Power System Loads and Power System Stability / by Yue Zhu.

By:

Zhu, Yue [VerfasserIn]

Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Springer Theses, Recognizing Outstanding Ph.D. ResearchPublisher: Cham : Springer International Publishing, 2020Publisher: Cham : Imprint: Springer, 2020Edition: 1st ed. 2020Description: 1 Online-Ressource(XXVI, 164 p. 109 illus., 87 illus. in color.)ISBN:

9783030377861

Subject(s):

Additional physical formats: 9783030377854 | 9783030377878 | 9783030377885 | Erscheint auch als: 9783030377854 Druck-Ausgabe | Erscheint auch als: 9783030377878 Druck-Ausgabe | Erscheint auch als: 9783030377885 Druck-AusgabeDOI: DOI: 10.1007/978-3-030-37786-1Online resources:

Summary: Introduction -- Power System Load Models and Load Modelling -- Power System Stability Indices -- Probabilistic Assessment and Sensitivity Analysis in Stability Studies -- Load Model Parameter Ranking for Different Types of Power System Stability Studies -- Factors Affecting Load Model Parameter Ranking -- Required Accuracy Level of Critical Load Model Parameters -- Conclusions and Future Work.Summary: This thesis develops a pioneering methodology and a concept for identifying critical loads and load model parameters in large power networks based on their influence on power system stability. The research described in the thesis first develops an automatic load modelling tool (ALMT) that can be used to automatically build load model from actual measured power system data without human intervention and the benefits of the ALMY are explored. Secondly, it develops a pioneering framework based on Morris screening method for ranking power system load model parameters based on their influence on overall power system stability (voltage, frequency, transient and small disturbance stability) considering different load models and loading conditions. Thirdly, a novel probabilistic methodology for determining the accuracy levels of critical load model parameters has been developed. This book will be of interest to students and researchers within the field of electrical engineering, as well as industry professionals.PPN: PPN: 1689109947Package identifier: Produktsigel: ZDB-2-ENE | ZDB-2-SEB | ZDB-2-SXEN

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