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Optimized Settings of Droop Parameters Using Stochastic Load Modeling for Effective DC Microgrids Operation

机译:使用随机负载建模优化下垂参数设置,以有效进行直流微电网运行

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Droop control is a widely used technique for load sharing in dc microgrids (MGs). However, it has an inherent limitation that leads to voltage deviations at the dc bus. More importantly, its current-sharing performance is degraded due to voltage drops across transmission line impedances. Depending on the amount of these voltage drops over the dc bus, droop control leads to different current-sharing errors and dc bus voltage degradations. Therefore, MG topology and loading conditions (LCs) have a considerable effect on current-sharing accuracy and voltage regulation. In this paper, an optimization procedure accounting all necessary information is introduced to find optimal droop parameters for the droop mechanism. First, a proper optimization problem is defined with required constraints and a cost function formulated as a summation of the current-sharing errors and the voltage degradations occurring at various LCs. Then, an optimization tool named as particle swarm is implemented to converge a satisfactory solution. During the computations, the cost impact of the current-sharing error at each LC is weighted based on the probability of occurrence of that LC, which is obtained from the stochastic load model for the considered MG. The effectiveness of the optimal droop parameters is verified through a simulation performed on MATLAB/Simulink and a dc MG test bench is prototyped for experimental validation.
机译:下垂控制是直流微电网(MG)中负载分配的一种广泛使用的技术。但是,它有一个固有的局限性,会导致直流总线上的电压偏差。更重要的是,由于传输线阻抗两端的电压降,其电流共享性能会下降。根据直流母线上的这些电压降的大小,下垂控制会导致不同的电流共享误差和直流母线电压下降。因此,MG拓扑和负载条件(LC)对均流精度和电压调节有很大影响。在本文中,介绍了一种考虑所有必要信息的优化程序,以找到下垂机制的最佳下垂参数。首先,用所需的约束条件定义一个适当的优化问题,并将成本函数表述为电流共享误差和各种LC处发生的电压降级的总和。然后,实施了一个名为“粒子群”的优化工具以收敛令人满意的解决方案。在计算过程中,将根据从考虑的MG的随机负载模型获得的LC发生概率,对每个LC处的均流误差的成本影响进行加权。通过在MATLAB / Simulink上进行的仿真验证了最佳下垂参数的有效性,并为实验验证设计了一个直流MG测试台原型。

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