Application of time-series prediction and optimisation schemes in power systems analysis and dynamic state estimation

Hadi Ariakia

Research output: ThesisDoctoral Thesis

51 Downloads (Pure)

Abstract

In the thesis relations between time series forecasting schemes and dynamic state estimation methods are investigated. It is shown in the thesis that dynamic state estimation problems can be considered as time series problems. Different time series forecasting model using nonlinear autoregressive network with exogenous inputs (NARX) and long short-term memory (LSTM) schemes for dynamic state estimation purposes are developed and these models are validated in the IEEE-39 bus systems.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • The University of Western Australia
Supervisors/Advisors
  • Fernando, Tyrone, Supervisor
  • Emami, Kianoush, Supervisor
  • Iu, Ho Ching, Supervisor
Thesis sponsors
Award date29 Sept 2020
DOIs
Publication statusUnpublished - 2020

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