Integration of ageing model in the energy yield simulation frame for PV-modules@imec

Genk - PhD
More than two weeks ago

Correct modeling of the ageing of PV-modules is crucial to assess the energy yield evolution over time


Topic title: Integration of ageing model in the energy yield simulation frame for PV-modules@imec

Topic description:

Close to 4% of the EU's electricity needs are provided by photovoltaics (PV) and this share is projected to exponentially increase in the coming years. Inevitably, as PV deployment  increases at such rate, PV stakeholders and grid operators strive for accurate predictions of PV energy yield and investment returns. Currently PV modules and module materials are compared on the market based on their performance at standard testing conditions (STC) and their capacity to pass standardized accelerated tests.

None of the listed assessment methods can warrant  high energy yield and durability on the field as recognized by both technical experts and financial investors. While the PV module manufacturers need to provide a reliability warranty for 20-30 years, and financial investors are equally planning on this timescale to realize a return on investment. Facing these demands, players in the downstream adapted a rather conservative attitude towards novel materials and technologies and they impose several years of outdoor testing. This forms a major barrier and delay for the implementation of innovations.

 This clearly highlights the need for a novel approach both in performance and reliability assessment of PV materials and technologies. The accelerating pace of technology development requires fast and precise assessment methods. We believe the solution lies in energy yield simulation resolving the properties of module materials, cells and interconnection methods.

Current energy yield simulation tools on the market using a black box or parametric approach provide an efficient tool only for PV plant design and high-level comparison of technologies. However, they cannot resolve the impact of specific material properties as well as their reliability improvements. Current approaches for degradation rate modelling assume linear degradation rate of 0.7-1.5 %/year for crystalline silicon neglecting completely the impact of climate and installation conditions and varying dynamic failure modes.

Imec aspires to develop lifelong energy yield simulation based on semi-empirical physics based simulation approach. This builds on its patented and extensively validate PV system energy yield simulation framework continuously updated to considered the emerging technologies. Moreover, our thermo-mechanical and multi-scale stress simulation approach will be another critical building block of the future reliability model.

Final goal of the PhD will be a physics based degradation rate prediction model integrated in the larger energy yield simulation framework of imec. Based on field failure insights the dominating failure mechanisms for current industrial technologies will be identified. From a combined semi-empirical and finite element modelling approach degradation models will be devise dependent on environmental stress conditions. From the detailed finite element or analytical degradation models through advanced computing and simulation methods the candidate will extract a reduced order model through numerous iterative cycle of validation and sensitivity analysis. Experimental validation of the model(s) through dedicated sample preparation and accelerated ageing tests and field data from imec partners will be a critical part of the thesis.

This topic is part of the core strategy of the PV Module & Systems Group located on the Energyville Campus in Genk. The student will collaborated with senior researchers and industrial partners. The  new state-of-the-art module assembly, characterization and reliability testing line in EnergyVille will be leveraged in the project

Required background: Master in Scienc or Engineering

Type of work: 15% literature, 50% modelling, 35% experimental

Supervisor: Jef Poortmans, Michael Daenen

Daily advisor: Eszter Voroshazi

The reference code for this position is 1812-71. Mention this reference code on your application form.


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