Thesis

Model-based optimisation approaches for system energy performance improvement and evaluation

Creator
Rights statement
Awarding institution
  • University of Strathclyde
Date of award
  • 2018
Thesis identifier
  • T14987
Person Identifier (Local)
  • 201679437
Qualification Level
Qualification Name
Department, School or Faculty
Abstract
  • The aim of this PhD study is to provide model-based optimisation approaches for system energy performance improvement and evaluation, and such approaches can solve many energy performance related problems, for example, they are able to optimise conveyor belt system energy performance, avoid ramp rate violation problem in the periodic implementation of dynamic economic dispatch solutions, reduce the number of voltage sensors in photovoltaic (PV) fault diagnosis, improve PV maximum power generation through rearranging PV modules, and also measure and verify energy savings.;For this purpose, three objectives are set in this study: i) To summarise existing model-based optimisation approaches for energy system modelling; ii) To apply obtained modelling methodologies in energy performance optimisation; and iii) To apply obtained modelling methodologies in energy performance evaluation. In order to achieve these objectives, the relevant theoretical preparations on model-based optimisation approaches for energy modelling are developed and then applied in these practical energy problems.;This thesis presents my contributions on modelling methodologies for energy performance optimisation, applications of these modelling methods in industrial energy systems, power generation dispatch, PV array fault diagnosis, and PV array power generation maximisation through rearrangement. Mathematical models are derived for energy system performance evaluation, optimal control models are introduced to minimise measurement and verification cost, and physical modelling and data regression modelling methodologies are also applied in practical measurement and verification projects on air conditioner intelligent switch control and heat pump water heaters. Weakness of these obtained results are analysed, and future work is presented too.
Advisor / supervisor
  • Yue, Hong
  • Lo, Kwok L.
Resource Type
Note
  • PhD by publication, publications listed but not included in the electronic version.
DOI
Date Created
  • 2018
Former identifier
  • 9912634493202996

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