Research On Control Strategy Of Photovoltaic DC Microgrid Based On Distributed Hybrid Energy Storage

After entering the 21 st century,when solar energy has been widely used around the world,DC microgrid with photovoltaic power generation as a distributed power source has also entered the stage of rapid development.However,due to the structure of the DC microgrid itself,it is vulnerable to the influence of external environment changes and load power fluctuation,which results in a series of problems such as photovoltaic arrays being unable to achieve maximum power output and energy storage devices unable to work in standard working conditions,endangering the safe and stable operation of the whole system.Therefore,this paper establishes a photovoltaic DC microgrid based on distributed hybrid energy storage.Through the research and design of the MPPT algorithm of photovoltaic array and the control strategy of hybrid energy storage and distributed energy storage in the energy storage system,reducing the external environment change and bring the negative impact of load power fluctuations,realize DC micro grid run stably for a long time.First of all,in terms of the photovoltaic power generation system in the DC microgrid,a simulation model was established by analyzing the power generation principle of photovoltaic cells,and the output characteristic curves of P-V and I-V were obtained.The accuracy of the simulation model was verified by the experimental test circuit of photovoltaic cells,and then the established photovoltaic model was combined in series and parallel.The influence of different illumination on the power output characteristic curve of the photovoltaic array is simulated and analyzed,and the output power has the characteristic of multiple peak values under the condition of partial shading,which provides the theoretical basis for the research and design of MPPT algorithm of the photovoltaic array in the following paper.Secondly,aiming at the problem that the traditional MPPT algorithm and particle swarm optimization algorithm will fall into the local maximum value when searching for the maximum power point in the local shadowing environment,this paper introduces a new intelligent algorithm--lion swarm algorithm.By analyzing the optimization principle of the original lion colony algorithm,it is found that the population initialization is randomly generated,and the selection of lion cubs in the optimization process is blind.In this paper,a corresponding improvement strategy is adopted for these shortcomings,and the maximum power of the photovoltaic system is established.The simulation model is tracked to verify the effectiveness of the proposed improved lion colony algorithm.Then,because of the traditional low pass filter in a hybrid energy storage system power allocation of accuracy is not high and the cut-off frequency fixed issue,in this paper,based on the gray Wolf algorithm improved variational mode decomposition algorithm,hybrid power is decomposed into suitable for the frequency component of different energy storage element and distribution to the corresponding energy storage device to compensate or given.The actual operation data of photovoltaic power station are used to compare and analyze the power allocation effects of the two algorithms,and the superiority of the control strategy proposed in this paper is verified.Finally,when distributed energy storage topology exists in the DC microgrid,it is easy to be influenced by multiple factors,resulting in the difference in charge state between multiple batteries,which will lead to the decrease of charge and discharge depth and affect the service life of the battery.Aiming at the deficiency of traditional droop control in this aspect,a balanced control strategy based on battery SOC is proposed to achieve the balanced distribution of SOC and input and output power among batteries in the system operation process.The simulation model of distributed hybrid energy storage based photovoltaic DC microgrid and the experimental test platform were built to verify the effectiveness of the equilibrium control strategy based on battery SOC proposed in this paper.