Generalized spatio-temporal model for the optimal sizing, operation, and location of energy system assets

Thesis

Future energy systems will contain large amounts of distributed energy resources (DER). In DER-based energy systems asset related to energy demand, supply, transport, storage, conversion, and demand response will be deeply coupled. This thesis develops the Space-Time Energy Vector Flow Networks (STEVFNs; pronounced like the name “Steven”) unified asset model, framework, and tool for the optimal design of DER-based energy systems. This thesis is the first to develop a generalized spatiotemporal asset model that unifies energy demand, energy supply, energy transport, energy storage, energy conversion, and demand response assets. STEVFNs enables energy system design by co-optimizing the sizing, operation, and location of energy system assets. It utilizes modern advancements in convex programming and is the first to enable the optimization of energy system design with rapid scenario assessment. It is demonstrated using a case study of designing an energy system to satisfy Singapore’s hourly electricity and high temperature heating demand using intercontinental solar and wind farms, distributed batteries, HVDC lines, distributed ammonia storage, ammonia transport, and various conversion technologies. STEVFNs is available as an open-source tool on GitHub for the co-optimization, with rapid scenario assessment, of the sizing, operation, and location of energy system assets that can provide energy demand, supply, transport, storage, conversion, and demand response.

Authors: Ahsan, A

• DOI: 10.5287/ora-2z1d60oje
• Type of award: DPhil
• Level of award: Doctoral
• Awarding institution: University of Oxford
• Language: English
• Keywords: energy systems optimization; renewable energy; optimization; systems engineering; system of systems
• Subjects: Nonlinear systems; Mathematical optimization; Energy transition; Renewable energy sources