Identification of coherent groups of generators for out-of-step protection : a case study of Sri Lankan power system

Abstract

Power systems are operated with tight stability margins, such that when a power system experiences a fault or disturbance, the generator rotors may subject to severe oscillations. These oscillations in the generator rotor angle translate into severe power flow oscillations (or power swings) across the system. Power swings can be categorized as stable swings, for which, the system itself can recover and the unstable swings, where system cannot recover itself, but need some remedial action to gain the stability. During power swings, magnitudes of voltages and currents can oscillate beyond their nominal values across the system. An unstable power swing condition can be identified as an Out-of-Step (OOS) event, which is a condition of angular instability or a state of Asynchronous Operation (AO) of generators. Out-of-Step event cannot be tolerable for a prolonged period of time due to its negative impact on power system equipment and its integrity. These oscillations might trigger distance relays and other backup relays removing key transmission elements leading widespread outages and even blackouts. Controlled islanding of the system is one of the solutions to isolate the systems operating asynchronously during and OOS event. For this purpose, identification of generator coherency would come in handy in this process of control islanding, where the generators with similar rotor dynamic characteristics swing together forming separate clusters in transmission network. Coherency analysis is fundamental for wide area measurement-based control in a power system. Also, it is important that the coherency identification to become online based, as coherent groups may differ in response to various event and operating conditions. This thesis proposes a generalized methodology to identify coherent groups of generators as an online decision-making approach based on real time data. This methodology will identify generators which tend to swing similarly at the initiation of OOS events based on real time rotor angle trajectories and aid to identify possible clusters within transmission network. Simulation results of OOS events on 2 area 4 generator system, IEEE 16 generator 68 bus system and Sri Lankan power system were used for coherency identification using the proposed methodology. The case study considers the identification of the occurrence of OOS event in Sri Lankan power system, as well as the formation of coherent groups of generators. Results indicate that the proposed methodology correctly identifies the number of groups and assigns each generator to its corresponding group. Further, it suggests the requirement of Wide Area Measurement System (WAMS) to ensure wide area information availability in order to facilitate the real time decision making.