Browsing by Author "Ncwane, Siyanda"

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    Power System Transient Stability Analysis Considering Load And Wind Power Generation Variability
    (2023) Ncwane, Siyanda; Folly, Komla
    This research investigated the transient stability of a power system that integrated wind power generators (WPGs) by considering the variability of the system load and power they produced. The power produced by the WPGs was modelled using wind speed, while the variability of the power system load and wind speed was modelled using distribution functions. Power system transient stability was investigated using the deterministic and probabilistic methods. The deterministic method was used to investigate the power system transient stability based on 9 scenarios consisting of low, moderate, and peak system loading and wind power generation conditions. The probabilistic method was also used to investigate power system transient stability using scenarios consisting of low, moderate, and peak system loading conditions. During each of the three system loading conditions, the variable power produced by the WPGs was modelled using 5000 samples that were randomly sampled using Monte-Carlo Simulations. It was found that selecting distribution functions based on their fit alone did not ensure that they modelled the load and wind speed range. Their data range modelling ability ensured that they synthesised the low and high load and wind speed values. It was also found through power system simulations that the transient stability was negatively impacted when the power system's net-load reduced because of increased wind power generation penetration levels. These findings highlight that distribution functions should not be selected based only on their fit to load and wind speed data. In addition to a good fit, they should also be assessed to determine whether they synthesise the data range. The research findings also highlight that power system transient stability should be investigated using scenarios in which the power produced by WPGs is high, during periods when the system's netload is low