Optimized Scheduling And Pricing Strategy For Aggregated Thermostatically Controlled Loads Considering User Comfort

Due to the increasing demand for electricity from society and the economy,and the development of renewable energy generation,demand-side management of smart grids is becoming increasingly important.Temperature control load is a type of energy storage equipment that has been proven to provide demand-side adjustment services through appropriate control,such as common air-conditioner,heat pumps,refrigerators,water heaters,etc.Although the energy storage capacity of a single temperature control load is relatively small.However,the polymerized temperature-controlled load has a large energy storage capacity,which can be regarded as a high-power energy storage battery.The purpose of this study is to reduce the deviation and cost of temperature-controlled loads participating in the grid frequency adjustment service,to ensure the user's power comfort,and to achieve the coordinated optimization of frequency adjustment deviation,auxiliary service costs,and user comfort.Regulating services provides a feasible solution to establish a quantitative index system for the power grid and users to evaluate the cost of participating in auxiliary services.Firstly,the thermal dynamic model of temperature-controlled load is introduced,including Monte Carlo model and second-order differential equation model.Two basic control strategies for polymerizing air-conditioning load are compared and analyzed.The characteristics of air-conditioning load and the advantages and disadvantages of basic control strategy are explained;And then introduced a layered energy management system based on the ubiquitous power IoT integrated energy system.Secondly,a strategy that comprehensively considers human comfort and tracking accuracy is proposed.In order to reduce the deviation and cost of temperature control load participating in the grid frequency adjustment service,ensure the user's power comfort,and realize the frequency adjustment deviation,auxiliary service cost and user Collaborative optimization of comfort,and the effect of grouped control of temperature-controlled loads on user comfort and tracking accuracy was studied.Considering that the focus of the power generation side and the demand side are different,three different control optimization schemes are proposed for reference,and a reasonablereference scheme is set for different reference objects.The temperature setpoint optimization algorithm based on Active-target Particle Swarm Optimization(APSO)was used for optimization,and the optimal comfort level and the best tracking accuracy were obtained.A compromise was considered considering user comfort and Control optimization model for tracking accuracy.Finally,based on the three control strategies mentioned in the previous chapter,a pricing model was considered,and a cost model of user dissatisfaction was established.At the same time,users and Automatic Generation Control(AGC)were considered to participate in the adjustment to reduce the cost of power companies.Power companies can match supply and demand through user-side load adjustments.This article has established the cost of multiple generator sets and the load adjustment costs of the users.In addition,a more convenient quadratic fitting Predicted Percentage Dissatisfied(PPD)is used to express the discomfort characteristics of the user.Due to the different adjustment capabilities of the user,the adjustment price of the user's load adjustment is also different.