A Monte Carlo method to solve the optimal coordination of directional overcurrent protections considering all the possible fault locations Articles uri icon

publication date

  • November 2024

issue

  • November 2024, art.110974

volume

  • 236

International Standard Serial Number (ISSN)

  • 0378-7796

Electronic International Standard Serial Number (EISSN)

  • 1873-2046

abstract


  • This paper presents a Monte Carlo method to solve the Optimal Coordination of Directional Over-Current Protections (OC-DOCP) considering transient configurations and all the possible Fault Locations (FLs). Previous methods cannot guarantee complete selectivity because they do not consider all the possible FLs. In the proposed method, near-end, and far-end faults are complemented by additional FLs, which are chosen from many randomly generated candidates (Monte Carlo method). Each FL candidate is included in the set of constraints at once to solve an OC-DOCP, whose results are the inputs for a simulator that assesses speed and selectivity indexes considering all the possible FLs. Thus, the FL with the maximum selectivity index is chosen to remain in the set of constraints for the next steps in an iterative procedure that finishes when the specified level of selectivity is reached. From the first iteration, the selectivity index obtained with the proposed method is substantially better than those obtained with the optimal solution of previous methods. The selectivity index is increased successively until it reaches practically 100%, without the need of including all the FLs in the set of constraints. Furthermore, an important improvement in the selectivity index is obtained without a significant worsening of the protection speed. The fact of solving many small optimization problems is an attractive feature of this method because facilitates the possibility of applying parallel computing to this problem.

subjects

  • Industrial Engineering

keywords

  • coordination of protective relays; directional overcurrent protections; monte carlo simulation; fault location; multi-objective optimization.