An overview of distributed economic dispatch of microgrids: advances and challenges

The integration of renewable energy provides a fresh boost for the development of power systems. Economic dispatch (ED) is necessary to achieve optimal power allocation while meeting practical physical constraints and ensuring economic benefits and production safety. Traditional centralized ED metho...

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Bibliographic Details
Published in:Systems science & control engineering Vol. 13; no. 1
Main Authors: Sun, Lei, An, Wenjing, Chen, Yangkai, Zhao, Peifeng, Ding, Derui
Format: Journal Article
Language:English
Published: Taylor & Francis Group 31.12.2025
Subjects:
distributed economic dispatch
distributed optimization algorithm
engineering constraints
Microgrids
privacy-preserving mechanisms
ISSN:2164-2583, 2164-2583
Online Access:Get full text
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Summary:The integration of renewable energy provides a fresh boost for the development of power systems. Economic dispatch (ED) is necessary to achieve optimal power allocation while meeting practical physical constraints and ensuring economic benefits and production safety. Traditional centralized ED methods are not always able to meet the ED demands of microgrids that mostly use distributed power sources. Consequently, distributed ED (i.e. DED) schemes are receiving more research attention because of their high reliability, scalability and uniformity in communication and computation loads. The latest theoretical advancements in DED algorithms are reviewed in this paper to give a comprehensive review. The survey focuses on design considerations of DED optimization algorithms for both discrete-time and continuous-time implementation scenarios and cutting-edge engineering applications by incorporating practical operational constraints or privacy-preserving mechanisms. Furthermore, deep insights are provided to reveal the intrinsic mechanism and exceptional performance of various DED algorithms. A brief outline of prospective research directions is provided based on the reviewed literature, which includes DED issues with non-convex and multi-objective functions, fast DED algorithms and DED algorithms without initialization.
ISSN:2164-2583
2164-2583
DOI:10.1080/21642583.2025.2467077