Doctoral student in Techno-economic Optimization of Thermal Energy Storage Full-time NEW

Doctoral Student in Techno-economic Optimization of Thermal Energy Storage

Industrial process heat represents a major challenge in the transition towards a climate-neutral energy system, as a large share of industrial heat demand is still supplied by fossil fuels. Thermal energy storage (TES) can support the integration of renewable heat and electricity by decoupling energy availability from industrial demand and providing reliable, dispatchable process heat. However, TES technologies are often assessed using different assumptions, modelling approaches and economic boundaries, making consistent comparison difficult. This doctoral project will address this challenge for industrial steam and other medium- to high-temperature heat applications.

The project will develop a modular techno-economic modelling and optimization framework to compare different TES concepts, including particle/powder storage, molten salts and phase-change-material (PCM) systems, using consistent technical, operational and economic boundaries. The models will consider integration with renewable heat sources such as geothermal and solar thermal energy, as well as hybridization with electrification and heat upgrading. A key research question is how storage technology, charging strategy and system sizing should be selected for different process temperatures, load profiles, storage durations, renewable-resource conditions and electricity markets. Quasi-steady-state models and annual optimization will be complemented by targeted dynamic modelling where transient effects significantly influence system performance.

The research will draw on experimental data, industrial case studies and collaborations from ongoing projects, covering applications such as steam supply up to approximately 300 °C and process air up to 400 °C. Expected outcomes include validated modelling tools, harmonized techno-economic indicators and technology-selection maps identifying cost-effective TES solutions across European industrial and market conditions. Benchmarking against alternative heat-supply options will support practical guidelines for technology selection, system design and investment in future industrial deployment.

Supervision: Justin Chiu acts as the main supervisor to the doctoral student. Salvatore Guccione is proposed as co-supervisor.

To be admitted to postgraduate education, the applicant must have basic eligibility in accordance with either of the following: passed a second cycle degree (for example a master's degree), or completed course requirements of at least 240 higher education credits, of which at least 60 second-cycle higher education credits, or acquired, in some other way within or outside the country, substantially equivalent knowledge. Completed coursework or course modules in engineering thermodynamics, heat transfer, energy system analysis, and optimization methods are required in accordance with admission criteria for the specified third cycle studies. In addition to the above, there is also a mandatory requirement for English equivalent to English B/6.

In order to succeed as a doctoral student at KTH you need to be goal oriented and persevering in your work. During the selection process, candidates will be assessed upon their ability to independently pursue his or her work, collaborate with others, have a professional approach and analyze and work with complex issues. Demonstrated proficiency in computational programming with Python, machine learning, and Mixed-Integer Linear Programming (MILP) is meritorious. Similarly, specific knowledge in thermal energy storage, heat exchangers, and techno-economic modeling is also a merit. After the qualification requirements, great emphasis will be placed on personal skills.