Analysis of Voltage Collapse in the Nigeria 30 Bus 330kv Power Network
Journal Title: IOSR Journals (IOSR Journal of Electrical and Electronics Engineering) - Year 2018, Vol 13, Issue 4
Abstract
In this paper, a novel approach to voltage collapse analysis using a probabilistic predictor-detector that relies on a conditioned probabilistic Quadratic Line Voltage Stability Index coined the q-LVSI and a moving average filter coined pq-LVSI for deductive analysis of power system network state. The proposed technique uses simple rules for logical analysis such as ratio-sum-of-thresholds, mean-value analysis and confidence conditioning to detect and estimate the presence of a collapsing signal from a sequence of several qLVSI estimates and for several simulation runs. A moving average filter consisting of long-term and short-term predictions is used to filter and enhance the predictions from the resulting q-LVSI values prior to probabilistic logical analysis. The technique is applied to some interconnected buses of the Nigeria power system network in order to determine the interconnected bus sequence(s) that are most likely to collapse. Simulations are performed in the MATLAB language and the results indicate that the Shiroro-Kaduna bus sequence has a higher tendency to collapse earlier when compared to the others. The results also show that the moving average filter long predictions will timely predict the interconnected power system line with the most likelihood of a collapse when there is a differential in the lead and lag parameters.
Authors and Affiliations
Dikio Idoniboyeobu, Sepiribo Lucky Braide, Alexander Ogacheko Idachaba
Keywords
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- EP ID EP388966
- DOI 10.9790/1676-1304034250.
- Views 154
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