Abstract
The growing need for reliable and cost-effective power generation drives the search for innovative solutions in thermal power plant management. This study aims to enhance power supply stability and reduce fuel costs in three thermal plants within Nigeria's 132kV distribution network using intelligent Steady-State Voltage (SSV) control. By employing advanced control strategies and optimizing operations, significant efficiency and reliability improvements were achieved. The research combined simulation models and real-world data to validate the proposed methodology, demonstrating notable enhancements in power stability and fuel consumption reduction. Nigeria's frequent power outages, disrupting business activities, are mainly due to voltage deviations outside the 0.95 to 1.05 range and high fuel costs for thermal plants. To address these issues, this study proposes an intelligent Static Synchronous Voltage Control (SSVC) strategy. The process starts by characterizing the 132kV distribution network and analyzing the fuel costs of its three thermal plants. Using this data, an SSVC rule base is designed and trained with Artificial Neural Networks (ANN) to stabilize power supply and minimize fuel costs. A SIMULINK model and algorithm were developed to implement the SSVC system. Significant improvements were observed upon implementation. Initially, the weak bus per-unit voltage was 0.930, leading to unstable power supply. With intelligent SSVC, the voltage stabilized at 1.023, enhancing reliability. Fuel costs for plant 1 dropped from ₦3260 to ₦2964, marking a 95.5% reduction compared to conventional methods. This study demonstrates that intelligent SSVC integration significantly improves power supply stability and reduces operational fuel costs in Nigeria's 132kV distribution network.