Power System Transient Stability Analysis Considering Load And Wind Power Generation Variability

dc.contributor.advisorFolly, Komla
dc.contributor.authorNcwane, Siyanda
dc.date.accessioned2024-05-30T09:34:57Z
dc.date.available2024-05-30T09:34:57Z
dc.date.issued2023
dc.date.updated2024-05-28T08:35:27Z
dc.description.abstractThis 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
dc.identifier.apacitationNcwane, S. (2023). <i>Power System Transient Stability Analysis Considering Load And Wind Power Generation Variability</i>. (). ,Faculty of Engineering and the Built Environment ,Department of Electrical Engineering. Retrieved from http://hdl.handle.net/11427/39746en_ZA
dc.identifier.chicagocitationNcwane, Siyanda. <i>"Power System Transient Stability Analysis Considering Load And Wind Power Generation Variability."</i> ., ,Faculty of Engineering and the Built Environment ,Department of Electrical Engineering, 2023. http://hdl.handle.net/11427/39746en_ZA
dc.identifier.citationNcwane, S. 2023. Power System Transient Stability Analysis Considering Load And Wind Power Generation Variability. . ,Faculty of Engineering and the Built Environment ,Department of Electrical Engineering. http://hdl.handle.net/11427/39746en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Ncwane, Siyanda AB - 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 DA - 2023 DB - OpenUCT DP - University of Cape Town KW - Engineering LK - https://open.uct.ac.za PY - 2023 T1 - Power System Transient Stability Analysis Considering Load And Wind Power Generation Variability TI - Power System Transient Stability Analysis Considering Load And Wind Power Generation Variability UR - http://hdl.handle.net/11427/39746 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/39746
dc.identifier.vancouvercitationNcwane S. Power System Transient Stability Analysis Considering Load And Wind Power Generation Variability. []. ,Faculty of Engineering and the Built Environment ,Department of Electrical Engineering, 2023 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/39746en_ZA
dc.language.rfc3066eng
dc.publisher.departmentDepartment of Electrical Engineering
dc.publisher.facultyFaculty of Engineering and the Built Environment
dc.subjectEngineering
dc.titlePower System Transient Stability Analysis Considering Load And Wind Power Generation Variability
dc.typeThesis / Dissertation
dc.type.qualificationlevelMasters
dc.type.qualificationlevelMSc
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