A Finite-Time Distributed Optimization Algorithm for Economic Dispatch in Smart 
Grids

Mao, S.; Dong, Z.; Schultz, Paul; Tang, Y.; Meng, K.; Dong, Z. Y.; Qian, F.

doi:10.1109/TSMC.2019.2931846

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A Finite-Time Distributed Optimization Algorithm for Economic Dispatch in Smart Grids

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Mao, S.
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Dong, Z.
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Schultz, Paul
Potsdam Institute for Climate Impact Research;

Tang, Y.
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Meng, K.
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Dong, Z. Y.
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Qian, F.
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Citation

Mao, S., Dong, Z., Schultz, P., Tang, Y., Meng, K., Dong, Z. Y., Qian, F. (2021): A Finite-Time Distributed Optimization Algorithm for Economic Dispatch in Smart Grids. - IEEE Transactions on Systems, Man, and Cybernetics: Systems, 51, 4, 2068-2079.
https://doi.org/10.1109/TSMC.2019.2931846

Cite as: https://publications.pik-potsdam.de/pubman/item/item_23366

Abstract

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.