TY  - 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 .

TY  - CONF
AU  - Parrado-Hernando, Gonzalo
AU  - Pfeifer, Antun
AU  - Herc, Luka
AU  - Gjorgievski, Vladimir
AU  - Batas-Bjelić, Ilija
AU  - Duić, Neven
AU  - Frechoso, Fernando
AU  - Miguel González, Luis Javier
AU  - Capellán-Perez, Iñigo
PY  - 2021
UR  - https://dais.sanu.ac.rs/123456789/12290
AB  - Working on holistic approaches that aim to capture a wide range of knowledge, researchers are usually faced with phenomena characterized by different time and geographical scales. This is the case of energy systems and Integrated Assessment Models (IAMs). More specifically, the nature of the variable renewable energy supply (VRES) has traditionally posed a barrier to accurately capturing the effects inflicted by VRES in the energy system. This research provides a soft link between an energy system model running with an hourly time step, on the one hand, and a yearly-based IAM, on the other hand, by the implementation of an emulator. The proposal here presented is a bridge, based on different types of knowledge, which successfully allows the flow of information between time scales. Results achieve a 100% renewable energy system on a case of Bulgaria. After a brief literature review on the topic, the method is explained in detail, including some results between EnergyPLAN (energy system model) and MEDEAS (Integrated Assessment Model, IAM) for Bulgaria. Results show that the ability of assessment is notably increased from the previous MEDEAS version. Finally, both results and limitations of this method are discussed. The authors hope this article captures interest in the field of IAMs, especially those which address with energy transition studies.
PB  - Zagreb : SDEWES
C3  - Proceedings of 16th Conference on Sustainable Development of Energy, Water and Environment Systems – SDEWES
T1  - Modelling of 100% Renewable Energy Systems in Integrated Assessment Models by multi-timeframe regression analysis
SP  - 0128
UR  - https://hdl.handle.net/21.15107/rcub_dais_12290
ER  - 

@conference{
author = "Parrado-Hernando, Gonzalo and Pfeifer, Antun and Herc, Luka and Gjorgievski, Vladimir and Batas-Bjelić, Ilija and Duić, Neven and Frechoso, Fernando and Miguel González, Luis Javier and Capellán-Perez, Iñigo",
year = "2021",
abstract = "Working on holistic approaches that aim to capture a wide range of knowledge, researchers are usually faced with phenomena characterized by different time and geographical scales. This is the case of energy systems and Integrated Assessment Models (IAMs). More specifically, the nature of the variable renewable energy supply (VRES) has traditionally posed a barrier to accurately capturing the effects inflicted by VRES in the energy system. This research provides a soft link between an energy system model running with an hourly time step, on the one hand, and a yearly-based IAM, on the other hand, by the implementation of an emulator. The proposal here presented is a bridge, based on different types of knowledge, which successfully allows the flow of information between time scales. Results achieve a 100% renewable energy system on a case of Bulgaria. After a brief literature review on the topic, the method is explained in detail, including some results between EnergyPLAN (energy system model) and MEDEAS (Integrated Assessment Model, IAM) for Bulgaria. Results show that the ability of assessment is notably increased from the previous MEDEAS version. Finally, both results and limitations of this method are discussed. The authors hope this article captures interest in the field of IAMs, especially those which address with energy transition studies.",
publisher = "Zagreb : SDEWES",
journal = "Proceedings of 16th Conference on Sustainable Development of Energy, Water and Environment Systems – SDEWES",
title = "Modelling of 100% Renewable Energy Systems in Integrated Assessment Models by multi-timeframe regression analysis",
pages = "0128",
url = "https://hdl.handle.net/21.15107/rcub_dais_12290"
}

Parrado-Hernando, G., Pfeifer, A., Herc, L., Gjorgievski, V., Batas-Bjelić, I., Duić, N., Frechoso, F., Miguel González, L. J.,& Capellán-Perez, I.. (2021). Modelling of 100% Renewable Energy Systems in Integrated Assessment Models by multi-timeframe regression analysis. in Proceedings of 16th Conference on Sustainable Development of Energy, Water and Environment Systems – SDEWES
Zagreb : SDEWES., 0128.
https://hdl.handle.net/21.15107/rcub_dais_12290

Parrado-Hernando G, Pfeifer A, Herc L, Gjorgievski V, Batas-Bjelić I, Duić N, Frechoso F, Miguel González LJ, Capellán-Perez I. Modelling of 100% Renewable Energy Systems in Integrated Assessment Models by multi-timeframe regression analysis. in Proceedings of 16th Conference on Sustainable Development of Energy, Water and Environment Systems – SDEWES. 2021;:0128.
https://hdl.handle.net/21.15107/rcub_dais_12290 .

Parrado-Hernando, Gonzalo, Pfeifer, Antun, Herc, Luka, Gjorgievski, Vladimir, Batas-Bjelić, Ilija, Duić, Neven, Frechoso, Fernando, Miguel González, Luis Javier, Capellán-Perez, Iñigo, "Modelling of 100% Renewable Energy Systems in Integrated Assessment Models by multi-timeframe regression analysis" in Proceedings of 16th Conference on Sustainable Development of Energy, Water and Environment Systems – SDEWES (2021):0128,
https://hdl.handle.net/21.15107/rcub_dais_12290 .