Doctoral student using lab equipment

Optimisation of Low Temperature District Heating Network with data driven control model

  • School: School of Architecture, Design and the Built Environment
  • Starting: 2018
  • Funding: UK student / EU student (non-UK)


The School of Architecture, Design and Built Environment is offering a fully funded new PhD studentship for three years to develop optimisation of Low Temperature District Heating Network with data driven control model. This research will be undertaken in collaboration with Siemens Ltd.

The novel data driven algorithm for heat management in Low Temperature District Network will be developed using Siemens MindSphere platform analytics and development tools. MindSphere is a cloud-based system developed by Siemens with advanced analytics that collects and analyses all kinds of sensor data in real time. It is equipped with open application programming interfaces (APIs) and development tools. The improved heat management will help householders achieve better internal climate with a faster heating response time and higher comfort levels due to the more even temperature distribution. The increased control levels will provide a better interface with the heating system allowing the user to have more control and feedback from the system to enable better utilisation.

MindSphere will collect data from a Low Temperature District Heating (LTDH) scheme develop under EU H2020 REMOURBAN grant. This is a five year H2020 Smart City and Community Lighthouse scheme, that aims at the development and validation in three lighthouse cities (Valladolid-Spain, Nottingham-UK and Tepebasi /Eskisehir-Turkey) of a sustainable urban regeneration model that leverages the convergence of energy, mobility and ICT sectors. Part of the project main interventions is a new LTDH system in four maisonette blocks of 94 low-raised flats at the Nottingham demo site. The opportunity to use the return flow from the existing high temperature network rather than extending high temperature supply has presented Nottingham with a cheaper and effective proposition for heating residential homes without the need for high pressure, high temperature resilient infrastructure. The REMOURBAN data collected at the NTU server is planned to be used in MindSphere to further facilitate better energy management and control to suit predicted demand profiles that will provide further energy savings and citizen engagement.

The successful candidate will spend time in the Nottingham located Siemens Managed Services business to learn vital skills and knowledge in MindSphere, an open cloud platform or “IoT operating system” developed by Siemens for applications in the context of the IoT, and with NTU alongside academics in the department of Computing and Technology.


Dr. Anton Ianakiev

Dr. Evtim Peytchev

Prof. Michael White

Entry qualifications

Applicants must have at least 2:1 honours in Civil, Environmental or Mechanical Engineering, or related subject. Applicants having programing experience is desirable. The candidate is expected to conduct work with industrial partners and should have good interpersonal skills. English language skills (if English is not your native language): an overall score of IELTS 6.5 or equivalent, with individual scores of 6.0 in each of the four sub-skills: writing, reading, speaking and listening.

How to apply

How to apply

Applications close at 12 pm on Thursday 18 October.

Please see our how to apply page for further information.

Fees and funding

The studentship will pay UK/EU tuition fees. It will also provide a maintenance stipend of approximately £14,777 per year for three years (the stipend is linked to the RCUK rate, starting in 2018).

This studentship is funded by NTU and Siemens and applicants will have to sign the terms of the agreement.

Guidance and support

Further information on guidance and support can be found on this page.

Still need help?

Anton Ianakiev