Middleware-based Energy Resource Management in Smart Grid
| aut.embargo | No | en_NZ |
| aut.filerelease.date | 2019-06-18 | |
| aut.thirdpc.contains | No | en_NZ |
| aut.thirdpc.permission | No | en_NZ |
| aut.thirdpc.removed | No | en_NZ |
| dc.contributor.advisor | Seet, Boon-Chong | |
| dc.contributor.advisor | Lie, Tek Tjing | |
| dc.contributor.author | Zhang, Jianchao | |
| dc.date.accessioned | 2017-05-17T23:33:07Z | |
| dc.date.available | 2017-05-17T23:33:07Z | |
| dc.date.copyright | 2016 | |
| dc.date.created | 2017 | |
| dc.date.issued | 2016 | |
| dc.date.updated | 2017-05-17T03:10:35Z | |
| dc.description.abstract | The Smart Grid incorporates advanced information and communication technologies into the power systems, and is characterised by a high penetration of distributed energy resources. Through virtual power plants (VPPs), prosumers and their distributed energy resources are expected to actively participate in the energy market. The optimal management of the energy resources in VPP requires proper modelling of the energy resources and their scheduling as well as a viable management framework to structure the solutions development for resource management based on the said models. This research aims to investigate and propose novel middleware-based methodologies for effective management of energy resources in VPPs that are constituted of buildings powered by the Smart Grid, as well as on-site solar and wind power generators. The main novel contribution of this research are: 1) a methodology for integration of building information modelling and software-defined networking to render VPP buildings Smart Grid ready; 2) an event-based resource management framework for distributed decision making in VPP; and 3) a two-step game theoretic approach to energy scheduling to address real-time market and energy consumption/production conditions in VPP. To practically evaluate the proposed designs, this research implemented prototypes of their multi-agent systems and conducted performance simulations using real-world energy data. | en_NZ |
| dc.identifier.uri | https://hdl.handle.net/10292/10479 | |
| dc.language.iso | en | en_NZ |
| dc.publisher | Auckland University of Technology | |
| dc.rights.accessrights | OpenAccess | |
| dc.subject | Middleware | en_NZ |
| dc.subject | Smart grid | en_NZ |
| dc.subject | Energy resources | en_NZ |
| dc.subject | Resource management | en_NZ |
| dc.title | Middleware-based Energy Resource Management in Smart Grid | en_NZ |
| dc.type | Thesis | |
| thesis.degree.grantor | Auckland University of Technology | |
| thesis.degree.level | Doctoral Theses | |
| thesis.degree.name | Doctor of Philosophy | en_NZ |