Matute, NelsonFlores, WilfredoLópez Quizhpi, Julio CésarAstudillo Salinas, Darwin FabiánMorquecho, EdgarTorres Contreras, Santiago Patricio2021-01-242021-01-242020978-172817100-50000-0000http://dspace.ucuenca.edu.ec/handle/123456789/35517https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097345869&doi=10.1109%2fISGT-Europe47291.2020.9248778&partnerID=40&md5=6a21956f41b83ffccefca1575c02a380Initial Solutions (IS) are decisive in meta-heuristics based optimization problems since they impact the performance of the optimization process. This research work proposes and compares some random and deterministic algorithms to create initial solutions based on existing expansion planning criteria to solve the AC Transmission Expansion Planning (TEP) problem. The TEP is formulated as a full non-convex optimization problem using the AC network representation. A local version of the Particle Swarm Optimization (LPSO) technique is employed to solve the TEP problem. The Garver 6-bus and IEEE 24-bus test systems are used to evaluate the IS algorithms performance. It is shown that these algorithms have great potential to improve the robustness and computational effort of meta-heuristics.es-ESAC modelElectric power systemsInitial solutionsLeast-effort criterionTransmission expansion planningARTÍCULO DE CONFERENCIA10.1109/ISGT-Europe47291.2020.9248778