Decision Modelling and Analysis of Decentralised Green Energy Systems and Their Impact (FULLY FUNDED)

Student background required:
The student should be familiar with and knowledgeable about decision theory, ideally decision making under uncertainty and multiple criteria decision analysis; the student should also be interested in and knowledgeable about the performance analysis of energy systems and their impact on economy and society.

Benefit to / Impact on Industry:
Decentralised Green Energy (DGE) is regarded to be central to the world’s future energy and economic strategies. It is estimated that the increased use of DGE in the UK could reduce CO2 emissions associated with heat and power generation by as much as 30%. It is hoped that the severe pollution of cities in China mainly caused by the use of fossil fuel for heating and transportation could be reduced by the widespread deployment of DGE systems. However, DGE systems and their potential impact on world economy have not been studied systematically. This project is proposed to fill the gap by investigating important issues about DGE systems and their contributions to green economy, which are of common and widespread interests to many countries. It is expected that many people in both public and private sectors can directly benefit from this project, such as policy makers, energy suppliers and consumers, energy network owners, and DGE investors and stakeholders in local communities, who have direct interests in the generation, transition and consumption of renewable energies.

What novelty will the student base their PhD on?
This multidisciplinary project will establish academic collaborations between three research teams specialising in complementary areas to investigate the success factors of and barriers to decentralised green energy (DGE) systems and their impact on the green economy. Apart from analysing ‘normal’ factors such as regulation, institutional frameworks and economic structures, it will focus on investigating whether societal and sociocultural factors, which are crucial to western countries like Germany and the UK, would also play an important role in China. As such, the modelling for DGE performance evaluation and impact analysis will require the systematic and consistent handling of multiple factors of both a quantitative and qualitative nature under uncertainty, which will be based on multiple criteria decision theory and evidence-based reasoning with both numerical data and expert knowledge. The findings will contribute to a global evidence base about DGE and be useful to researchers in policy analysis, energy transition, sustainability, and renewable energies.

Project overview:
Sustainable generation and consumption of energy is paramount for the world economy and the welfare of mankind of current and future generations. Decentralised Green Energy (DGE) will be central to the world’s future energy and economic strategies. ‘Decentralised’ means to produce and consume energy locally to avoid energy loss in long distance transmission. DGE can harness a wide range of small-scale renewable and low carbon sources and lead to local community involvement, investment and increased employment. This project is aimed to help create a more favourable techno-economic and socio-institutional environment for the diffusion of DGE systems, generate more positive impacts on the economy, and enable DGE systems to become self-sustainable and resource efficient.

Outline of Proposed Project Plan:
Year 1: Taught courses and preparatory study
Year 2: A full scale literature review about DGE systems will be conducted and some real DGE systems will be evaluated together with possible site visits. Key factors for performance and impact assessment of DGE systems will be identified and their measurement methods will be investigated. A report or paper will be generated to summarise the findings.
Year 3: An evaluation model will be developed to assess the outputs and effectiveness of a DGE system; a decision model will be developed to analyse the contribution of larger scale DGE system deployment to the green economy. These models will be validated using both secondary data and real case studies.
Year 4: The developed evaluation and decision models will be further applied in consultation with the industrial partners. A number of papers will be written and submitted and a PhD thesis will be generated.