<span style="font-variant: small-caps">e</span>4<span style="font-variant: small-caps">clim</span> 1.0: The Energy for a Climate Integrated Model: Description and Application to Italy
We develop an open-source Python software integrating flexibility needs from Variable Renewable Energies (VREs) in the development of regional energy mixes. It provides a flexible and extensible tool to researchers/engineers, and for education/outreach. It aims at evaluating and optimizing energy de...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2019-11-01
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| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/12/22/4299 |
| _version_ | 1798041113735462912 |
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| author | Alexis Tantet Marc Stéfanon Philippe Drobinski Jordi Badosa Silvia Concettini Anna Cretì Claudia D’Ambrosio Dimitri Thomopulos Peter Tankov |
| author_facet | Alexis Tantet Marc Stéfanon Philippe Drobinski Jordi Badosa Silvia Concettini Anna Cretì Claudia D’Ambrosio Dimitri Thomopulos Peter Tankov |
| author_sort | Alexis Tantet |
| collection | DOAJ |
| description | We develop an open-source Python software integrating flexibility needs from Variable Renewable Energies (VREs) in the development of regional energy mixes. It provides a flexible and extensible tool to researchers/engineers, and for education/outreach. It aims at evaluating and optimizing energy deployment strategies with higher shares of VRE, assessing the impact of new technologies and of climate variability and conducting sensitivity studies. Specifically, to limit the algorithm’s complexity, we avoid solving a full-mix cost-minimization problem by taking the mean and variance of the renewable production−demand ratio as proxies to balance services. Second, observations of VRE technologies being typically too short or nonexistent, the hourly demand and production are estimated from climate time series and fitted to available observations. We illustrate <span style="font-variant: small-caps;">e</span>4<span style="font-variant: small-caps;">clim</span>’s potential with an optimal recommissioning-study of the 2015 Italian PV-wind mix testing different climate data sources and strategies and assessing the impact of climate variability and the robustness of the results. |
| first_indexed | 2024-04-11T22:16:58Z |
| format | Article |
| id | doaj.art-1b35de5ac43c473aaaa301a30551a354 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-11T22:16:58Z |
| publishDate | 2019-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-1b35de5ac43c473aaaa301a30551a3542022-12-22T04:00:21ZengMDPI AGEnergies1996-10732019-11-011222429910.3390/en12224299en12224299<span style="font-variant: small-caps">e</span>4<span style="font-variant: small-caps">clim</span> 1.0: The Energy for a Climate Integrated Model: Description and Application to ItalyAlexis Tantet0Marc Stéfanon1Philippe Drobinski2Jordi Badosa3Silvia Concettini4Anna Cretì5Claudia D’Ambrosio6Dimitri Thomopulos7Peter Tankov8LMD/IPSL, École Polytechnique, IP Paris, Sorbonne Université, ENS, PSL University, CNRS, 91128 Palaiseau, FranceLMD/IPSL, École Polytechnique, IP Paris, Sorbonne Université, ENS, PSL University, CNRS, 91128 Palaiseau, FranceLMD/IPSL, École Polytechnique, IP Paris, Sorbonne Université, ENS, PSL University, CNRS, 91128 Palaiseau, FranceLMD/IPSL, École Polytechnique, IP Paris, Sorbonne Université, ENS, PSL University, CNRS, 91128 Palaiseau, FranceIRJI, Université de Tours, 37200 Tours, FranceDépartement d’Economie, École polytechnique, IP Paris, 91128 Palaiseau, FranceLIX, École polytechnique, IP Paris, CNRS, 91128 Palaiseau, FranceLIX, École polytechnique, IP Paris, CNRS, 91128 Palaiseau, FranceCREST, ENSAE, École Polytechnique, IP Paris, 91128 Palaiseau, FranceWe develop an open-source Python software integrating flexibility needs from Variable Renewable Energies (VREs) in the development of regional energy mixes. It provides a flexible and extensible tool to researchers/engineers, and for education/outreach. It aims at evaluating and optimizing energy deployment strategies with higher shares of VRE, assessing the impact of new technologies and of climate variability and conducting sensitivity studies. Specifically, to limit the algorithm’s complexity, we avoid solving a full-mix cost-minimization problem by taking the mean and variance of the renewable production−demand ratio as proxies to balance services. Second, observations of VRE technologies being typically too short or nonexistent, the hourly demand and production are estimated from climate time series and fitted to available observations. We illustrate <span style="font-variant: small-caps;">e</span>4<span style="font-variant: small-caps;">clim</span>’s potential with an optimal recommissioning-study of the 2015 Italian PV-wind mix testing different climate data sources and strategies and assessing the impact of climate variability and the robustness of the results.https://www.mdpi.com/1996-1073/12/22/4299renewable energyclimate variabilityenergy mixmean-variancesensitivity |
| spellingShingle | Alexis Tantet Marc Stéfanon Philippe Drobinski Jordi Badosa Silvia Concettini Anna Cretì Claudia D’Ambrosio Dimitri Thomopulos Peter Tankov <span style="font-variant: small-caps">e</span>4<span style="font-variant: small-caps">clim</span> 1.0: The Energy for a Climate Integrated Model: Description and Application to Italy Energies renewable energy climate variability energy mix mean-variance sensitivity |
| title | <span style="font-variant: small-caps">e</span>4<span style="font-variant: small-caps">clim</span> 1.0: The Energy for a Climate Integrated Model: Description and Application to Italy |
| title_full | <span style="font-variant: small-caps">e</span>4<span style="font-variant: small-caps">clim</span> 1.0: The Energy for a Climate Integrated Model: Description and Application to Italy |
| title_fullStr | <span style="font-variant: small-caps">e</span>4<span style="font-variant: small-caps">clim</span> 1.0: The Energy for a Climate Integrated Model: Description and Application to Italy |
| title_full_unstemmed | <span style="font-variant: small-caps">e</span>4<span style="font-variant: small-caps">clim</span> 1.0: The Energy for a Climate Integrated Model: Description and Application to Italy |
| title_short | <span style="font-variant: small-caps">e</span>4<span style="font-variant: small-caps">clim</span> 1.0: The Energy for a Climate Integrated Model: Description and Application to Italy |
| title_sort | span style font variant small caps e span 4 span style font variant small caps clim span 1 0 the energy for a climate integrated model description and application to italy |
| topic | renewable energy climate variability energy mix mean-variance sensitivity |
| url | https://www.mdpi.com/1996-1073/12/22/4299 |
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