Optimal Power Flow through Artificial Intelligence Techniques

Context: The integration of optimization methods into the various processes carried out by an electric power system seeking energy efficiency have led to satisfying results in reduction consumption as well terms technical losses, security increase and reliability.
 Objective: purpose this article is identify a method offering best outcome for flow distribution with 10 nodes at 13.2 kV.
 Methodology: voltage profiles are presented 10-node using Newton Raphson method. Afterward, optimized genetic ant colony algorithms.
 Results: Their implementation determined that sum potential differences lines notably reduced algorithm. However, code takes less time run has lower number iterations.
 Conclusions: most efficient achieved algorithm since evolution population shows better levels comparison algorithm.
 Financing: Universidad Francisco José de Caldas Colciencias