Multi-field and multi-scale Computational Approach to design and durability of PhotoVoltaic Modules View Homepage


Ontology type: schema:MonetaryGrant     


Grant Info

YEARS

2012-2017

FUNDING AMOUNT

1483980 EUR

ABSTRACT

"Photovoltaics (PV) based on Silicon (Si) semiconductors is one the most growing technology in the World for renewable, sustainable, non-polluting, widely available clean energy sources. Theoretical and applied research aims at increasing the conversion efficiency of PV modules and their lifetime. The Si crystalline microstructure has an important role on both issues. Grain boundaries introduce additional resistance and reduce the conversion efficiency. Moreover, they are prone to microcracking, thus influencing the lifetime. At present, the existing standard qualification tests are not sufficient to provide a quantitative definition of lifetime, since all the possible failure mechanisms are not accounted for. In this proposal, an innovative computational approach to design and durability assessment of PV modules is put forward. The aim is to complement real tests by virtual (numerical) simulations. To achieve a predictive stage, a challenging multi-field (multi-physics) computational approach is proposed, coupling the nonlinear elastic field, the thermal field and the electric field. To model real PV modules, an adaptive multi-scale and multi-field strategy will be proposed by introducing error indicators based on the gradients of the involved fields. This numerical approach will be applied to determine the upper bound to the probability of failure of the system. This statistical assessment will involve an optimization analysis that will be efficiently handled by a Mathematica-based hybrid symbolic-numerical framework. Standard and non-standard experimental testing on Si cells and PV modules will also be performed to complement and validate the numerical approach. The new methodology based on the challenging integration of advanced physical and mathematical modelling, innovative computational methods and non-standard experimental techniques is expected to have a significant impact on the design, qualification and lifetime assessment of complex PV systems." More... »

URL

http://cordis.europa.eu/project/rcn/104569_en.html

Related SciGraph Publications

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/2209", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "type": "DefinedTerm"
      }
    ], 
    "amount": {
      "currency": "EUR", 
      "type": "MonetaryAmount", 
      "value": "1483980"
    }, 
    "description": "\"Photovoltaics (PV) based on Silicon (Si) semiconductors is one the most growing technology in the World for renewable, sustainable, non-polluting, widely available clean energy sources. Theoretical and applied research aims at increasing the conversion efficiency of PV modules and their lifetime. The Si crystalline microstructure has an important role on both issues. Grain boundaries introduce additional resistance and reduce the conversion efficiency. Moreover, they are prone to microcracking, thus influencing the lifetime. At present, the existing standard qualification tests are not sufficient to provide a quantitative definition of lifetime, since all the possible failure mechanisms are not accounted for. In this proposal, an innovative computational approach to design and durability assessment of PV modules is put forward. The aim is to complement real tests by virtual (numerical) simulations. To achieve a predictive stage, a challenging multi-field (multi-physics) computational approach is proposed, coupling the nonlinear elastic field, the thermal field and the electric field. To model real PV modules, an adaptive multi-scale and multi-field strategy will be proposed by introducing error indicators based on the gradients of the involved fields. This numerical approach will be applied to determine the upper bound to the probability of failure of the system. This statistical assessment will involve an optimization analysis that will be efficiently handled by a Mathematica-based hybrid symbolic-numerical framework. Standard and non-standard experimental testing on Si cells and PV modules will also be performed to complement and validate the numerical approach. The new methodology based on the challenging integration of advanced physical and mathematical modelling, innovative computational methods and non-standard experimental techniques is expected to have a significant impact on the design, qualification and lifetime assessment of complex PV systems.\"", 
    "endDate": "2017-11-30T00:00:00Z", 
    "funder": {
      "id": "https://www.grid.ac/institutes/grid.452896.4", 
      "type": "Organization"
    }, 
    "id": "sg:grant.3792837", 
    "identifier": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "3792837"
        ]
      }, 
      {
        "name": "cordis_id", 
        "type": "PropertyValue", 
        "value": [
          "104569"
        ]
      }
    ], 
    "inLanguage": [
      "en"
    ], 
    "keywords": [
      "available clean energy sources", 
      "PV modules", 
      "durability", 
      "involved field", 
      "nonlinear elastic field", 
      "multi-scale Computational Approach", 
      "Si crystalline microstructure", 
      "world", 
      "proposal", 
      "research aim", 
      "standard qualification tests", 
      "qualification", 
      "Si cells", 
      "silicon", 
      "aim", 
      "Photovoltaic Modules", 
      "statistical assessment", 
      "quantitative definition", 
      "real PV modules", 
      "possible failure mechanisms", 
      "numerical approach", 
      "conversion efficiency", 
      "significant impact", 
      "grain boundaries", 
      "probability", 
      "multi-field strategy", 
      "innovative computational approach", 
      "adaptive multi-scale", 
      "technology", 
      "design", 
      "non-standard experimental testing", 
      "new methodology", 
      "electric field", 
      "important role", 
      "present", 
      "Photovoltaics", 
      "lifetime assessment", 
      "Si", 
      "lifetime", 
      "complex PV systems", 
      "multi-field", 
      "innovative computational methods", 
      "system", 
      "predictive stage", 
      "thermal field", 
      "real test", 
      "simulation", 
      "additional resistance", 
      "issues", 
      "gradient", 
      "semiconductor", 
      "Mathematica", 
      "mathematical modelling", 
      "multi-physics", 
      "non-standard experimental techniques", 
      "computational approach", 
      "failure", 
      "Theoretical", 
      "error indicator", 
      "hybrid symbolic-numerical framework", 
      "optimization analysis", 
      "integration", 
      "durability assessment"
    ], 
    "name": "Multi-field and multi-scale Computational Approach to design and durability of PhotoVoltaic Modules", 
    "recipient": [
      {
        "id": "https://www.grid.ac/institutes/grid.462365.0", 
        "type": "Organization"
      }
    ], 
    "sameAs": [
      "https://app.dimensions.ai/details/grant/grant.3792837"
    ], 
    "sdDataset": "grants", 
    "sdDatePublished": "2019-03-07T11:22", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com.uberresearch.data.processor/core_data/20181219_192338/projects/base/cordis_projects_3.xml.gz", 
    "startDate": "2012-12-01T00:00:00Z", 
    "type": "MonetaryGrant", 
    "url": "http://cordis.europa.eu/project/rcn/104569_en.html"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/grant.3792837'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/grant.3792837'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/grant.3792837'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/grant.3792837'


 

This table displays all metadata directly associated to this object as RDF triples.

97 TRIPLES      19 PREDICATES      83 URIs      76 LITERALS      4 BLANK NODES

Subject Predicate Object
1 sg:grant.3792837 schema:about anzsrc-for:2209
2 schema:amount N95c250815159483a8f2aad9d288d30e6
3 schema:description "Photovoltaics (PV) based on Silicon (Si) semiconductors is one the most growing technology in the World for renewable, sustainable, non-polluting, widely available clean energy sources. Theoretical and applied research aims at increasing the conversion efficiency of PV modules and their lifetime. The Si crystalline microstructure has an important role on both issues. Grain boundaries introduce additional resistance and reduce the conversion efficiency. Moreover, they are prone to microcracking, thus influencing the lifetime. At present, the existing standard qualification tests are not sufficient to provide a quantitative definition of lifetime, since all the possible failure mechanisms are not accounted for. In this proposal, an innovative computational approach to design and durability assessment of PV modules is put forward. The aim is to complement real tests by virtual (numerical) simulations. To achieve a predictive stage, a challenging multi-field (multi-physics) computational approach is proposed, coupling the nonlinear elastic field, the thermal field and the electric field. To model real PV modules, an adaptive multi-scale and multi-field strategy will be proposed by introducing error indicators based on the gradients of the involved fields. This numerical approach will be applied to determine the upper bound to the probability of failure of the system. This statistical assessment will involve an optimization analysis that will be efficiently handled by a Mathematica-based hybrid symbolic-numerical framework. Standard and non-standard experimental testing on Si cells and PV modules will also be performed to complement and validate the numerical approach. The new methodology based on the challenging integration of advanced physical and mathematical modelling, innovative computational methods and non-standard experimental techniques is expected to have a significant impact on the design, qualification and lifetime assessment of complex PV systems."
4 schema:endDate 2017-11-30T00:00:00Z
5 schema:funder https://www.grid.ac/institutes/grid.452896.4
6 schema:identifier N45d33ba2ea9a4c1094028f999e403fa7
7 Ne2fb1705e6e64572a205d8fddb8fea15
8 schema:inLanguage en
9 schema:keywords Mathematica
10 PV modules
11 Photovoltaic Modules
12 Photovoltaics
13 Si
14 Si cells
15 Si crystalline microstructure
16 Theoretical
17 adaptive multi-scale
18 additional resistance
19 aim
20 available clean energy sources
21 complex PV systems
22 computational approach
23 conversion efficiency
24 design
25 durability
26 durability assessment
27 electric field
28 error indicator
29 failure
30 gradient
31 grain boundaries
32 hybrid symbolic-numerical framework
33 important role
34 innovative computational approach
35 innovative computational methods
36 integration
37 involved field
38 issues
39 lifetime
40 lifetime assessment
41 mathematical modelling
42 multi-field
43 multi-field strategy
44 multi-physics
45 multi-scale Computational Approach
46 new methodology
47 non-standard experimental techniques
48 non-standard experimental testing
49 nonlinear elastic field
50 numerical approach
51 optimization analysis
52 possible failure mechanisms
53 predictive stage
54 present
55 probability
56 proposal
57 qualification
58 quantitative definition
59 real PV modules
60 real test
61 research aim
62 semiconductor
63 significant impact
64 silicon
65 simulation
66 standard qualification tests
67 statistical assessment
68 system
69 technology
70 thermal field
71 world
72 schema:name Multi-field and multi-scale Computational Approach to design and durability of PhotoVoltaic Modules
73 schema:recipient https://www.grid.ac/institutes/grid.462365.0
74 schema:sameAs https://app.dimensions.ai/details/grant/grant.3792837
75 schema:sdDatePublished 2019-03-07T11:22
76 schema:sdLicense https://scigraph.springernature.com/explorer/license/
77 schema:sdPublisher N8dd89d4ad1254d1497072d26d48a9381
78 schema:startDate 2012-12-01T00:00:00Z
79 schema:url http://cordis.europa.eu/project/rcn/104569_en.html
80 sgo:license sg:explorer/license/
81 sgo:sdDataset grants
82 rdf:type schema:MonetaryGrant
83 N45d33ba2ea9a4c1094028f999e403fa7 schema:name dimensions_id
84 schema:value 3792837
85 rdf:type schema:PropertyValue
86 N8dd89d4ad1254d1497072d26d48a9381 schema:name Springer Nature - SN SciGraph project
87 rdf:type schema:Organization
88 N95c250815159483a8f2aad9d288d30e6 schema:currency EUR
89 schema:value 1483980
90 rdf:type schema:MonetaryAmount
91 Ne2fb1705e6e64572a205d8fddb8fea15 schema:name cordis_id
92 schema:value 104569
93 rdf:type schema:PropertyValue
94 anzsrc-for:2209 schema:inDefinedTermSet anzsrc-for:
95 rdf:type schema:DefinedTerm
96 https://www.grid.ac/institutes/grid.452896.4 schema:Organization
97 https://www.grid.ac/institutes/grid.462365.0 schema:Organization
 




Preview window. Press ESC to close (or click here)


...