Distributed Continuous-Time Algorithm for Economic Dispatch Problem Over Switching Communication Topology

This brief mainly studies the economic dispatch problem (EDP) in smart grid. The purpose of this problem is to minimize the total power generation cost under the conditions of balance between supply and demand and power generation capacity constraints. A distributed continuous-time solver is propose...

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Bibliographic Details
Published in:IEEE transactions on circuits and systems. II, Express briefs Vol. 68; no. 6; pp. 2002 - 2006
Main Authors: Yan, Jiaojiao, Cao, Jinde, Cao, Yichao
Format: Journal Article
Language:English
Published: New York IEEE 01.06.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
distributed algorithm
Economic dispatch
Electric power generation
Generators
gradient measurement noise
initialization-free
Network topologies
Network topology
Noise measurement
Power dispatch
Power generation
Privacy
privacy-guaranteed
sign of relative state
Smart grid
Smart grids
Supply & demand
Switches
Switching
Topology
ISSN:1549-7747, 1558-3791
Online Access:Get full text
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Summary:This brief mainly studies the economic dispatch problem (EDP) in smart grid. The purpose of this problem is to minimize the total power generation cost under the conditions of balance between supply and demand and power generation capacity constraints. A distributed continuous-time solver is proposed, which only requires the sign of relative dual variable information between neighbors, which ensures the privacy of the generators. In addition, the algorithm does not require initialization and allows online changes of network topology, load, etc. It is theoretically proved that the algorithm achieve the optimal scheduling of smart grid over undirected switching graphs under certain conditions. In the presence of gradient measurement noise, the variation form of the algorithm which converges in the mean square sense is given. Finally, the simulation example illustrates the validness of the algorithm.
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ISSN:1549-7747
1558-3791
DOI:10.1109/TCSII.2020.3041504