Multi-objective Optimization of Current Limiting Scheme Considering Constraint Conditions

The multi-objective optimization of current limiting scheme for power system is a complex, nonconvex and nonlinear problem and it is more complex when considering constraint conditions. Aiming to minimize total investments and short-circuit capacity margin under constraint conditions, a multi-objective optimization model of current limiting scheme based on the fast and elitist non-dominated sorting in genetic algorithms is presented. In order to increase the iterative rate, penalty coefficient is changed from zero to the maximum during the iterative process. Moreover, the influence on impedance matrix caused by common current limiting measure is analyzed, and the sensitivity relation between current limiting measure and node self-impedance is proposed. The conditions when the algorithm is used in multi-objective optimization of current limiting scheme are discussed. Then, case studies performed on IEEE 39-node network indicate the effectiveness of the proposed model and method in simulation results.