and other services.