Research On Energy Management Optimization Strategy For Microgrids With High-Penetration Renewables

In response to the environmental and energy problems caused by the overexploitation of fossil energy,the third industrial revolution,driven by energy change and information technology,is gradually emerging.Smart grid,new energy,and distributed power are the key topics of energy change: smart grid and renewable energy play an important role in the transformation of power system models,and microgrids as the one of that technical fields will provide a solution for the reliable interconnection of renewable energy.Although the integration of renewable energy and controllable loads in microgrid systems helps to improve the efficiency and sustainability of power systems,new energy dispatch is vulnerable to climate and environmental impacts.The randomness and intermittentness will bring challenges to the safe and stable operation of the power system,so research on the management and dispatch of renewable energy is of great significance to promote efficient and coordinated operation of the system.The research object of this article is a micro-grid consisting of photovoltaic generators and wind turbines,which aims to analyze the problems caused by renewable power generation methods.The main work is as follows:Firstly,based on the concept and structure of the microgrid,the mathematical model of each component of the microgrid is introduced,including the principle and mathematical model of renewable energy in the microgrid.The operating characteristics,cost functions,and their limitations of batteries,supercapacitors,and fuel cells have been studied as the focus.Then,an energy scheduling optimization model is established for users who install photovoltaic panels and energy storage batteries.The operation and analysis of the optimization results show that the microgrid energy storage system can not only make up for the discontinuity of renewable energy generation,but also help suppress random interference by power users.Based on the above analysis,the energy management of hybrid energy storage systems is further studied from the perspective of microgrid operation.Hybrid energy storage systems can take advantage of various energy storage methods.This paper uses model predictive control methods to study the optimal strategy of microgrids,and proposes an two-layer energy management algorithm for asynchronous time based on predictive models.The algorithm management algorithm for asynchronous time based on predictive models.The algorithm introduces life-cycle management of energy storage equipment,which helps to enhance system robustness,smooth power fluctuations,and reduce operating costs.The algorithm structure includes two energy scheduling layers with different sampling intervals.The lowerlevel fast model has a shorter sampling time,and the objective function is to maximize the revenue and compensate for the prediction error of renewable energy.The upper-layer slow model has a longer sampling time,and the objective function is to reduce economic costs and the cost of energy storage battery losses.The optimization of the algorithm at different time scales not only provides the optimal control scheme for the economic dispatch of the microgrid,but also analyzes and minimizes the degradation of the energy storage system to improve the service life of the entire energy storage system.Finally,an example with different pricing schemes and parameters is selected for experimental analysis,which proves the effectiveness of the algorithm.The simulation results show that the accumulator,supercapacitor and fuel cell can cooperate to optimize the energy scheduling of microgrid.The algorithm can effectively utilize the energy storage modes,improve the use efficiency of renewable energy in microgrid,and reduce the operation cost while inhibiting the prediction error.