Tomasz Weron : Citation Profile


Are you Tomasz Weron?

Politechnika Wrocławska (50% share)
Politechnika Wrocławska (50% share)

5

H index

3

i10 index

87

Citations

RESEARCH PRODUCTION:

6

Articles

4

Papers

RESEARCH ACTIVITY:

   8 years (2013 - 2021). See details.
   Cites by year: 10
   Journals where Tomasz Weron has often published
   Relations with other researchers
   Recent citing documents: 13.    Total self citations: 6 (6.45 %)

MORE DETAILS IN:
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   Permalink: http://citec.repec.org/pwe470
   Updated: 2024-01-16    RAS profile: 2022-04-25    
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Relations with other researchers


Works with:

Nitka, Weronika (5)

Maciejowska, Katarzyna (3)

Weron, Rafał (2)

Serafin, Tomasz (2)

Authors registered in RePEc who have co-authored more than one work in the last five years with Tomasz Weron.

Is cited by:

Weron, Rafał (17)

Uniejewski, Bartosz (11)

Marcjasz, Grzegorz (9)

Maciejowska, Katarzyna (7)

Sznajd-Weron, Katarzyna (7)

Kowalska-Pyzalska, Anna (6)

Serafin, Tomasz (6)

Janczura, Joanna (5)

Nitka, Weronika (4)

Chawla, Yash (3)

Bertsch, Valentin (2)

Cites to:

Weron, Rafał (76)

Marcjasz, Grzegorz (23)

Uniejewski, Bartosz (23)

Sznajd-Weron, Katarzyna (19)

Serafin, Tomasz (17)

Nowotarski, Jakub (13)

Gianfreda, Angelica (13)

Maciejowska, Katarzyna (10)

Paraschiv, Florentina (10)

Pelagatti, Matteo (9)

Nitka, Weronika (6)

Main data


Where Tomasz Weron has published?


Journals with more than one article published# docs
Physica A: Statistical Mechanics and its Applications2
Energies2

Working Papers Series with more than one paper published# docs
HSC Research Reports / Hugo Steinhaus Center, Wroclaw University of Technology4

Recent works citing Tomasz Weron (2024 and 2023)


YearTitle of citing document
2023Smoothing Quantile Regression Averaging: A new approach to probabilistic forecasting of electricity prices. (2023). Uniejewski, Bartosz. In: Papers. RePEc:arx:papers:2302.00411.

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2023Enhancing Energy System Models Using Better Load Forecasts. (2023). Musgens, Felix ; Grothe, Oliver ; Watermeyer, Mira ; Mobius, Thomas. In: Papers. RePEc:arx:papers:2302.11017.

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2023A hybrid model for day-ahead electricity price forecasting: Combining fundamental and stochastic modelling. (2023). Musgens, Felix ; Grothe, Oliver ; Mobius, Thomas ; Watermeyer, Mira. In: Papers. RePEc:arx:papers:2304.09336.

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2023Combining predictive distributions of electricity prices: Does minimizing the CRPS lead to optimal decisions in day-ahead bidding?. (2023). Weron, Rafal ; Nitka, Weronika. In: Papers. RePEc:arx:papers:2308.15443.

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2023Multivariable short-term electricity price forecasting using artificial intelligence and multi-input multi-output scheme. (2023). Huang, Xiaojia ; Wang, Jianzhou ; Nie, Ying ; Jiang, Ping. In: Energy Economics. RePEc:eee:eneeco:v:117:y:2023:i:c:s0140988322006004.

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2023From point forecasts to multivariate probabilistic forecasts: The Schaake shuffle for day-ahead electricity price forecasting. (2023). Kruger, Fabian ; Kachele, Fabian ; Grothe, Oliver. In: Energy Economics. RePEc:eee:eneeco:v:120:y:2023:i:c:s0140988323001007.

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2023Distributional neural networks for electricity price forecasting. (2023). Weron, Rafał ; Ziel, Florian ; Narajewski, Micha ; Marcjasz, Grzegorz. In: Energy Economics. RePEc:eee:eneeco:v:125:y:2023:i:c:s0140988323003419.

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2023Forecasting electricity prices with expert, linear, and nonlinear models. (2023). Ravazzolo, Francesco ; del Grosso, Filippo ; Gianfreda, Angelica ; Bille, Anna Gloria. In: International Journal of Forecasting. RePEc:eee:intfor:v:39:y:2023:i:2:p:570-586.

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2023Conversion of anaerobic digestates from biogas plants: Laboratory fertilizer formulation, scale-up and demonstration of applicative properties on plants. (2023). Gil, Filip ; Mikula, Katarzyna ; Trzaska, Krzysztof ; Skrzypczak, Dawid ; Chojnacka, Katarzyna ; Witek-Krowiak, Anna ; Moustakas, Konstantinos ; Polomska, Xymena ; Mironiuk, Magorzata ; Izydorczyk, Grzegorz. In: Renewable Energy. RePEc:eee:renene:v:203:y:2023:i:c:p:506-517.

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2023A Predictive Fuzzy Logic Model for Forecasting Electricity Day-Ahead Market Prices for Scheduling Industrial Applications. (2023). Birbas, Alexios ; Alefragis, Panayiotis ; Karampinis, Ioannis ; Plakas, Konstantinos ; Papalexopoulos, Alex. In: Energies. RePEc:gam:jeners:v:16:y:2023:i:10:p:4085-:d:1146667.

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2023ARX-GARCH Probabilistic Price Forecasts for Diversification of Trade in Electricity Markets—Variance Stabilizing Transformation and Financial Risk-Minimizing Portfolio Allocation. (2023). Janczura, Joanna ; Pu, Andrzej. In: Energies. RePEc:gam:jeners:v:16:y:2023:i:2:p:807-:d:1031193.

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2023Intraday power trading: toward an arms race in weather forecasting?. (2023). Wozabal, David ; Kuppelwieser, Thomas. In: OR Spectrum: Quantitative Approaches in Management. RePEc:spr:orspec:v:45:y:2023:i:1:d:10.1007_s00291-022-00698-5.

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Works by Tomasz Weron:


YearTitleTypeCited
2021Enhancing load, wind and solar generation for day-ahead forecasting of electricity prices In: Energy Economics.
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article21
2018The role of educational trainings in the diffusion of smart metering platforms: An agent-based modeling approach In: Physica A: Statistical Mechanics and its Applications.
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article6
2017The role of educational trainings in the diffusion of smart metering platforms: An agent-based modeling approach.(2017) In: HSC Research Reports.
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This paper has nother version. Agregated cites: 6
paper
2021A review on the Sznajd model — 20 years after In: Physica A: Statistical Mechanics and its Applications.
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article0
2019Day-Ahead vs. Intraday—Forecasting the Price Spread to Maximize Economic Benefits In: Energies.
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article36
2020Balancing Generation from Renewable Energy Sources: Profitability of an Energy Trader In: Energies.
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article12
2016The Interplay Between Conformity and Anticonformity and its Polarizing Effect on Society In: Journal of Artificial Societies and Social Simulation.
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article5
2013Rewiring the network. What helps an innovation to diffuse? In: HSC Research Reports.
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paper7
2019Balancing RES generation: Profitability of an energy trader In: HSC Research Reports.
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paper0
2019Enhancing load, wind and solar generation forecasts in day-ahead forecasting of spot and intraday electricity prices In: HSC Research Reports.
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paper0

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