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Convergence speed analysis and optimization for distributed control of virtual power plant

机译:虚拟电厂分布式控制的收敛速度分析与优化

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Distributed control can be applied to a virtual power plant (VPP) to allocate electrical power among distributed generators (DGs). By using consensus algorithm and selecting the incremental cost of each DG as the consensus variable, economic dispatch of the VPP can be realized in a distributed manner. Therefore, only local communication among DGs is required and some performance limitations caused by centralized control can be avoided as well. However, the slow convergence speed is of concern in the distributed control. In this paper, mathematical analysis is presented to reveal factors influencing the convergence speed of the consensus algorithm. Specially, a convergence speed optimization method is developed to reduce the iterations, including communication network (CN) topology designing, edge weights optimization, and leader selecting. The performance of the optimization method is demonstrated through several simulation cases.
机译:分布式控制可以应用于虚拟电厂(VPP),以在分布式发电机(DG)之间分配电力。通过使用共识算法并选择每个DG的增量成本作为共识变量,可以以分布式的方式实现VPP的经济调度。因此,只需要DG之间的本地通信,就可以避免由于集中控制而导致的一些性能限制。但是,缓慢的收敛速度是分布式控制中需要考虑的问题。本文通过数学分析来揭示影响共识算法收敛速度的因素。特别是,开发了一种收敛速度优化方法来减少迭代,包括通信网络(CN)拓扑设计,边缘权重优化和领导者选择。通过几个仿真案例证明了优化方法的性能。

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