BEGIN:VCALENDAR VERSION:2.0 PRODID:-//132.216.98.100//NONSGML kigkonsult.se iCalcreator 2.20.4// BEGIN:VEVENT UID:20260523T080802EDT-8245LUSFA7@132.216.98.100 DTSTAMP:20260523T120802Z DESCRIPTION:Abstract\n\nThe global energy situation is shifting towards ren ewable energy sources (RESs) for sustainability and reduced fossil fuel re liance. This shift brings uncertainties from volatile RESs and new forms o f loads (e.g.\, electric vehicles)\, challenging power system operation an d security. Addressing these challenges\, this thesis aims to leverage a s urrogate modeling method\, namely the polynomial chaos expansion method\, to systematically investigate and mitigate the impacts of uncertainties on power system transfer capability and economic dispatch (ED). The overarch ing goal is to offer vital guidance for ensuring and enhancing the securit y of power systems while maximizing the utilization of transmission assets and economic benefits\, considering the high uncertainty level of current and future power grids.\n\nThe thesis first studies the impacts of uncert ainties brought by volatile RESs\, random loads\, and unforeseen equipment outages on power system available transfer capability (ATC)\, a crucial i ndex in power system security analysis. By exploiting polynomial chaos the ory and moment-based methods\, a data-driven sparse polynomial chaos expan sion (DDSPCE) method is developed for probabilistic total transfer capabil ity (PTTC) and ATC assessment. Notably\, without requiring pre-assumed pro bability distributions of random inputs\, the proposed DDSPCE directly exp loits data for estimating the probabilistic characteristics of PTTC (e.g.\ , mean\, variance\, probability density function (PDF)\, and cumulative di stribution function (CDF))\, based on which the ATC with a certain confide nce level can be readily calculated. An integrated sparse framework furthe r enhances its computational efficiency and accuracy. Simulations on the m odified IEEE 118-bus system and the modified PEGASE 1354-bus system valida te the DDSPCE method’s efficacy in PTTC evaluation. Furthermore\, the resu lts underscore the significance of incorporating discrete uncertainties\, like equipment outages\, in both PTTC and ATC assessments.\n\nThe thesis t hen delves into the impacts of uncertainties\, especially from wind power\ , on ED\, a critical aspect of the power system daily operation. A DDSPCE- based surrogate modeling method is developed to estimate the probabilistic characteristics of ED solutions\, including their mean\, variance\, and d istribution functions. The developed method can handle extensive random in puts without their predefined probability distributions. Extensive simulat ion results on an integrated electricity and gas system (IEGS) using real- life wind power data validate the efficiency and effectiveness of the prop osed method in quantifying the impacts of uncertainties on the ED solution s\, even when the ED solutions are multimodal. These results highlight the DDSPCE method’s efficacy and efficiency in addressing general and complex scenarios.\n\nAfter investigating the impacts of uncertainties on power s ystem static security and ED\, the thesis focus turns to mitigating these impacts. To this end\, this thesis conducts a global sensitivity analysis to allocate the dominant random inputs to assist in designing the uncertai nty-control measures. Particularly\, different PCE-based models are develo ped and compared for global sensitivity analysis within the transfer capab ility enhancement and ED. Leveraging the insights from the sensitivity inf ormation\, uncertainty control strategies (e.g.\, by utilizing energy stor age systems) can be designed\, thereby mitigating the impacts of uncertain ties. These findings offer invaluable direction for uncertainty management and control design in real-world power system operations.\n DTSTART:20231201T180000Z DTEND:20231201T180000Z LOCATION:MD 267\, Macdonald Engineering Building\, CA\, QC\, Montreal\, H3A 0C3\, 817 rue Sherbrooke Ouest SUMMARY:PhD defence of Xiaoting Wang – Uncertainty Quantification and Contr ol in Power System Security and Operation Via Data-Driven Polynomial Chaos Expansion Based Methods URL:/ece/channels/event/phd-defence-xiaoting-wang-unce rtainty-quantification-and-control-power-system-security-and-operation-353 152 END:VEVENT END:VCALENDAR