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Convergence Analysis of a Distributed Gradient Algorithm for Economic Dispatch in Smart Grids

International Journal of Electrical Power and Energy Systems(2022)

The Key Laboratory of Dependable Service Computing in Cyber Physical Society of Education Ministry of China

Cited 12|Views15
Abstract
The increasingly complex modern energy network arouses the need of flexible and dependable approaches to solve the economic dispatch problem (EDP) in the smart grids. Toward this end, this paper develops a fresh distributed algorithm with constant step-size, which aims to schedule the power generation among generators by complying with individual generation capacity limits to satisfy the total load demand at the minimized cost. The convergence of the proposed algorithm is analyzed through utilizing the Lyapunov method and the spectral decomposition technique. When the selected constant step-size is smaller than a specifically provided upper bound, the theoretical analysis demonstrates that the proposed algorithm can linearly achieve the optimal solution of the EDP under the smooth and strongly convex assumption on generation cost functions. In particular, the linear convergence rate of the proposed algorithm is tunable, and a relationship among the linear convergence rate, generation cost functions, network topology, weight matrix and constant step-size is established. The availability of the proposed algorithm is verified through simulation experiments.
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Economic dispatch,Distributed algorithm,Constant step-size,Linear convergence,Smart grids
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要点】:本文提出了一种分布式梯度算法,用于智能电网经济调度问题,通过保持恒定步长,实现发电机之间的功率分配,降低总发电成本,并证明了算法在特定条件下具有线性收敛性。

方法】:采用Lyapunov方法和谱分解技术对算法的收敛性进行了分析,并建立了算法收敛速度与发电成本函数、网络拓扑、权重矩阵和恒定步长之间的关系。

实验】:通过模拟实验验证了所提出算法的有效性,具体数据集名称未提及,但实验结果表明算法在满足条件下能够有效收敛至最优解。