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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…mehr

Produktbeschreibung
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.
Autorenporträt
Dr Yue Zhu gained his BEng in electrical engineering and PhD from the University of Manchester in 2015 and 2018 respectively. He has authored or co-authored 3 journal papers and 5 conference papers; one of these conference papers was commended at the Mediterranean Conference on Power Generation, Transmission Distribution and Energy Conversion in 2018. Dr Zhu is now working at the State Grid Shanghai Energy Interconnection Research Institute.