Study On The Optimal Control Of Electric Boiler Heat Storage System Based On MPC Method

The construction industry is one of the main sources of energy consumption and carbon emissions in China.Strengthening energy saving and emission reduction measures in the construction sector will significantly reduce carbon emissions and promote China to achieve the goal of carbon peaking and carbon neutrality.In the building energy consumption,the energy consumption in the building operation stage is twice as much as that in the building construction stage,among which the building operation stage of traditional coal-fired and gas-fired central heating in the north consumes a lot of energy and has high carbon emissions.With the introduction of the carbon neutrality target,the north has started to realize clean energy heating through the implementation of "coal to electricity" and coal to heat pumps.At the present stage,the state vigorously promotes the use of renewable energy generation instead of thermal power generation,which makes the use of electric boiler heat storage system more and more widespread in the north,so it is very important to carry out research on the optimal control of electric boiler heat storage system for energy saving and emission reduction.The research on the optimal operation of electric boiler heat storage system was initially carried out by scholars of electric power-related majors,and most of the research mainly considered the power supply capacity on the distribution side,and the research on the model of user heat load demand and the model of electric boiler heat storage system was relatively simplified,and the description of heat load and system dynamics was not accurate enough.Therefore,it is necessary to conduct more in-depth research on electric boiler heat storage system,and build more refined and accurate models and optimization algorithms to make the electric boiler heat storage system operate at lower cost.The purpose of this paper is to propose a model predictive control(MPC)-based optimal operation strategy for electric boiler heat storage systems,so that the system can be operated at the lowest cost while ensuring the comfort of users.The research mainly includes the construction of MPC simulation platform and case study analysis,and the simulation platform mainly includes reference trajectory,dynamic prediction model,and optimization controller module.In this study,the reference trajectory is set as the user demand heat load for a period of time in the future.In the study,the user-side heat load demand predicted by using the historical data of user heat load using time series analysis method is used as the reference trajectory for MPC control,which is used to guide the difference between the actual output and the desired output of the system.The prediction model,as the core part of MPC control,is used to predict the future behavior of the system and guide the controller’s decision making.The study uses the energy consumption simulation software TRNSYS to build a dynamic prediction model of the electric boiler heat storage system,and the model constructed by TRNSYS is close to the physical model and can describe the dynamic changes of the system more accurately.The optimization algorithm of the optimization controller in the study is selected as genetic algorithm,and finally the TRNSYS model is connected to the genetic algorithm that comes with MATLAB through the external call interface Type155 of TRNSYS to realize the construction of the simulation platform.The case study part is to take a high-class hotel as an example,using the time series analysis prediction model to predict the time series of user heat load demand in the future period as a reference trajectory,and the model of electric boiler heat storage system established by TRNSYS software as the system dynamic prediction model,using the simulation platform to optimize this simulation.The optimization results of the simulation platform are compared with the operation results of the design working mode.Compared with the design working condition,the electric boiler heat storage system can save about 23% of the operation cost for one week of operation under the MPC control strategy,and the power consumption of the electric boiler heat storage system is reduced in the afternoon peak,which helps to cut the peaks and fill the valleys on the distribution network side.In addition,the increase of electricity consumption at night is also beneficial to improve the utilization rate of clean energy generation such as wind power.In this paper,a simulation platform based on Model Predictive Control(MPC)for electric boiler thermal storage system is built,and the simulation platform is used to simulate a high-class hotel building as an example.The results show that the MPC control strategy can not only reduce the operating cost of the system,but also help to reduce the peak and fill the valley on the distribution grid side and improve the utilization rate of renewable energy generation.