Filtro morfológico para detecção de correntes geomagneticamente induzidas em sistemas elétricos de potência

Abstract

Geomagnetically induced currents (GICs) are caused by ionized particles from solar flares, which interact with Earth's magnetic field, producing mirror currents in the surface of the planet, which flow through parallel paths, such as railways, communications systems, metal pipes and transmission lines. Typically, these currents are presented as almost continuous low frequency components (below 1 Hz). When these currents interact with the power system it can cause overloading of equipment and transmission lines, causing the shutdown of large parts of the electrical system and therefore disruptions in the power supply. In Brazil, the electric companies are severely fined by regulators when there is an occurrence of an unplanned outage that is not caused by a permanent fault. Protection devices, which are responsible for maintaining the continuity of service, by eliminating transient and permanent short circuits, and act to abnormal loading conditions, are devoid of functions capable the detecting GICs, which impair the useful life some equipment. This paper proposes a morphological filter for application in digital relays, able to identify the occurrence of geomagnetically induced currents in power transmission lines and other equipment in the electrical system, which are monitored by these devices. Such methodology has been implemented and tested in Matlab, processing signals computationally generated by the simulation of a test system in the EMTP-ATP® software. The results obtained confirm the effectiveness of the filter in the detection of GICs in real time for all the analyzed cases. Finally, the proposed methodology can assist electric companies as a possible identification tool of GICs as a cause of unplanned shutdowns subject to fines by regulatory agencies. Thus, through the proposed filter, it is expected to improve the performance of relays to not act improperly by the presence of GICs, as well to assist the electric companies to identify possible causes for unplanned outages.