Dual m-convex variable subsets family and extremum analysis for the opf problem

Keyphrases

• Nonconvex 100%
• Convex Subsets 100%
• M-convex 100%
• Optimal Power Flow Problem 66%
• Separation of Variables 66%
• Abstract Convex 66%
• Feasible Domain 66%
• Separated Variables 66%
• Optimization Problem 33%
• Convex Optimization 33%
• Optimal Power Flow 33%
• Local Minima 33%
• Centralized Optimization 33%
• Infimum 33%
• Mapping Function 33%
• Global Optimal Solution 33%
• Convex Objective Function 33%
• IEEE System 33%
• Min-max Principle 33%
• Implicit Function 33%
• Optimal Power Flow Model 33%
• Dual Analysis 33%
• Lagrange Dual Problem 33%
• Nonlinear Equality Constraints 33%
• Karush-Kuhn-Tucker Conditions 33%
• Differential Function 33%
• Explicit Mapping 33%
• Primal-dual Problem 33%
• Convex Analysis 33%
• Power System Network 33%
• Complementary Factors 33%

Mathematics

• Convex Subset 100%
• Feasible Domain 66%
• Dual Problem 66%
• Objective Function 33%
• Min-Max 33%
• Local Minimum 33%
• Infimum 33%
• Karush-Kuhn-Tucker Condition 33%
• Convex Analysis 33%
• Equality Constraint 33%
• Implicit Function 33%
• Minkowski 33%

Engineering

• Optimal Power Flow 100%
• Flow Problem 50%
• Objective Function 25%
• Optimisation Problem 25%
• Power Engineering 25%
• Simulation Result 25%
• Flow Model 25%
• Max 25%
• Local Minimum 25%
• Lagrange 25%
• Equality Constraint 25%
• Infimum 25%
• Implicit Function 25%
• Mapping Function 25%