Leeds Beckett University is partnering with Huddersfield-based Zenergy Solar on a 28-month research project to create a digital platform that makes large-scale solar energy systems easier to manage for organisations operating across multiple sites.
The Leeds business news collaboration brings together the university’s computing and data expertise with Zenergy’s renewable energy experience to develop ZenSmart, a system designed to address complexity that prevents businesses adopting solar at scale.
The Knowledge Transfer Partnership, part-funded by UKRI through Innovate UK, will help organisations including social housing landlords, care homes and schools manage solar installations across multiple properties from a single dashboard.
Simplifying Complex Solar Management
Dr Sheikh-Akbari, Reader / School of Built Environment, Engineering and Computing, said:
“Zenergy Solar build and supply custom-built solar energy solutions, including solar panels and battery storage. They work mainly with commercial and public and third sector clients, including care homes, social housing associations and schools. The solar energy market can be complex, with a wide range of suppliers, technologies, and considerations around cost and long term maintenance.
“Our KTP with Zenergy Solar aims to support their ambition to make solar energy solutions easier to implement and manage for organisations, such as social housing landlords and care home providers, who have multiple properties and a complex infrastructure of solar energy to manage.”
The ZenSmart platform will enable organisations to monitor energy generation in real-time for quicker fault detection, manage multiple buildings through one user-friendly dashboard, and create bespoke solutions optimising different solar panels and battery sizes in a single system.
AI-Powered Fault Detection
Julian Wiley, Managing Director at Zenergy Solar, said:
“The solar energy sector faces significant challenges due to the diverse suppliers available, complicated monitoring systems and ineffective fault detection technologies. ZenSmart will be an innovative product, bringing LBU’s advanced technical expertise and cutting-edge research to simplify the social energy market and encourage broader adoption and ongoing innovation. It will track and operate multiple potential solutions without the added headache of multiple portals and data repositories.
“Using advanced AI, we will be able to enhance fault detection, reduce downtime and improve reliability, whilst performance modelling will support more complex product installations.”
The platform will use advanced AI to enhance fault detection, reduce downtime and improve reliability, while performance modelling will support more complex installations without requiring multiple portals and data repositories.
Graduate Role Created
The partnership will recruit a graduate as KTP Associate in a new Smart Energy Systems Engineer role, working full-time with Zenergy Solar while supported by Leeds Beckett academics. The position closed for applications on 26 February.
The academic team includes Dr Sheikh-Akbari, Professor Amar Aggoun (head of computer science and professor of visual computing), and Dr Pooneh Bagheri Zadeh (course director for computer science).
The project targets organisations managing solar installations across multiple sites, where coordinating different technologies, suppliers and monitoring systems creates complexity that prevents scaling renewable energy adoption despite commercial viability.
Why this matters for Leeds
This partnership showcases Leeds institutions solving real-world business challenges through applied research, turning university expertise into commercial innovation that addresses barriers to renewable energy adoption. Creating the graduate KTP Associate role demonstrates how Leeds collaborations generate skilled employment in emerging green technology sectors. The project strengthens Leeds’ position in sustainable technology development while helping local and regional businesses overcome practical obstacles to solar adoption.![]()












































