A Comparative Study of the Analytical Methods of Voltage Stability : A Case Study of Sudan National Grid

Abstract

Voltage instability has become a major concern in many power systems around the world, and it has been recognized that many of the blackouts that have been reported are caused by voltage instability due to gradual voltage collapse. The problem has been aggravated recently because electric power utilities are forced to transmit maximum power through existing networks due to tighter budgets and that additionally, excessive restrictions have been put in place by regulators for environmental reasons, which make extension of current transmission systems more expensive. In this thesis, several techniques for voltage stability analysis are described and applied to the IEEE 14-bus, IEEE 30-bus systems (as a benchmark) and the National Grid of Sudan. The most common methods used in static voltage stability analysis have been considered; these are the L-index, modal analysis, V-Q sensitivity analysis, voltage change index and continuation power flow method in order to detect weak buses and/or areas in the power systems which are likely to cause a voltage collapse or a blackout. The weak buses or areas which are prone to voltage collapses in the IEEE 14-bus, IEEE 30-bus systems and the Sudan National Grid have been identified using computer simulation. The validity of the results has been confirmed through detailed comparison of the results for the five different methods mentioned above. The simulation results obtained from these five different methods lead to similar conclusions in most of the cases with some degree of discrepancy. Comparison of the five methods was discussed and it has been found that the L-index offered the simplest method with minimum computational effort and with good agreement with most of the other methods. It was also found that the Q-V sensitivity method was not able to differentiate between different stability modes, and it could be misleading when applied to a large system having more than one area.