Modelling of Distributed Energy Components and Optimization of Energy Vector Dispatch within Smart Energy Systems
| dc.contributor.author | Kong, Qing | |
| dc.date.accessioned | 2019-03-11T17:13:14Z | |
| dc.date.available | 2019-03-11T17:13:14Z | |
| dc.date.issued | 2019-03-11 | |
| dc.date.submitted | 2019-03-05 | |
| dc.description.abstract | The smart energy system concept provides an integrated framework for the adoption of renewable energy resources and novel energy technologies, such as distributed battery energy storage systems and electric vehicles. In this effort, large-scale transition towards smart energy systems can significantly reduce the environmental emissions of energy production, while leveraging the compatible operation of numerous distributed grid components to improve upon the energy utility, reliability, and flexibility of existing power grids. Most importantly, transitioning from fossil fuels to renewable energy resources provides environmental benefits within both the building and transportation sectors, which must adapt to address both increasing pressure from international climate change-related policy-making, as well as to meet the increasing power demands of future generations. In the case of building operation, the transition towards future energy systems consequently result in the adoption of decentralized energy networks as well as various distributed energy generation, conversion, and storage technologies. As such, there is significant potential for existing systems to adopt more economic and efficient operating strategies, which may manifest in novel operational modes such as demand-response programs, islanded operation, and optimized energy vector dispatch within local systems. Furthermore, new planning and design considerations can provide economic, environmental, and energy efficiency benefits. While these potential benefits have been justified in existing literature, there is still a strong research need to quantify the impacts of optimal building operation within these criteria, under a smart energy system context. Meanwhile, the transportation sector may benefit from the smart energy network concept by leveraging electric mobility technologies and by transitioning vehicle charging demand onto the grid’s electricity network. In this transition, the emissions associated with fossil fuel consumption are displaced by grid-generated electricity, much of which may be derived from zero-emission resources in systems containing high renewable generation capacities. While small electric vehicle fleets have currently been successfully integrated into the grid, higher market penetration rates of electric vehicles demand significantly more charging infrastructure. In consideration of the consequences of various electric vehicle charging modes resulting from large-scale mobility electrification, there is a gap in the literature for the planning and design of charging infrastructure for facilitating interactions between electric vehicle fleets and future smart energy network systems. Within the work presented in this thesis, quantitative analysis has been presented for the potential for optimal building operation between complementary commercial and residential building types. From this, the economic and environmental benefits of applying the principles of smart energy systems within mixed residential and commercial hubs have been evaluated at reductions of 61.2% and 1.29%, respectively, under the context of an Ontario, Canada case study. Furthermore, reduced installation of local energy storage systems and consumption of grid-derived electricity were reduced by 6.7% and 13.8%, respectively, in comparison against base case scenarios in which buildings were operated independent of the proposed microgrid configuration. Meanwhile, the investigative work for the role of charging infrastructure in electric vehicle integration within smart energy systems provided insight into the power flow characteristics required to facilitate advanced electric vehicle charging modes. Most importantly, the work demonstrated limitations to the controlled/smart charging and the vehicle-to-grid charging modes imposed by charging port availability, electric vehicle plug-in durations, and maximum power flow characteristics. These results have highlighted the need for charging infrastructure to emulate the availability and fast response characteristics of stationary energy storage systems for successful vehicle-to-grid implementation, as well as the need for maximum power flow limitations for charging infrastructure to be well above the current level 2 standard for home- and workplace-charging. | en |
| dc.identifier.uri | http://hdl.handle.net/10012/14491 | |
| dc.language.iso | en | en |
| dc.pending | false | |
| dc.publisher | University of Waterloo | en |
| dc.subject | smart energy network | en |
| dc.subject | energy hub | en |
| dc.subject | electric vehicles | en |
| dc.subject | vehicle-to-grid | en |
| dc.subject | building energy modelling | en |
| dc.title | Modelling of Distributed Energy Components and Optimization of Energy Vector Dispatch within Smart Energy Systems | en |
| dc.type | Master Thesis | en |
| uws-etd.degree | Master of Applied Science | en |
| uws-etd.degree.department | Chemical Engineering | en |
| uws-etd.degree.discipline | Chemical Engineering | en |
| uws-etd.degree.grantor | University of Waterloo | en |
| uws.contributor.advisor | Fowler, Michael | |
| uws.contributor.affiliation1 | Faculty of Engineering | en |
| uws.peerReviewStatus | Unreviewed | en |
| uws.published.city | Waterloo | en |
| uws.published.country | Canada | en |
| uws.published.province | Ontario | en |
| uws.scholarLevel | Graduate | en |
| uws.typeOfResource | Text | en |