Proceedings of the 2017 2nd International Conference on Machinery, Electronics and Control Simulation (MECS 2017)

Multi-objective Optimal Load Distribution Based on Decomposition-Coordination Method of Large Scale Sy

Authors
Kang Liu, Yu Lu, Hai Lu Wang, Feng Jiang
Corresponding Author
Kang Liu
Available Online June 2016.
DOI
https://doi.org/10.2991/mecs-17.2017.68How to use a DOI?
Keywords
large scale systems; decomposition-coordination; multi-objective; load distribution
Abstract
This paper divides a model of complicated system which includes numbers of fossil-fueled power plants into a two-tier structure model with coupled subsystems, using decomposition-coordination method of large scale systems. The method consists of Lagrangian relaxation, sub-gradient algorithm and particle swarm optimization (PSO). First, an optimal load distribution model on economy and pollution is proposed. Second, the model is decomposed via Lagrangian relaxation, and PSO is adopted to obtain the optimal solution of each subsystem. Third, the sub-gradient algorithm is used to update the Lagrangian multiplier to coordinate the coupling relation among subsystems. Finally, through iteration of sub-gradient algorithm and PSO, the simulation example realizes the goal that the power plants can obtain the maximum economic efficiency in the case of the minimum pollutant emissions.
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Volume Title
Proceedings of the 2017 2nd International Conference on Machinery, Electronics and Control Simulation (MECS 2017)
Series
Advances in Engineering Research
Publication Date
June 2016
ISBN
978-94-6252-352-4
ISSN
2352-5401
DOI
https://doi.org/10.2991/mecs-17.2017.68How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Kang Liu
AU  - Yu Lu
AU  - Hai Lu Wang
AU  - Feng Jiang
PY  - 2016/06
DA  - 2016/06
TI  - Multi-objective Optimal Load Distribution Based on Decomposition-Coordination Method of Large Scale Sy
BT  - Proceedings of the 2017 2nd International Conference on Machinery, Electronics and Control Simulation (MECS 2017)
PB  - Atlantis Press
SN  - 2352-5401
UR  - https://doi.org/10.2991/mecs-17.2017.68
DO  - https://doi.org/10.2991/mecs-17.2017.68
ID  - Liu2016/06
ER  -