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A Finite-Time Distributed Optimization Algorithm for Economic Dispatch in Smart Grids
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DOI：10.1109/TSMC.2019.2931846.png)
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Abstract
En 中文
The economic dispatch problem (EDP) is one of the fundamental and important problems in power systems. The objective of EDP is to determine the output generation of generators to minimize the total generation cost under various constraints. In this article, a finite-time consensus-based distributed optimization algorithm is proposed to solve EDP. It is only required that each device in the communication network has access to its own local generation cost function, designed virtual local demand and its neighbors' local optimization variables. The proposed finite-time algorithm can solve EDP, if the gain parameters in the algorithm satisfy some conditions under undirected and connected time-varying graphs. Moreover, the bounded or linear increasing assumption on the gradient and subgradient of objecive functions is relaxed in this algorithm. Examples under several cases are provided to verify the effectiveness of the proposed distributed optimization algorithm.
Keywords:
Convergence
Smart grids
Generators
Cost function
Consensus
distributed optimization algorithm
economic dispatch
finite time
smart grids
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