Distributed economic optimisation strategies for active distribution networks based on consensus algorithms

Aiming at the problems of increasing renewable energy and distributed power generation, changing power supply demand of distribution network, which is difficult to be adapted by traditional centralized optimization, a distributed economic dispatch strategy based on consensus theory is proposed, which utilizes the consensus algorithm in the multi-intelligent body system to obtain the optimal solution of economic dispatch by reaching the consensus of incremental cost. The algorithm only requires the information exchange of distributed power sources of neighboring nodes, which effectively reduces the amount of computation and communication. Example simulations and analysis verify the effectiveness and feasibility of the method.

Authors

Publication Details

Journal
IET conference proceedings.
Published
2025-03-01
DOI
https://doi.org/10.1049/icp.2025.0404
Citations
1
Primary Topic
Power Systems and Renewable Energy
Type
article
Field-Weighted Citation Impact
0.53
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Distributed economic optimisation strategies for active distribution networks based on consensus algorithms

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IET conference proceedings.
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Distributed economic optimisation strategies for active distribution networks based on consensus algorithms

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article en
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Abstract

Aiming at the problems of increasing renewable energy and distributed power generation, changing power supply demand of distribution network, which is difficult to be adapted by traditional centralized optimization, a distributed economic dispatch strategy based on consensus theory is proposed, which utilizes the consensus algorithm in the multi-intelligent body system to obtain the optimal solution of economic dispatch by reaching the consensus of incremental cost. The algorithm only requires the information exchange of distributed power sources of neighboring nodes, which effectively reduces the amount of computation and communication. Example simulations and analysis verify the effectiveness and feasibility of the method.

IET conference proceedings.Vol. 2024(33)
Openalex Percentile: Top 33%
Power Systems and Renewable Energy
0.53
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