| The system is not only able to make full use of natural power generation and reduce carbon emissions,but can also use energy storage to smooth out power fluctuations,improve the aggregation capacity of distributed energy sources,reduce the impact of renewable energy on the grid,and improve the smoothness of power supply.However,the optimal allocation of energy storage capacity is one of the keys to solving the microgrid problem.Therefore,this paper investigates how to optimise the allocation of energy storage to maximise economic benefits based on the microgrid of wind power generation + energy storage.To begin,this paper studied the structure and functions of each component of the scenic storage microgrid system,established mathematical models and analysed the power output characteristics of each according to the working principles of photovoltaic and wind turbine;studied the classification and characteristics of energy storage technology,and finally chose lithium iron phosphate as the energy storage device and built mathematical models according to its power output characteristics.On this basis,this paper constructs a two-layer optimization model of energy storage system capacity configuration and the operating economic efficiency of the whole system,in which the upper layer considers the lowest total cost of configuring the energy storage system based on the scenery active output and load characteristics,and the lower layer takes maximizing the operating economic efficiency as the optimization objective based on the optimal configuration of the energy storage system,with the upper and lower layers constrained by each other under different constraints,and proposes to use the self-balancing rate,load shortage rate and renewable energy utilization rate as the core evaluation index;according to the changes of PV,wind turbine and load,the autonomous operation method is proposed to configure energy storage capacity and regulate the economic operation of energy storage to balance the micro grid system.Then,the background and principle of the grey wolf algorithm are introduced,and the mathematical model of the improved algorithm is constructed,and the step-by-step flow of its algorithm is proposed;to verify the superiority and feasibility of the improved grey wolf algorithm,five benchmark test functions are selected for simulation testing,and the results show that the improved grey wolf algorithm has the best performance.The upper and lower layer models are solved using the improved grey wolf algorithm.Finally,this article takes the wind resources data of a microgrid in a certain area as the research object,selects a typical day in a residential area,and analyzes the original data of the case study.Based on the analysis of the operating status of the typical day,problems exist in the absence of installed energy storage devices.By comparing the difference between the traditional energy storage capacity configuration and the improved algorithm energy storage configuration,it is demonstrated that the improved grey wolf algorithm for energy storage optimization improves the overall system’s economic efficiency and energy utilization rate,and increases electricity sales revenue,proving the correctness of the energy storage capacity configuration model and algorithm proposed in this article.Based on the above conclusions,an energy storage system was configured and experimentally verified for the new energy generation and microgrid experimental platform at our university,and the experimental results showed that the algorithm can achieve energy storage capacity optimization configuration and improve the economic efficiency of microgrid operation. |
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