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Pregled bibliografske jedinice broj: 1211428

Capturing features of hourly-resolution energy models through statistical annual indicators

Parrado-Hernando, Gonzalo; Herc, Luka; Pfeifer, Antun; Capellán-Perez, Iñigo; Batas Bjelić, Ilija; Duić, Neven; Frechoso-Escudero, Fernando; Javier Miguel González, Luis; Z. Gjorgievski, Vladimir
Capturing features of hourly-resolution energy models through statistical annual indicators // Renewable energy, 197 (2022), 1192-1223 doi:10.1016/j.renene.2022.07.040 (međunarodna recenzija, članak, znanstveni)

CROSBI ID: 1211428 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Capturing features of hourly-resolution energy models through statistical annual indicators

Autori
Parrado-Hernando, Gonzalo ; Herc, Luka ; Pfeifer, Antun ; Capellán-Perez, Iñigo ; Batas Bjelić, Ilija ; Duić, Neven ; Frechoso-Escudero, Fernando ; Javier Miguel González, Luis ; Z. Gjorgievski, Vladimir

Izvornik
Renewable energy (0960-1481) 197 (2022); 1192-1223

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
EnergyPLAN, Integrated assessment model (IAM), 100% Renewables, Variable renewable energy supply, hourly resolution energy model

Sažetak
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.

Izvorni jezik
Engleski

Znanstvena područja
Strojarstvo



POVEZANOST RADA

Profili:

Avatar Url Luka Herc (autor)

Avatar Url Neven Duić (autor)

Avatar Url Antun Pfeifer (autor)

Poveznice na cjeloviti tekst rada:

doi www.sciencedirect.com www.sciencedirect.com

Citiraj ovu publikaciju:

Parrado-Hernando, Gonzalo; Herc, Luka; Pfeifer, Antun; Capellán-Perez, Iñigo; Batas Bjelić, Ilija; Duić, Neven; Frechoso-Escudero, Fernando; Javier Miguel González, Luis; Z. Gjorgievski, Vladimir
Capturing features of hourly-resolution energy models through statistical annual indicators // Renewable energy, 197 (2022), 1192-1223 doi:10.1016/j.renene.2022.07.040 (međunarodna recenzija, članak, znanstveni)
Parrado-Hernando, G., Herc, L., Pfeifer, A., Capellán-Perez, I., Batas Bjelić, I., Duić, N., Frechoso-Escudero, F., Javier Miguel González, L. & Z. Gjorgievski, V. (2022) Capturing features of hourly-resolution energy models through statistical annual indicators. Renewable energy, 197, 1192-1223 doi:10.1016/j.renene.2022.07.040.
@article{article, author = {Parrado-Hernando, Gonzalo and Herc, Luka and Pfeifer, Antun and Capell\'{a}n-Perez, I\~{n}igo and Batas Bjeli\'{c}, Ilija and Dui\'{c}, Neven and Frechoso-Escudero, Fernando and Javier Miguel Gonz\'{a}lez, Luis and Z. Gjorgievski, Vladimir}, year = {2022}, pages = {1192-1223}, DOI = {10.1016/j.renene.2022.07.040}, keywords = {EnergyPLAN, Integrated assessment model (IAM), 100\% Renewables, Variable renewable energy supply, hourly resolution energy model}, journal = {Renewable energy}, doi = {10.1016/j.renene.2022.07.040}, volume = {197}, issn = {0960-1481}, title = {Capturing features of hourly-resolution energy models through statistical annual indicators}, keyword = {EnergyPLAN, Integrated assessment model (IAM), 100\% Renewables, Variable renewable energy supply, hourly resolution energy model} }
@article{article, author = {Parrado-Hernando, Gonzalo and Herc, Luka and Pfeifer, Antun and Capell\'{a}n-Perez, I\~{n}igo and Batas Bjeli\'{c}, Ilija and Dui\'{c}, Neven and Frechoso-Escudero, Fernando and Javier Miguel Gonz\'{a}lez, Luis and Z. Gjorgievski, Vladimir}, year = {2022}, pages = {1192-1223}, DOI = {10.1016/j.renene.2022.07.040}, keywords = {EnergyPLAN, Integrated assessment model (IAM), 100\% Renewables, Variable renewable energy supply, hourly resolution energy model}, journal = {Renewable energy}, doi = {10.1016/j.renene.2022.07.040}, volume = {197}, issn = {0960-1481}, title = {Capturing features of hourly-resolution energy models through statistical annual indicators}, keyword = {EnergyPLAN, Integrated assessment model (IAM), 100\% Renewables, Variable renewable energy supply, hourly resolution energy model} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus

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