A hierarchical algorithm for large-scale system optimization problems with duality gaps

2005 ◽  
pp. 662-671 ◽  
Author(s):  
P. Tatjewski
Keyword(s):  
Large Scale ◽  
Optimization Problems ◽  
System Optimization ◽  
Large Scale System ◽  
Hierarchical Algorithm ◽  
Duality Gaps

The Study on Electric Power System Based on Swarm Intelligence

2012 ◽  
Vol 442 ◽  
pp. 424-429 ◽  
Author(s):  
Ze Sheng Xu ◽  
Zhi Feng Ma ◽  
Xin Wen Di ◽  
Tao Luo ◽  
Hong Yun Guo ◽  
...  
Keyword(s):  
Power System ◽  
Swarm Intelligence ◽  
Large Scale ◽  
Optimization Problems ◽  
System Optimization ◽  
Electric Power System ◽  
Central Research ◽  
Centralized Control ◽  
Mathematical Basis ◽  
Selection Of

In this paper, we introduce the swarm intelligence computation and its applications in power system. Because swarm intelligence does not need any precondition of centralized control and global model, it is very suitable to solve large scale power system nonlinear optimization problems which are hard to establish effective formalized models and difficult to be solved by traditional methods. In order to apply swarm intelligence better in power system, we propose two central research directions in the future: (1) The mathematical basis of swarm intelligence is unsubstantial and it lacks profound and pervasive theoretical analysis, so we must analysis its convergence and selection of parameters, especially the parameter selection of large scale power system optimization problems. (2) Because swarm intelligence is internally parallel, we should realize it based on the parallel computation theory. This work will also be helpful for the real-time need of power system.

Computationally Efficient Hybrid Method for Transmission Network Expansion Planning

2017 ◽  
Vol 18 (2) ◽  
Author(s):  
Ashu Verma ◽  
Soumya Das ◽  
P. R. Bijwe
Keyword(s):  
Power System ◽  
Large Scale ◽  
Optimization Problems ◽  
Hybrid Approach ◽  
Solution Process ◽  
System Optimization ◽  
Mixed Integer ◽  
Transmission Network ◽  
Network Expansion ◽  
Expansion Planning

Abstract Transmission network expansion planning (TNEP) is an important and computationally very demanding problem in power system. Many computational approaches have been proposed to handle TNEP in the past. The problem is mixed integer, large scale and its complexity increases exponentially with the size of the system. Metaheuristic techniques have gained a lot of importance in last few years to solve the power system optimization problems, due to their ability to handle complex optimization functions and constraints. Many of them have been successfully applied for TNEP. The biggest challenge in these techniques is the requirement of large computational efforts. This paper uses a two-stage solution process to solve the TNEP problems. The first stage uses compensation based method to generate a quick, suboptimal solution. The valuable information contained in this solution is used to generate a set of heuristics aimed at drastically reducing the number of population for fitness evaluations required in the 2nd stage with application of metaheuristic method. The resulting hybrid approach produces very good quality solutions very efficiently. Results for 24 bus and 93 bus test systems have been obtained with the proposed method to ascertain the potential of the method in comparison to earlier approaches.

Large-scale system optimization

1986 ◽  
Vol 10 (2) ◽  
pp. 123-128 ◽  
Author(s):  
G.M. Ostrovsky ◽  
Ye.M. Mikhailova ◽  
T.A. Berezhinsky
Keyword(s):  
Large Scale ◽  
System Optimization ◽  
Large Scale System

Large Scale Plant Optimization Problems

1988 ◽  
Author(s):  
Paul Cronin ◽  
Harry Woerde ◽  
Rob Vasbinder
Keyword(s):  
Large Scale ◽  
Optimization Problems ◽  
Plant Optimization

Large Scale System Defense

2008 ◽  
Author(s):  
Steven M. Bellovin ◽  
Salvatore J. Stolfo ◽  
Angelos D. Keromytis
Keyword(s):  
Large Scale ◽  
Large Scale System

scholarly journals A Practical Algorithm for General Large Scale Nonlinear Optimization Problems

1999 ◽  
Vol 9 (3) ◽  
pp. 755-778 ◽  
Author(s):  
Paul T. Boggs ◽  
Anthony J. Kearsley ◽  
Jon W. Tolle
Keyword(s):  
Nonlinear Optimization ◽  
Large Scale ◽  
Optimization Problems ◽  
Practical Algorithm
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