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Found 34 matching student topics

Displaying 25–34 of 34 results

2032 Brisbane Olympic Games: how can we achieve climate-positive urban objectives?

Brisbane is the first host city to be contractually bound to deliver a climate-positive Olympic Games in 2032 (Queensland Government, 2023). Most of the 8,000-megawatt coal plants are expected to close by 2032, which requires a viable and sustainable transition to renewable energies (Simshauser, 2024).In this project, we investigate how digital energy services and analytics (DESA) can help a sustainable energy transition for a climate-positive 2032 Brisbane Olympic Games.ReferencesQueensland Government. (2023). All Queensland. All in. 2032 procurement strategy. https://www.forgov.qld.gov.au/__data/assets/pdf_file/0011/404030/Q2032-procurement-strategy.pdfSimshauser, P. …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Information Systems
Research centre(s)
Centre for Data Science

Is battery storage overrated? Achieving grid equilibrium through digital energy services and analytics

The share of renewable energy in electricity generation has globally increased to 28.3%, however, an acceleration of the sustainable energy transition is required to limit worldwide temperature rise (REN21, 2022).Energy storage offers various benefits, such as balancing the mismatch between electricity supply and demand; however, due to its charge/discharge inefficiencies (energy storage results in a loss of at least 10% of electricity in the charge/discharge process), digital solutions are needed to manage grid equilibrium effectively (Watson et al., 2022).In this …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Information Systems
Research centre(s)
Centre for Data Science

Artificial intelligence (AI) to balance fluctuations of intermittent renewable energy sources

Artificial intelligence (AI) can play a significant role in analyzing and predicting energy consumption and production patterns from renewable sources such as solar and wind (Lyu & Liu 2021). This is particularly important due to the key challenge of intermittency, where major renewable sources for electricity, such as solar and wind, are subject to the inconsistencies of the weather (Watson et al., 2022).In this project, we investigate how AI and machine learning algorithms can optimize smart grids and other components …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Information Systems
Research centre(s)
Centre for Data Science

Understanding public perceptions of the sustainable energy transition: a social network analysis

The challenge to keep global warming to 1.5°C above pre-industrial levels has become even greater due to a continued increase in greenhouse gas emissions (IPCC, 2023). One major challenge is the shift from fossil fuels to renewable energy to reduce emissions (Gholami et al., 2016). The share of renewable energy in electricity generation has increased to 28.3%, however, an acceleration of the pace of the transition is required to limit global temperature rise (REN21, 2022).In this project we investigate public …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Information Systems
Research centre(s)
Centre for Data Science

Advanced numerical modeling to study dust deposition mechanisms on photovoltaic panels for the agrivoltaic industry.

The increase in global energy demand necessitates further advancement in photovoltaic (PV) systems. Advancements in PVs could potentially play a role to help meet the Paris Agreement of limiting global temperature increase to below 2 degrees Celsius. In conjunction with the rising demand for clean energy production, the global agricultural industry needs to keep pace with rising food demand which is expected to increase by 50% by 2050 to feed over a projected 10 billion people. The scarcity of fertile …

Study level
PhD, Honours
Faculty
Faculty of Engineering
School
School of Mechanical, Medical and Process Engineering

Internet of Mobile Energy

The emergence of the two-way communication model and Distributed Energy Sources (DES) is transforming traditional power systems from largely centralised energy production to more decentralised and connected management systems. This is called the 'smart grid'.As the smart grid evolves, electric vehicles (EVs) are emerging as unconventional and highly-disruptive participants in the grid that can add significant benefit and flexibility. Notably, EVs are equipped with a relatively high capacity battery that stores energy to power the vehicle.EV batteries, coupled with the …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Computer Science

Metal polymer batteries and supercapacitors for renewable energy storage

Australia boasts rich wind and solar energy resources. To avoid fluctuations placing severe burden on the power grids, a reliable and efficient battery storage is required.The present technology based on lithium-ion batteries suffers from high manufacturing costs, poor safety and short life-span. Metal-polymer batteries are expected to overcome the storage and the charging speed of the traditional batteries in the near future, opening new avenues for renewable energy resources …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Chemistry and Physics
Research centre(s)
Centre for Materials Science
Centre for Clean Energy Technologies and Practices

Decision optimisation in energy supply chain

this project aims to develop integrated forecasting and decision optimisation models for renewable energies.

Study level
PhD
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science

Probabilistic forecasting of energy

This project aims to develop probabilistic forecasting models for renewable energies vi a Bayesian approach.  The models will be developed for very short term and short-term (10 minutes to 24 hours ahead).

Study level
PhD
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science

Spatio-Temporal Forecasting of renewable energies

This project aims to develop short-term (up to 24 hours ahead) forecasting models that take into account the spatial as well as temporal information in wind farms and solar farms. Such models are useful for operational planning in farms and stabilising the network.

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science

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