Martí-Franquès COFUND Fellowship Programme


Details

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Reference:

2018MFP-COFUND-49

Area:

Engineering and Architecture

Supervisor name and surname:

Manel Vallès Rasquera

Supervisor email:

manel.valles@urv.cat

Supervisor short biography

Co-supervisor name and surname:

Dieter Boer

Co-supervisor email:

dieter.boer@urv.cat

Co-supervisor institution:

Universitat Rovira i Virgili

Co-supervisor short biography

PhD programme:

Nanoscience, Materials and Chemical Engineering

Title of the research project:

Modeling and optimization: Energy efficiency and Thermal energy storage

Description of the research project:

OVERVIEW
Goal of this research project: improve energy efficiency considering thermal energy storage (TES) by developing systematic tools for the optimal design and optimization. Specifically, we will investigate the combined use of mathematical programming, simulation and life cycle assessment principles to automatically generate the best design alternatives that may be implemented to achieve environmental improvements.
The overarching aim is the development of technically and economically feasible thermal systems, improving the energy efficiency in applications that can include case studies from industry, buildings, renewable energies or greenhouses.
Models will be developed, that characterize the energy conversion and storage starting from simplified base cases and integrating more complexity. These models will be created on one side in specific software applications as EnergyPlus or TRNSYS, and on the other hand in creating our own code using GAMS or Matlab.

BACKGROUND
This research project will focus on developing novel (global) optimization techniques for the solution of linear/nonlinear and mixed integer nonlinear programming problems (MILP or MINLP) arising in most real case applications.
This project will develop decision-making tools based on the combined use of multi-objective optimization and LCA.
To achieve these goals, we will use multi-objective programming tools combined with LCA for multi-criteria problems. Stochastic programming will assist decision-makers in the face of uncertainty. LCA tools will be employed to assess process alternatives from an environmental perspective.
We will apply these tools to different case studies that have attracted an increasing interest in the recent past. Particularly, we will focus on applications with TES, highlighting the advantages of the proposed methods as compared to traditional design tools.

PROJECT CONTRIBUTION AND METHODOLOGY
Main novelties compared to other contributions presented so far in the literature:
(1) The combined use of mathematical programming, simulation and LCA in case studies as industry, buildings, renewable energies or greenhouses including TES.
(2) The systematic analysis of the mathematical structure of multi-objective problems arising in environmental engineering, which will allow us to identify redundant environmental metrics that can be omitted.
(3) The development of algorithms to expedite the search for optimal solutions in the environmental impact minimization.

THE IDEAL CANDIDATE
Candidates should have a bachelor and/or a master degree on Chemical, Industrial, Mechanical Thermal Engineering, Physics or similar. Knowledge or experience in modeling as well as basic knowledge of standard modeling software packages (e.g. TRNSYS, Matlab, GAMS...) will be considered as a valuable asset. He should have a good level of English (at least B2 or equivalent).

REFERENCES
orcid.org/0000-0002-0748-1287
orcid.org/0000-0002-5532-6409

Gross anual salary:

26443.80 €

Dedication:

Full time

Working hours:

37.5 hours a week

Expected start date:

European union This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 713679