A globally convergent primal—dual interior point algorithm for convex programming

1994 ◽  
Vol 64 (1-3) ◽  
pp. 123-147 ◽  
Author(s):  
Renato D. C. Monteiro
Keyword(s):  
Convex Programming ◽  
Interior Point ◽  
Interior Point Algorithm ◽  
Globally Convergent ◽  
Primal Dual

Fast compressed sensing analysis for imaging reconstruction with primal dual interior point algorithm

2020 ◽  
Vol 129 ◽  
pp. 106082
Author(s):  
Lianying Chao ◽  
Jiefei Han ◽  
Lisong Yan ◽  
Liying Sun ◽  
Fan Huang ◽  
...  
Keyword(s):  
Compressed Sensing ◽  
Interior Point ◽  
Interior Point Algorithm ◽  
Imaging Reconstruction ◽  
Primal Dual

Optimal Reactive Power Compensation in Power System Considering SVC

2013 ◽  
Vol 774-776 ◽  
pp. 1873-1876 ◽  
Author(s):  
Zhen Chen ◽  
Chen Liang ◽  
Run Qing Bai ◽  
Chao Ma ◽  
Lei Gao
Keyword(s):  
Mathematical Model ◽  
Interior Point ◽  
Static Load ◽  
Reactive Power ◽  
Northwest China ◽  
Reactive Power Compensation ◽  
Interior Point Algorithm ◽  
Primal Dual ◽  
The Mathematical Model ◽  
Load Margin

This paper introduces a method for optimal reactive power compensation considering SVC. Static load margin of each node is calculated and then sorted to determine the location of reactive power compensation. To know the optimal compensating capacity, the mathematical model of fuzzy multi-objective is established, and it can be solved by the primal-dual interior point algorithm. The proposed method is applied to a grid of Northwest China with satisfactory results.

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