Capturing features of hourly-resolution energy models through statistical annual indicators
Само за регистроване кориснике
2022
Аутори
Parrado-Hernando, G.Herc, Luka
Pfeifer, Antun
Capellán-Perez, Iñigo
Batas Bjelić, Ilija
![](/themes/MirageDAIS/images/orcid.png)
Duić, Neven
![](/themes/MirageDAIS/images/orcid.png)
Frechoso-Escudero, Fernando
Miguel González, Luis Javier
Gjorgievski, Vladimir
Чланак у часопису (Објављена верзија)
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Метаподаци
Приказ свих података о документуАпстракт
Long term-energy planning has gradually moved towards finer temporal and spatial resolutions of the energy system to design the decarbonization of the society. However, integrated assessment models (IAMs), focusing on a broader concept of sustainability transition, are typically yearly-resolution models which complicates capturing the specific supply-demand dynamics, relevant in the transition towards renewable energy sources (RES). Different methods for introducing sub-annual information are being used in IAMs, but the hourly representation of variable RES remains challenging. This article presents a method to translate the main dynamics of an hourly-resolution energy model into a yearly-resolution model. Here we test our method with the current European Union region (EU-27) by configuring and applying the hourly-resolution EnergyPLAN. Multiple linear regression analysis is applied to 174960 simulations (set by varying 39 inputs by clusters and reaching 100% renewable systems), relati...ng the adjusted capacity factors of the technologies as well as the variation of electricity demand and natural gas consumption as a function of the options installed to manage the variable RES. The obtained results allow validation of the developed approach, which shows to be flexible and easily generalizable enough to be applied to any couple of hourly and annual-resolution models and/or country. © 2022 Elsevier Ltd
Кључне речи:
regression analysis / statistical analysis / sustainability / electricity / 100% renewables / alternative energy / electricity supply / energy model / energy planning / EnergyPLAN / European Union / Integrated assessment model / Integrated assessment model (IAM) / integrated assessment models / linear regression / natural gas / natural gas / natural gas wells / renewable energy resources / renewable energy sources / renewables / resolution modeling / variable renewable energies / Variable renewable energy source (VRES)Извор:
Renewable Energy, 2022, 197, 1192-1223Финансирање / пројекти:
- LOCOMOTION, funded through European Union's Horizon 2020 research and innovation programme, Grant No. 821105
- Juan de la Cierva-Incorporación Research Fellowship of the Ministry of Science and Innovation of Spain (no. IJC2020-046215-I)
Напомена:
- A preliminary version of this work was presented at the 16th SDEWES Conference Dubrovnik on Monday, October 11th, 2021, in room D (Energy system analysis 1) https://hdl.handle.net/21.15107/rcub_dais_12290
Институција/група
Институт техничких наука САНУ / Institute of Technical Sciences of SASATY - JOUR AU - Parrado-Hernando, G. AU - Herc, Luka AU - Pfeifer, Antun AU - Capellán-Perez, Iñigo AU - Batas Bjelić, Ilija AU - Duić, Neven AU - Frechoso-Escudero, Fernando AU - Miguel González, Luis Javier AU - Gjorgievski, Vladimir PY - 2022 UR - https://dais.sanu.ac.rs/123456789/13495 AB - Long term-energy planning has gradually moved towards finer temporal and spatial resolutions of the energy system to design the decarbonization of the society. However, integrated assessment models (IAMs), focusing on a broader concept of sustainability transition, are typically yearly-resolution models which complicates capturing the specific supply-demand dynamics, relevant in the transition towards renewable energy sources (RES). Different methods for introducing sub-annual information are being used in IAMs, but the hourly representation of variable RES remains challenging. This article presents a method to translate the main dynamics of an hourly-resolution energy model into a yearly-resolution model. Here we test our method with the current European Union region (EU-27) by configuring and applying the hourly-resolution EnergyPLAN. Multiple linear regression analysis is applied to 174960 simulations (set by varying 39 inputs by clusters and reaching 100% renewable systems), relating the adjusted capacity factors of the technologies as well as the variation of electricity demand and natural gas consumption as a function of the options installed to manage the variable RES. The obtained results allow validation of the developed approach, which shows to be flexible and easily generalizable enough to be applied to any couple of hourly and annual-resolution models and/or country. © 2022 Elsevier Ltd T2 - Renewable Energy T1 - Capturing features of hourly-resolution energy models through statistical annual indicators SP - 1192 EP - 1223 VL - 197 DO - 10.1016/j.renene.2022.07.040 UR - https://hdl.handle.net/21.15107/rcub_dais_13495 ER -
@article{ author = "Parrado-Hernando, G. and Herc, Luka and Pfeifer, Antun and Capellán-Perez, Iñigo and Batas Bjelić, Ilija and Duić, Neven and Frechoso-Escudero, Fernando and Miguel González, Luis Javier and Gjorgievski, Vladimir", year = "2022", abstract = "Long term-energy planning has gradually moved towards finer temporal and spatial resolutions of the energy system to design the decarbonization of the society. However, integrated assessment models (IAMs), focusing on a broader concept of sustainability transition, are typically yearly-resolution models which complicates capturing the specific supply-demand dynamics, relevant in the transition towards renewable energy sources (RES). Different methods for introducing sub-annual information are being used in IAMs, but the hourly representation of variable RES remains challenging. This article presents a method to translate the main dynamics of an hourly-resolution energy model into a yearly-resolution model. Here we test our method with the current European Union region (EU-27) by configuring and applying the hourly-resolution EnergyPLAN. Multiple linear regression analysis is applied to 174960 simulations (set by varying 39 inputs by clusters and reaching 100% renewable systems), relating the adjusted capacity factors of the technologies as well as the variation of electricity demand and natural gas consumption as a function of the options installed to manage the variable RES. The obtained results allow validation of the developed approach, which shows to be flexible and easily generalizable enough to be applied to any couple of hourly and annual-resolution models and/or country. © 2022 Elsevier Ltd", journal = "Renewable Energy", title = "Capturing features of hourly-resolution energy models through statistical annual indicators", pages = "1192-1223", volume = "197", doi = "10.1016/j.renene.2022.07.040", url = "https://hdl.handle.net/21.15107/rcub_dais_13495" }
Parrado-Hernando, G., Herc, L., Pfeifer, A., Capellán-Perez, I., Batas Bjelić, I., Duić, N., Frechoso-Escudero, F., Miguel González, L. J.,& Gjorgievski, V.. (2022). Capturing features of hourly-resolution energy models through statistical annual indicators. in Renewable Energy, 197, 1192-1223. https://doi.org/10.1016/j.renene.2022.07.040 https://hdl.handle.net/21.15107/rcub_dais_13495
Parrado-Hernando G, Herc L, Pfeifer A, Capellán-Perez I, Batas Bjelić I, Duić N, Frechoso-Escudero F, Miguel González LJ, Gjorgievski V. Capturing features of hourly-resolution energy models through statistical annual indicators. in Renewable Energy. 2022;197:1192-1223. doi:10.1016/j.renene.2022.07.040 https://hdl.handle.net/21.15107/rcub_dais_13495 .
Parrado-Hernando, G., Herc, Luka, Pfeifer, Antun, Capellán-Perez, Iñigo, Batas Bjelić, Ilija, Duić, Neven, Frechoso-Escudero, Fernando, Miguel González, Luis Javier, Gjorgievski, Vladimir, "Capturing features of hourly-resolution energy models through statistical annual indicators" in Renewable Energy, 197 (2022):1192-1223, https://doi.org/10.1016/j.renene.2022.07.040 ., https://hdl.handle.net/21.15107/rcub_dais_13495 .
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