Research On Energy Optimization Scheduling Method For Micro-grid Based On Demand Side Response

With the rapid economic development,it is difficult for traditional power grids to meet the people’s growing needs for a better life.The ensuing electricity market reform is a challenge.Real-time price(RTP)was born in a completely market-oriented power system.Taking the power plant bidding and clearing price as the basic elements,RTP mainly reflects the balance between supply and demand of each line and node.When a certain line power Tight supply,the price of the line node will rise.RTP updates once an hour,to more accurately reflect the relationship between the cost of electricity and demand for each period.At present,the United States and Western European countries use real-time electricity prices in electricity markets,such as the US PJM market.The main research object of this paper is optical storage joint system and smart home system.The research idea is to supply power to the demand side with photo voltaic power generation or distribution network as the main power source,and to improve system performance by controlling the charge-discharge or flexible load operation time and operating power of the energy storage system.In addition,from the grid perspective,the electricity price mechanism ensure that the demand side participates in the operation of the electricity market and expand the degree power systems of great significance.In this paper,in the electricity market,real-time electricity price is used as the adjustment signal to study the economic optimization of smart home system.According to the different application purposes,the optical storage system and smart home system composed of flexible load and energy storage components are constructed respectively.The research contents are as follows:(1)For the microgrid and smart home systems,the flexible load model,photovoltaic power generation model,energy storage dispatching model,and economic evaluation model are established from the user’s point of view,and will be mainly used in smart homes for optimal dispatch or optical storage microgrid systems.Three kinds of typical load modeling methods are introduced in detail,and on this basis,the flexible load is improved and innovated,laying the foundation for energy management of smart home systems.(2)In view of the intelligent home system,the flexible load and energy storage components of the system are modeled according to the control attributes.Considering the electricity cost of users and perception in the power consumption of the experience,the establishment of economic and intelligent perception Home Furnishing system evaluation model,which is based on user perception evaluation logarithmic function model is adopted to describe the user satisfaction and user’s electricity and grid electricity price relationship the power of users experience to quantify,lay the foundation for intelligent scheduling system Home Furnishing.(3)An economical optimal dispatch method of optical storage system considering energy storage loss is proposed.In order to solve the shortcomings that the traditional household energy storage scheduling method can not quantify the service life of the battery,this paper briefly introduces the method of building a battery life quantification model based on the rain flow counting method.The model is used to calculate the energy storage loss in the system,Based on this,an economical model of optical storage combined system considering energy storage loss is established.The real-time electricity price and load-photo voltaic curve are taken as input,and an improved Particle Swarm Optimization algorithm is used to optimize the household energy storage components.(4)A real-time scheduling model based on fuzzy decision-making is proposed for grid-connected household energy management system with rooftop photo voltaic and household energy storage components.This model improve the robustness of the system under different power supply and demand conditions.It also schedules the system in real time on the basis of meeting users’ inertia electricity.In the process of optimal scheduling,considering the constraints of system operation requirements and battery technical characteristics,the fuzzy control method and the smart bee colony algorithm are used to realize the real-time energy storage scheduling in order to achieve the optimal system life-cycle economy.Finally,Model and different ways to conduct a comprehensive assessment of electricity.Taking into account the traditional fuzzy controller does not have the learning ability,intelligent bee colony algorithm is applied to the controller parameter optimization.Taking the PJM market electricity price in the United States as a reference,the real-time and economy of the model and method are verified by analyzing the influence of intelligent fuzzy scheduling on grid energy flow,battery energy storage,user economic benefits and decision response speed.Since the input of the controller is not related to the prediction,the optimization of optical storage joint optimization does not depend entirely on the accuracy of the prediction information.This method not only overcomes the shortcomings of previous studies in handling uncertainties,but also has the millisecond response speed required by real-time scheduling.(5)Constructed a two-stage scheduling model of smart home system to overcome the load and the impact of randomness and volatility of new energy power generation on the scheduling results,and integrated the battery and home load attribute characteristics.Different from the elastic coefficient model and traditional exponential function modeling method,this paper improves and innovates the load model based on the load state modeling method and the robust model.From the perspective of consumers,considering the characteristics of energy storage and load,this paper proposes a two-phase coordinated operation method of smart home appliances to meet the needs of users’ electricity demand and electricity satisfaction.The smart dispatching of home appliance enhances the ability of the demand side to respond the power supply of the grid,which is beneficial to establish a stable and reliable supply and demand relationship with a certain flexible space between the power grid and the user.This is of great significance to the construction,development and improvement of the demand side response of the smart grid.The method not only effectively reduces the user’s electricity costs,but also retains the user’s positive electricity experience.This is an important reference value for encouraging users to participate in the operation of the smart grid and to promote a healthy supply and demand relationship of the grid source,meanwhile it has positive significance for the implementation of the power grid reform.