Bridging Renewable Energy Intermittency: Seasonal Thermal Energy Storage for District Heating

Master’s Thesis Project Fall 2024

Context

As the world transitions towards a net-zero greenhouse gas emissions economy, the intermittent nature of some Renewable Energy Sources (RES) poses challenges for maintaining a reliable energy supply. Meanwhile, large amounts of waste heat generated by various sources across multiple sectors (i.e. industrial processes, data centers and buildings) are directly released into the environment, representing a missing potential of an energy source that could otherwise be recovered and utilized. The Swiss buildings stock is responsible for approximately 40% of the total end energy demand in Switzerland and for about one third of the country’s CO2 emissions. Residential and tertiary buildings require a consistent thermal energy supply for its heating demand in the winter months and increasingly for cooling in the summer months. Switzerland’s Energy Strategy 2050 aims to reduce the net CO2 emissions of the Swiss buildings park to zero by 2050. In this context, this project aims to bridge the gap between intermittent RES, exergy loss of waste heat rejection, and the buildings stock’s thermal energy demands by exploring the feasibility of Seasonal Thermal Energy Storage (STES) technologies in 5th-Generation District Heating and Cooling Networks (5G-DHCNs). By storing excess heat generated during periods of renewable energy abundance and waste heat recovery, STES systems can provide a reliable heat supply to meet winter heating demands.

Project/Tasks

  • Conduct literature review on renewable energy intermittency, waste heat recovery, and thermal energy storage technologies.
  • Clustering of the heat demand based on meaningful criteria, such as weather data, ambient air temperature, carbon intensity of grid electricity, etc.,
  • Identify potential heat sources for STES systems, including RES and waste heat sources.
  • Develop mathematical models for STES systems and optimise their use for a district using Mixed-Integer Linear Programming (MILP) techniques.
  • Implement and optimize STES models based on different objective functions, such as maximizing energy efficiency or minimizing costs.
  • Evaluate the performance of STES systems and compare them with conventional energy systems that operate without storage.
  • Conduct sensitivity analysis on key parameters affecting STES performance, such as energy storage density, charging and discharging rates, and thermal losses.
  • Comparative analysis of the different modelled STES scenarios from an economic and environmental perspectives.

Skills

  • Strong interest in renewable energy systems and thermal energy storage technologies.
  • Proficiency in mathematical modeling and optimization techniques, particularly with MILP.
  • Proficient in programming languages, especially Python.
  • Ability to interpret simulation results and write comprehensive reports.
  • Relevant coursework:
    • ME-454 Modelling and Optimisation of Energy Systems
    • ME-409 Energy Conversion and Renewable Energy

Administrative

This project is part of a collaborative research project involving multiple labs from EPFL called the ‘HeatingBits’, and a collaborative project called ‘GISOptiTes’ between EPFL and OST University of Applied Sciences of Eastern Switzerland in Rapperswil. The project will be supervised by Sai Sudharshan Ravi (PhD student, IPESE) and Dr. Eduardo Pina (postdoc, IPESE). Interested candidates are invited to submit their CV along with a short motivation letter to sai.ravi.@epfl.ch or eduardo.pina.@epfl.ch