Research On The Energy Management Strategy Of Photovoltaic-Storage DC Microgrid System

In recent years,distributed generation,represented by wind and photovoltaic renewable energy,is developing vigorously.This kind of intermittent distributed power supply is connected in the form of microgrid,which can effectively improve the utilization rate of renewable energy sources,and can also support the large grid to supply power flexibly.However,due to the volatility and uncertainty of distributed energy sources,controlling the energy flow in microgrid is challenging,and the reliability and economy of operation are not guaranteed.Therefore,in order to achieve the cost-effective and safe operation of a microgrid,this paper focuses on the photovoltaic power prediction and energy management for the photovoltaic-storage microgrid system.Firstly,photovoltaic and hybrid energy storage units are studied respectively according to the structure of photovoltaic-storage microgrid.In photovoltaic cells,In photovoltaic cell,focus on analysis of climatic factors and the correlation of photovoltaic power.In the energy storage unit,considering the limitations of a single energy storage device,the hybrid energy storage system is constituted by the coordination and cooperation of ultracapacitors and accumulators,and its working characteristics and degradation cost are analyzed.At the same time,the energy flow between each unit of the system is described.Secondly,in terms of photovoltaic power prediction,the genetic algorithm is proposed to optimize the weight and threshold of the neural network model.The prediction model established through the selected relevant amount,the optimized model compared with the model,using three weather sunny,cloudy,rainy examples verified,and according to the error index evaluation of two kinds of model prediction accuracy.The optimized model improves the prediction accuracy and provides a good data basis for the optimal scheduling of microgrid.Then,the energy scheduling problem of optical storage microgrid is studied from the perspective of economic operation of microgrid.According to the advantages of the energy storage components in the hybrid energy storage system,a hybrid energy storage hierarchical optimization strategy combining the idea of multi-time scale hierarchical scheduling and model predictive control theory is proposed.The upper long time scale model takes the lowest operating cost as the optimization objective,and comprehensively considers the peak-valley difference of electricity price and the life of energy storage element.The battery energy storage unit with large power and slow response speed is used to adjust the peak-valley characteristics of photovoltaic power on the long time scale.In order to minimize the deviation from the reference value of the upper dispatching plan,the lower short-time scale model uses the super-capacitor with fast response speed to adjust the fluctuation characteristics of photovoltaic output power on the short time scale.Finally,in the simulation part,the effectiveness of the proposed model and strategy is proved by comparing with the single-layer energy scheduling scheme and analyzing the calculation examples of different electricity price schemes and different prediction parameters.The simulation results show that the layered cooperation of storage battery and ultracapacitors can optimize the state of charge of the energy storage system,and provide an optimal control scheme for the economic dispatching of microgrid.