Impact of Dynamic Response on Generator Rotor Angle of an Island Generating Plant in the Nigerian Grid Network
Keywords:
Artificial Neural Network; Electrical Engineering; Electrical Power Transmission; Generator Transient Stability; Power Flow AnalysisAbstract
This study investigated the impact of varying load demand and dynamic response on the generator rotor angle in the Nigerian grid network. Data spanning 7 years (2015 to 2022), including generator, transformer, line, cable, busway, energy flow, and single-line diagram information, were collected from Shiroro Hydroelectric Power Station, Transmission Company of Nigeria (TCN), Mando and Kaduna Electricity Distribution Company (KAEDCO). Transient stability analysis was conducted using MATLAB 2020a, focusing on a 10-second window after disturbances. Results from power flow analysis showed high transformer loading, notably GWAGWADA at 124.7% and undervoltage issues in several buses, including Bus 847 (93.94 V) and Bus 1306 (84.06 V). The lowest undervoltage value was 84.06 V while the highest was 94.96 V (Bus758). The highest rotor angle deviation occurred during ADDL3- DROPL3 events, with a value of 9.785 degrees at 7.5 seconds. Compared with the IEEE 14 Bus system, which showed 3.907 degrees under similar conditions, the Shiroro Generator had a 5.878-degrees stability advantage. Artificial Neural Network (ANN) modelling of Shiroro Generator Units 2-4 was based on initial operating conditions. The ANN demonstrated satisfactory training, with regression values exceeding 0.9 and best validation performances of 64.12 and 1261.19 at early iterations. This study underscored the need for targeted interventions to enhance the transient stability of the Nigerian grid.
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