Affiliation:
1. Master’s Program in Electricity, Salesian Polytechnic University, Quito EC170702, Ecuador
2. Smart Grid Research Group—GIREI (Spanish Acronym), Electrical Engineering Deparment, Salesian Polytechnic University, Quito EC170702, Ecuador
3. Master’s Program in Artificial Intelligence, Valencia International University, 46002 Valencia, Spain
Abstract
This paper analyzes the behavior of an electrical power system when N-1 contingencies occur in the transmission stage, which can be produced by incorrect operation of the protection relays, phenomena of natural origin, or increased loadability, which affect the operation and reliability of the electrical system. The operation output of a transmission line results in the variation of the nominal values of the electrical parameters involved because they disturb the stability of the generation, transmission systems, and the supply of electrical energy to the loads, such as voltages and angles of the nodes and the active and reactive power of the system. The proposed methodology was based on analyzing the different electrical parameters of the power system, quantifying the contingency index in a state of regular operation, and comparing it to operation in contingency N-1, with which the most severe contingency was determined and, therefore, achieved; identifying contingencies that can cause system collapses; improving the contingency index from 23.08555 to 22.9276624 for the L16–19 contingency and to 22.9795235 for the L21–22 contingency, which are the most severe contingencies determined with the proposed methodology. To test the proposed methodology, the IEEE 39 bus-bar test system was considered, and the elements that should be implemented to avoid the vulnerability of the power system to N-1 contingencies were determined.
Funder
Salesian Polytechnic University
GIREI-Smart Grid Research Group
Reference34 articles.
1. Transmission security enhancement under (N-1) contingency conditions with optimal unified power flow controller and renewable energy sources generation;Kavuturu;J. Electr. Eng. Technol.,2020
2. A two-stage constructive heuristic algorithm to handle integer investment variables in transmission network expansion planning;Oliveira;Electr. Power Syst. Res.,2021
3. (2024, April 04). Resumen Ejecutivo PME. Available online: https://www.recursosyenergia.gob.ec/wp-content/uploads/2020/01/1.
4. Transmission Expansion Planning Considering Grid Topology Changes and N-1 Contingencies Criteria;Palacios;Recent Adv. Electr. Eng. Electron. Energy,2021
5. Wang, Y., Chen, L., Zhou, H., Zhou, X., Zheng, Z., Zeng, Q., Jiang, L., and Liang, L. (2021). Flexible transmission network expansion planning based on DQN algorithm. Energies, 14.