Research On Control Strategy Of Thermostatically Controlled Loads In Microgrid

Demand side response,as a typical smart power technology,provides technical support for microgrid to run independently and flexibly and controllably.Incorporating it into the energy management system to intelligently manage electricity users can effectively regulate and eliminate distributed generation,and promote the efficient use of renewable energy and assist the stable operation of the micro-grid system.The thermostatically control loads(TCLs)have a high ratio of electricity,flexible and controllable characteristics in microgrid,that develop different time scales control strategy based on direct load control is the most direct and effective demand side response technology.This article takes the campus microgrid system as the research object,investigates and analyzes the temperature-controlled load in the system,and establishes the physical model.Based on this,this paper studied the real-time control strategy,improved strategy based on the recently optimized scheduling,the energy allocation strategy of the cluster,and they assist the intelligent operation of the microgrid at different timescales to achieve the goal of promoting distributed energy consumption and improving the economic operation of the microgrid.First of all,consider the preparation of strategic research,select the typical campus building campus micro-grid system,through field visits and sample surveys on the basic situation of the thermostatically control equipment and user habits research,monitoring the actual load of electricity to run the load characteristics analysis,and master the characteristics of the typical building TCLs.Based on the actual monitoring of the power characteristics,combined with the heat exchange theory were discussed to establish the physical model of the fixed frequency and frequency conversion equipment,and combined with the above two points to form a load behavior curve that consider user behavior habits to provide the theoretical foundation for the follow-up control strategy and energy scheduling research.Based on the above preparatory work,this paper studies the real-time control strategy with decentralized temperature control equipment as the main body to improve the distributed photovoltaic capacity as the main goal,taking into account the user comfort and constraints of micro-network contact line fluctuations.Based on the theory of queuing control,this paper presents a control scheme suitable for fixed/inverter frequency equipment,that is,the advanced control strategy based on ultra-short-term prediction.In this method,the virtual hysteresis loop is scrolled optimally to take into account the power difference between the controlled load and the control target in the current and future period of time,avoiding over control as much as possible and realizing the efficient use of the thermal storage performance of the device.The household split air conditioners are selected as the controlled equipment,and the actual microgrid data are used to simulate and verify the effect of this method.In order to provide the optimal target curve for real-time control,this paper studies the optimal scheduling strategy of temperature control load.Starting with the physical model of the equipment,this paper analyzed the differences between the average method and the queuing method in terms of energy transfer and the requirements for mutual transformation between the two methods.In this paper,we use the average method to estimate the transferable energy of temperature-controlled load within a reasonable range of parameters.Based on this,this paper designs an optimization scheduling strategy,constructs an energy scheduling optimization model with setting temperature change and scheduling resource quantity as decision variables,and outputs the best temperature load curve and decision variables after control as the target curve and constraints of real-time control,to guide the real-time temperature control.Considering that the microgrid contains many kinds of TCL groups,based on the single-group energy optimal dispatch model,this paper studies the energy allocation strategy that minimizes the peak-to-valley difference and maximizes the dispelling of distributed energy,each schedulable resource group can be efficiently utilized within user comfort constraints.At the same time,an information gap decision theory(IGDT)is introduced to establish a robust optimization model,which reduces the risk of improper energy allocation due to equipment switching uncertainty.