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

DOI

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.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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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  - 10.2991/mecs-17.2017.68
ID  - Liu2016/06
ER  -