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ABSTRACT
This study is aimed at improving the Nigerian National Grid's voltage collapse prediction's dependability, particularly within the framework of sustaining power supply within Nigeria. To achieve this, new voltage stability index (NLSI-1) designed to forecast voltage breakdown in national grid is developed, old 28-bus and current 52-bus 330kV Nigeria National Grid were simulated for comparison and validation of the developed voltage stability index. This research employed a multi-faceted approach. It encompassed an extensive review of existing literature to establish the foundation of voltage stability analysis, followed by the creation of a dedicated voltage stability index. Simulation was carried out on the 28-bus, 330kV Nigeria National Grid using the MATLAB R2015a x64 environment, while an analysis of the 52-bus, 330- kV Power-flow analysis using the Newton-Raphson method was used for the Nigerian National Grid. This methodology enabled acquisition of essential data for calculating voltage stability indices. The findings from the evaluation of the 28-bus, 330kV Nigeria power grid indicate a high level of stability as observed through all predictive indices falling consistently below the critical threshold of 1. In comparison, the 52-bus, 330kV NNG displayed notable susceptibility to voltage collapse in nine key transmission lines. The newly developed line stability index (NLSI) emerged as a reliable predictor of voltage collapse across various network sections. In conclusion, the study underscores the resilience and reliability of the 330kV, 28-bus network, highlighting the importance of continuous monitoring and predictive tools for ensuring the stability and dependability of the Nigerian National Grid. Recommendations stemming from this study suggest the adoption of NLSI for measuring voltage stability in real time targeted at maintaining and upgrading the identified vulnerable transmission lines, thus fortifying the national grid's stability and contributing to Nigeria's economic and social development.
