Adaptive Droop Control Strategy for Load Sharing in Hybrid Micro Grids

Mahmoud Zadehbagheri, A. Ma’arif, M. J. Kiani, Ali Asghar Poorat
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Abstract

Energy management becomes essential when distributed energy sources such as solar, wind, and fuel cell are connected in a micro-grid. In this paper, using a combination of two powerful neural network tools and fuzzy logic, intelligentization, and adaptation of droop control along with voltage and current control as one of the most common methods of decentralized control is done. One of the essential features of this method is its fast performance and the need for telecommunication infrastructure. In this paper, we provide a comprehensive control system that enables proper operation in both upstream and island network modes for both AC and DC microgrids. The proposed method is simulated to evaluate its effectiveness. The proposed structure, by adapting the control system by ANFIS structure, can properly distribute power between distributed products in a brilliant way and without the need for operators and costly telecommunications infrastructure in the face of severe disturbances such as change. The state between the connection and the island or fault occurrence ensures the stability of both the AC and DC parts of the microgrid. The results show the effectiveness of the proposed method.
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混合微电网负荷分担的自适应下垂控制策略
当太阳能、风能和燃料电池等分布式能源连接到微电网中时,能源管理变得至关重要。本文将两种强大的神经网络工具与模糊逻辑相结合,对下垂控制以及电压和电流控制作为分散控制最常用的方法之一进行了智能化和自适应的研究。该方法的一个基本特点是其快速性能和对电信基础设施的需求。在本文中,我们提供了一个全面的控制系统,使交流和直流微电网在上游和岛网模式下都能正常运行。通过仿真验证了该方法的有效性。该结构通过采用ANFIS结构的控制系统,可以在面对变化等严重干扰时,不需要运营商和昂贵的电信基础设施,以一种巧妙的方式在分布式产品之间合理分配电力。连接与孤岛或故障发生之间的状态保证了微电网交流和直流部分的稳定。实验结果表明了该方法的有效性。
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