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​​AI-Driven Maintenance Optimization for Minigrid​

Doctoral Training Grant Funding Information 

This funding model includes a 36 month fully funded PhD Studentship, set in-line with UK Research & Innovation values. For 2025/6, this will be £20,780 per year. The tax-free stipend will be paid monthly. This PhD Studentship also includes a Full-Time Fee Scholarship for up to 3 years. The funding is subject to your continued registration on the research degree, making satisfactory progression within your PhD, as well as attendance on and successful completion of the Postgraduate Certificate in Research Practice.

All applicants will receive the same stipend irrespective of fee status. 

Application Closing Date: 


Midday (UK Time) on Wednesday 17th September 2025 for a start date of 2nd February 2026.

How to Apply 

To apply, please follow the below steps:

  1. Complete the BCU Online Application Form.
  2. Complete the Doctoral Studentship Proposal Form in full, ensuring that you quote the project ID. You will be required to upload your proposal in place of a personal statement on the BCU online application form.
  3. Upload two references to your online application form (at least one of which must be an academic reference). 
  4. Upload your qualification(s) for entry onto the research degree programme. This will be Bachelor/Master’s certificate(s) and transcript(s). 
  5. International applicants must also provide a valid English language qualification. Please see the list of English language qualifications accepted here. Please check the individual research degree course page for the required scores. 

Frequently Asked Questions 

To help support you to complete your application, please consult the frequently asked questions below: 

Project title: AI-Driven Maintenance Optimization for Minigrid​ 

Project Lead: Associate Professor Florimond Gueniat​ 

Project ID: 29 - 46456366​ 

Project description:

Access to reliable and sustainable energy is essential for economic growth, especially in rural and off-grid communities. Solar-powered minigrids hold great potential to transform these areas by enabling productive activities like irrigation, cold storage, and small-scale manufacturing. However, challenges such as inefficient supply chains, high maintenance costs, and uncertain financial returns hinder their widespread adoption. ​ 

​Building on the UKRI-funded Smart SIP+ project in Bangladesh, which develops solar-powered pumps and cold storage systems to support agriculture, this PhD research aims to address key barriers to scaling solar-powered minigrids. While existing efforts have focused on technical aspects like energy production, this research will tackle critical gaps in predictive maintenance, and associated business model design. 

​The project will leverage AI and IoT to create predictive maintenance strategies, enhancing reliability and minimizing downtime. Additionally, innovative business models and alternative revenue streams will be explored to ensure financial viability and improve returns on investment. Inclusivity will be central to the framework, ensuring the benefits of minigrid systems reach marginalized and underrepresented community members. 

​Research Questions 

  1. ​How can AI and IoT be used to optimize the supply chain for minigrid components, reducing costs and taking maintenance into account? 
  2. ​What predictive maintenance strategies can be developed using AI to enhance the reliability and lifespan of minigrid systems? 
  3. ​What business models associated to the maintenance can ensure the financial viability and ROI of solar-powered minigrids? 
  4. ​How can inclusivity be integrated into the design, deployment, and operation of minigrid systems to ensure equitable benefits for all community members? 

​By integrating AI, IoT, and digital twins, the framework aims to make solar-powered minigrids more cost-effective, reliable, and scalable. This research will provide actionable insights for policymakers, developers, and investors, paving the way for sustainable energy solutions that empower rural economies. 

Anticipated findings and contributions to knowledge:

Theoretical Contributions:  

  • ​A novel AI-driven framework for integrating supply chain, maintenance optimization and business planning in minigrid systems.  
  • ​New insights into the application of Industry 4.0/5.0 technologies in the renewable energy sector.  

Practical Contributions:  

  • ​A scalable and cost-effective solution for improving the reliability and sustainability of minigrids.  
  • ​A user-friendly digital platform for supply chain, maintenance management, business models and alternative revenue streams that enhance ROI and financial viability.  
  • ​Inclusive design and deployment strategies that ensure equitable benefits for all community members. 

Policy Contributions:  

  • ​Evidence-based recommendations for policymakers to support the adoption of AI-driven minigrid solutions in developing countries.  

Person Specification:

​​Entry Requirements: 

  • ​To apply for our Engineering PhD Research Degree you should have, or expect to be awarded, a Master’s degree in a relevant subject area from a British or overseas university.  

  • ​Exceptional candidates without a Master’s degree, but holding a first class or upper second class Bachelor’s degree in a relevant subject area, may be considered.  

  • ​We also welcome enquiries from potential PhD researchers with appropriate levels of professional experience. ​ 

​Essential Criteria:  

  • ​Experience in conducting research at appropriate level, preferably in areas related to renewable energy, supply chain optimization or predictive maintenance.  

  • ​Proficiency in AI and IoT technologies. Experience with digital twins and predictive maintenance strategies. Knowledge of solar energy systems and minigrids.  

  • ​Excellent written and verbal communication skills. Ability to present research findings effectively to both technical and non-technical audiences.  

  • ​Cultural sensitivity and the ability to work effectively in diverse cultural settings.  

  • ​A strong motivation to contribute to the field of renewable energy and economic development. Commitment to completing a PhD and conducting high-quality research. 

Overseas applicants:

International applicants must also provide a valid English language qualification, such as International English Language Test System (IELTS) or equivalent with an overall score of 6.5 with no band below 6.0.

Contact:

If you have any questions or need further information, please use the contact details below: 

- For enquiries about the project content, please contact: florimond.gueniat@bcu.ac.uk

- For enquiries about the application process, please contact: research.admissions@bcu.ac.uk