scholarly journals Large-scale sequential quadratic programming algorithms

1992 ◽  
Author(s):  
S.K. Eldersveld
Acta Numerica ◽  
1995 ◽  
Vol 4 ◽  
pp. 1-51 ◽  
Author(s):  
Paul T. Boggs ◽  
Jon W. Tolle

Since its popularization in the late 1970s, Sequential Quadratic Programming (SQP) has arguably become the most successful method for solving nonlinearly constrained optimization problems. As with most optimization methods, SQP is not a single algorithm, but rather a conceptual method from which numerous specific algorithms have evolved. Backed by a solid theoretical and computational foundation, both commercial and public-domain SQP algorithms have been developed and used to solve a remarkably large set of important practical problems. Recently large-scale versions have been devised and tested with promising results.


2021 ◽  
Author(s):  
Sayed Abdullah Sadat ◽  
mostafa Sahraei-Ardakani

After decades of research, efficient computation of AC Optimal Power Flow (ACOPF) still remains a challenge. ACOPF is a nonlinear nonconvex problem, and operators would need to solve ACOPF for large networks in almost real-time. Sequential Quadratic Programming (SQP) is one of the powerful second-order methods for solving large-scale nonlinear optimization problems and is a suitable approach for solving ACOPF with large-scale real-world transmission networks. However, SQP, in its general form, is still unable to solve large-scale problems within industry time limits. This paper presents a customized Sequential Quadratic Programming (CSQP) algorithm, taking advantage of physical properties of the ACOPF problem and the choice of the best performing ACOPF formulation. The numerical experiments suggest that CSQP outperforms commercial and noncommercial nonlinear solvers and solves test cases within the industry time limits. A wide range of test cases, ranging from 500-bus systems to 30,000-bus systems, are used to verify the test results.


2021 ◽  
Author(s):  
Sayed Abdullah Sadat ◽  
mostafa Sahraei-Ardakani

After decades of research, efficient computation of AC Optimal Power Flow (ACOPF) still remains a challenge. ACOPF is a nonlinear nonconvex problem, and operators would need to solve ACOPF for large networks in almost real-time. Sequential Quadratic Programming (SQP) is one of the powerful second-order methods for solving large-scale nonlinear optimization problems and is a suitable approach for solving ACOPF with large-scale real-world transmission networks. However, SQP, in its general form, is still unable to solve large-scale problems within industry time limits. This paper presents a customized Sequential Quadratic Programming (CSQP) algorithm, taking advantage of physical properties of the ACOPF problem and the choice of the best performing ACOPF formulation. The numerical experiments suggest that CSQP outperforms commercial and noncommercial nonlinear solvers and solves test cases within the industry time limits. A wide range of test cases, ranging from 500-bus systems to 30,000-bus systems, are used to verify the test results.


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