Distributed Consensus Based Algorithm for Economic Dispatch in a Microgrid

Economic dispatch problem (EDP) is a fundamental optimization problem of power systems. With the penetration of renewable energy sources in microgrids, this paper proposes a distributed algorithm based on consensus theory to solve the EDP with a quadratic cost function. The method takes advantage of...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on smart grid Vol. 10; no. 4; pp. 3630 - 3640
Main Authors: Wang, Rui, Li, Qiqiang, Zhang, Bingying, Wang, Luhao
Format: Journal Article
Language:English
Published: Piscataway IEEE 01.07.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Communication networks
Computer simulation
consensus algorithm
Convergence
Cost function
distributed algorithm
Distributed algorithms
Distributed generation
Economic dispatch problem
Eigenvalues
Eigenvalues and eigenfunctions
Electric power grids
Feedback
Generators
Graph theory
microgrid
Microgrids
multi-agent system
Optimization
Perturbation theory
Power dispatch
Renewable energy sources
Upper bounds
ISSN:1949-3053, 1949-3061
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Economic dispatch problem (EDP) is a fundamental optimization problem of power systems. With the penetration of renewable energy sources in microgrids, this paper proposes a distributed algorithm based on consensus theory to solve the EDP with a quadratic cost function. The method takes advantage of the fact that incremental costs need to be equal for all buses at optimal output power values. Thus, the incremental cost of each bus is selected as a consensus variable and the local mismatch between total demand and generation is assigned as a feedback variable to meet demand constraints. Unlike the existing related works, the feedback gains for the feedback variables are different and time-varying. Using multi-parameter perturbation theory and graph theory, the convergence of the algorithm is proved. Furthermore, the upper bounds of the feedback gains are given theoretically, and we obtain that the algorithm converges to the optimal solution at a rate governed by the second largest eigenvalue of the system matrix. Meanwhile, the algorithm is a fully distributed algorithm without a leader or a virtual command node. The simulation results illustrate the effectiveness of the algorithm even though there is a demand change and generator damage. Some simulation results intuitively illustrate how the convergence speed changes with the feedback gains.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1949-3053
1949-3061
DOI:10.1109/TSG.2018.2833108