Research On Optimization Of Hybrid Renewable Energy System For Demand Side Management Based On Model Predictive Control

In recent years,with the rapid development of social and economic development,the rapid growth of electricity demand has forced the government to accelerate the transformation of the electricity market.In order to ensure the stable operation of the power grid and improve the operation efficiency of the power market,various regulatory policy mechanisms are constantly applied in modern energy management methods.As the smallest unit in user side management,the ordinary family has a small power load,but because of its large quantity,it is imperative to conduct energy management on the user side.Model predictive control as a kind of feedback control,through the rolling optimization method of sampling to data on the model,and then through the feedback compensation model prediction error correction and other disturbances,eliminate the effects of error,to get the optimal control scheme.In this paper,the problem of user side energy management based on model predictive control is studied,and other control methods are compared to demonstrate the superiority of control.Firstly,this paper discusses the research status of hybrid energy system management made a summary,and on the user side energy management are reviewed,from the Angle of the two kinds of demand response,analysis of the current user side the main method of energy management,at the same time shows the user side the significance of energy management for the long-term development of our country.Secondly,two kinds of modeling methods are introduced in the hybrid energy system,traditional energy flow modeling and distributed switching modeling.Distributed switch modeling is a further improvement in traditional energy flow modeling,which is based on the wind-light-electric hybrid switching system model and the integrated grid switching model with interference.With interference of PV grid switch model is in the wind-light-electric model on deepening,the electricity from the solar power end and user load disturbance,considering the modeling,system modeling closer to the actual situation.Thirdly,three control methods are used to control the three types of models.Through design feedback controller can prove that the hybrid energy system users appear urgent demand,still can be adjusted by itself,to meet user demand,to ensure the safety of power;the optimal control strategy is optimized by using open-loop optimization control for wind-light and electric hybrid switching system,and the optimal control strategy is obtained under the constraint condition.But for the interference of PV grid system,the optimization of open loop control strategy does not guarantee that every moment of optimal objective functions by using a model predictive control,establish a closed-loop rolling optimization control method,the interference of every moment considered in control algorithm,in the case of with interference,ensure the stability of the user load power and the optimal performance.Finally,the feasibility and superiority of the three control methods are verified by simulation experiment,and the real experimental platform based on LABVIEW technology is built,which can run in practical situations.By observing the control strategy of monitoring page and output,the advantages of model prediction control in user side energy management are further demonstrated.