Whole System Design and Grid Flexibility
Wildfires & Powerline Network Design
The project investigates how the powerline network can be designed to reduce powerline-related wildfire risk. Based on available literature, a specialised software was developed to quantify risk, compare and suggest alternative powerline paths.
Supervisors:
- Prof. Guillermo Rein, Department of Mechanical Engineering
Exploring Emerging Grid Energy Storage: A Techno-Economic Analysis of Sodium-Ion Batteries
To support the UK achieve its net-zero target, Great Britain's electricity grid needs to transition entirely to clean energy sources. This shift increases the need for grid flexibility. As natural gas will no longer provide the required flexibility, new technologies are emerging to fill this gap. One potential solution is sodium-ion batteries, which address cost and sustainability challenges in the lithium-ion battery. With sodium-ion cells nearing commercialisation, this project aims to assess their viability by analysing their technical performance and capital costs through bottom-up modelling, as well as performing financial modelling and valuation for sodium-based grid energy storage.
Supervisors:
- Dr. Jacqueline Edge, Department of Mechanical Engineering
Optimisation of PV and Battery Systems for Cost-Effective Energy Solutions in Commercial Buildings
This thesis presents an optimisation model for solar photovoltaic and battery energy storage systems tailored to commercial buildings. The model comprehensively incorporates relevant factors such as weather conditions, building energy demand, electricity pricing, and the costs, specifications, and degradations of the technologies involved. By analysing these elements, it identifies the optimal types and capacities of PV and battery, and the best operating strategy for electricity export/import and battery charge/discharge. The model uses Mixed-Integer Linear Programming to minimise the 15-year net present cost of ownership, which includes CAPEX, OPEX, maintenance, and replacement costs.
Supervisors:
- Dr. Salvador Acha, Department of Chemical Engineering
Understanding the economic value of renewables hybridised with storage
The weather-dependency of renewable energy sources highlights the need for flexible solutions to manage their variability and ensure economic viability. To address revenue cannibalisation, hybrid energy systems have been developed, where renewable assets like wind and solar are co-located with storage systems. This project aims to identify optimal operations and asset sizing while considering factors such as site location, electricity markets, and available revenue streams. The findings and recommendations could inform policy and investment decisions, ultimately lowering costs and accelerating the transition to zero-carbon electricity.
Supervisors:
- Dr. Iain Staffell, Centre for Environmental Policy
- Dr. Oliver Schmidt, Centre for Environmental Policy
Peer-to-Peer Energy Trading: A Strategic Implementation Framework Formulation
As decentralized energy resources (DER) grow, traditional systems struggle to maintain stability. Regions are becoming more independent by relying on DERs, reducing the need for centralized grids. Peer-to-peer (P2P) energy trading addresses these challenges by allowing small producers to sell electricity directly to users, democratizing energy access and reducing transmission losses. This research will develop a strategic implementation framework for P2P energy trading, analysing key drivers and challenges through primary and secondary research to guide stakeholders in this evolving landscape.
Supervisors:
- Dr. Salvador Acha, Department of Chemical Engineering
Estimating Distributed Solar Photovoltaic Capacity via Demand Profiles: A Macro-Level Approach
Solar PV is now the cheapest way to generate energy on a per Watt basis. Consequently, across the world we are witnessing rapid uptake of this technology. Smaller scale PV systems are typically connected to the distribution grid and are not directly metered by the ESO. If the capacities of these systems are unknown, then their influence on the net energy demand is also uncertain, ultimately leading to a reduction in system efficiency, which can then contribute to a higher energy price. Existing methods to estimate distributed PV capacity on a macro-level use datasets or satellite imagery. This project employs a new approach using demand profile analysis.
Supervisors:
- Dr. Iain Staffell, Centre for Environmental Policy
- Dr. César Quilodránn Casas, Department of Earth Science and Engineering
- Adriana Martins, BloombergNEF
Geospatial Least-Cost Hydrogen Production Modeling: A Case Study of Laos
Laos is on a path to expand its hydropower capacity, which boosts its economy by leveraging its abundant resources. For sustainable growth, advancing the local industry and diversifying beyond electricity exports is necessary. A promising strategy involves producing green hydrogen. An existing model has been used as a baseline and further developed to evaluate Laos' specific hydrogen potential. This model, which employs spatial-temporal data, identifies the least-cost green hydrogen production sites based on renewables, primarily hydropower. The different scenarios will be presented to the Laotian government through a dashboard and at a conference in Laos to gather further feedback.
Supervisors:
- Prof. Adam Hawkes, Department of Chemical Engineering
- Dr. Vignesh Sridharan, Department of Chemical Engineering
GGR Policy Design: The Need for a New UK Net Zero Policy Design Toolkit
Investigating the role of empirical, high-fidelity Greenhouse Gas Removal (GGR) value chain analysis in developing a novel policy decision support tool, to aid in the realisation of economically functioning GGR value chains.
Supervisors:
- Dr. Mark Workman, Energy Futures Lab
- Dr. Aoife Brophy, University of Oxford
Optimal Design and Operation of an Integrated Power and Synthetic Fuel Network with Storage
Anna-Bryndís Zingsheim Rúnudóttir
Decarbonising multi-energy vector systems requires smart modelling approaches given their inherent interdependencies and complexities due to the intermittency of renewable energy resources. The project presents a smart energy (mixed integer linear programming) model to determine the optimal design and operation of an integrated wind, electricity, hydrogen, and synthetic fuel network to decarbonise the Icelandic economy. Iceland represents an ideal case study, given that the relatively simpler task of decarbonising electricity and heat has already been achieved. Only hard-to-abate sectors, including heavy road transport, maritime, and aviation remain.
Supervisors:
- Prof. Nilay Shah, Department of Chemical Engineering
- Dr. Hafþór Ægir Sigurjónsson