Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Electrical and Electronic Engineering | en_US |
| dc.contributor.advisor | Bu, Siqi (EEE) | en_US |
| dc.creator | Wang, Zhaoyuan | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/13705 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | en_US |
| dc.rights | All rights reserved | en_US |
| dc.title | Uncertainty quantification for frequency stability of renewable penetrated power systems | en_US |
| dcterms.abstract | In recent years, with the wide utilization of renewable energies, conventional power systems are undergoing the transformation into renewable penetrated power systems. However, the high penetration of renewable energy generations (RPGs) greatly threatens the frequency stability of modern power systems since the integration of RPGs introduces uncertainties into systems and decreases system inertia. Therefore, uncertainty quantification (UQ) methods for frequency stability of renewable penetrated power systems are urgently needed. | en_US |
| dcterms.abstract | In this thesis, firstly, methods for probabilistic frequency stability analysis (PESA) considering the dynamics of RPGs with different control strategies are proposed. Based on the system frequency response (SFR) model, the frequency response affected by different control strategies of RPGs is analyzed, which reveals the necessity of considering the dynamics of RPGs in PESA. Moreover, a multi-interval sensitivity (MIS) method is proposed to reduce the simulation time of PESA, thereby improving efficiency. And then, a multi-element low-rank approximation (MELRA) method is proposed to conduct uncertainty propagation analysis (UPA) while considering the frequency response characteristics, thereby increasing the accuracy of PESA. Additionally, based on the Gaussian mixture model (GMM), the limitation of moment-based UPA methods is discussed by investigating the relationship between moments and probability distributions of uncertainties. | en_US |
| dcterms.abstract | Secondly, to tackle the heterogeneity and interactions of wind power generations (WPGs), i.e., wake effects (WEs) in wind farms (WFs), an analytical WE model suitable for PFSA is proposed, which considers multiple factors, including terrain, wind direction, and time delay of wind flow, and thus can reflect the WEs in WFs more realistically. Moreover, a multiple output Gaussian process regression (MOGPR) for PFSA considering the WEs in WFs is proposed, where the implicit relationship among system frequency response and area-level frequency responses is utilized so that the accuracy of PFSA is improved. Furthermore, the impact of terrain, wind direction, and WF layout on PFSA is investigated based on the proposed WE model and MOGPR. | en_US |
| dcterms.abstract | Thirdly, to quantify the frequency response trajectory affected by uncertainties more efficiently, a generic multi-output polynomial chaos expansion (GMPCE) based on multi-task Elastic Net is proposed. GMPCE has multiple outputs, the sparse structure, and polynomial chaos bases suitable for independent uncertainties with arbitrary probability distributions. Thus, it is suitable for large-scale uncertainties, avoids the curse of dimensionality, and can quantify the system frequency response at each time point simultaneously. Also, a generic transformation method based on independent component analysis (ICA) is proposed, which can transform the uncertainties with complicated correlations into independent ones and thus broadens the application of proposed GMPCE. | en_US |
| dcterms.abstract | Finally, to tackle slow timescale characterizations of uncertainties (STCUs) and fast timescale characterizations of uncertainties (FTCUs) simultaneously, the FTCU transformation method based on Karhunen-Loeve expansion (KLE) is proposed, which enables STCUs and FTCUs to be formulated by probability distribution methods in a unified form. Moreover, a scalable polynomial chaos expansion (PCE) method is proposed to improve the efficiency of UPA of power system frequency stability considering STCUs and FTCUs. And then, a comprehensive UQ framework based on the proposed FTCU transformation method and scalable PCE is proposed, where frequency stability indices, frequency response trajectories, and the sensitivity between stability indices and uncertainties are quantified. These results will provide constructive guidance for system operators to ensure the frequency stability of renewable penetrated power systems. | en_US |
| dcterms.extent | xxi, 158 pages : color illustrations | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2025 | en_US |
| dcterms.educationalLevel | Ph.D. | en_US |
| dcterms.educationalLevel | All Doctorate | en_US |
| dcterms.LCSH | Renewable energy sources | en_US |
| dcterms.LCSH | Electric power system stability | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.accessRights | open access | en_US |
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