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Simulation of transcontinental wind and solar PV generation time series

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  • Nuño, Edgar
  • Maule, Petr
  • Hahmann, Andrea
  • Cutululis, Nicolaos
  • Sørensen, Poul
  • Karagali, Ioanna

Abstract

The deployment of Renewable Energy Sources (RES) is driving modern power systems towards a fundamental green transition. In this regard, there is a need to develop models to accurately capture the variability of wind and solar photovoltaic (PV) power, at different geographical and temporal scales. This paper presents a general methodology based on meteorological reanalysis techniques allowing to simulate aggregated RES time series over large geographical areas. It also introduces a novel PV conversion approach based on aggregated power curves in order to capture the uncertainty associated to the technical characteristics of individual installations spread across large regions. The proposed methodology is validated using actual power data in Europe and can be applied to represent intermittent generation in network development plans, reliability and market studies, as well as operational guidelines.

Suggested Citation

  • Nuño, Edgar & Maule, Petr & Hahmann, Andrea & Cutululis, Nicolaos & Sørensen, Poul & Karagali, Ioanna, 2018. "Simulation of transcontinental wind and solar PV generation time series," Renewable Energy, Elsevier, vol. 118(C), pages 425-436.
    • Handle: RePEc:eee:renene:v:118:y:2018:i:c:p:425-436
    DOI: 10.1016/j.renene.2017.11.039
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    References listed on IDEAS

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    1. Matti Koivisto & Kaushik Das & Feng Guo & Poul Sørensen & Edgar Nuño & Nicolaos Cutululis & Petr Maule, 2019. "Using time series simulation tools for assessing the effects of variable renewable energy generation on power and energy systems," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 8(3), May.
    2. Gea-Bermúdez, Juan & Bramstoft, Rasmus & Koivisto, Matti & Kitzing, Lena & Ramos, Andrés, 2023. "Going offshore or not: Where to generate hydrogen in future integrated energy systems?," Energy Policy, Elsevier, vol. 174(C).
    3. Russell McKenna & Stefan Pfenninger & Heidi Heinrichs & Johannes Schmidt & Iain Staffell & Katharina Gruber & Andrea N. Hahmann & Malte Jansen & Michael Klingler & Natascha Landwehr & Xiaoli Guo Lars', 2021. "Reviewing methods and assumptions for high-resolution large-scale onshore wind energy potential assessments," Papers 2103.09781, arXiv.org.
    4. Olsen, Karen Pardos & Zong, Yi & You, Shi & Bindner, Henrik & Koivisto, Matti & Gea-Bermúdez, Juan, 2020. "Multi-timescale data-driven method identifying flexibility requirements for scenarios with high penetration of renewables," Applied Energy, Elsevier, vol. 264(C).
    5. McKenna, Russell & Pfenninger, Stefan & Heinrichs, Heidi & Schmidt, Johannes & Staffell, Iain & Bauer, Christian & Gruber, Katharina & Hahmann, Andrea N. & Jansen, Malte & Klingler, Michael & Landwehr, 2022. "High-resolution large-scale onshore wind energy assessments: A review of potential definitions, methodologies and future research needs," Renewable Energy, Elsevier, vol. 182(C), pages 659-684.
    6. Romano, E. & Mutschler, R. & Hollmuller, P. & Sulzer, M. & Orehounig, K. & Rüdisüli, M., 2024. "Spatial carbon and price spillovers among EU countries on their pathway toward net-zero electricity supply," Energy Economics, Elsevier, vol. 131(C).
    7. Aqdas Naz & Nadeem Javaid & Muhammad Babar Rasheed & Abdul Haseeb & Musaed Alhussein & Khursheed Aurangzeb, 2019. "Game Theoretical Energy Management with Storage Capacity Optimization and Photo-Voltaic Cell Generated Power Forecasting in Micro Grid," Sustainability, MDPI, vol. 11(10), pages 1-22, May.
    8. Murcia, Juan Pablo & Koivisto, Matti Juhani & Luzia, Graziela & Olsen, Bjarke T. & Hahmann, Andrea N. & Sørensen, Poul Ejnar & Als, Magnus, 2022. "Validation of European-scale simulated wind speed and wind generation time series," Applied Energy, Elsevier, vol. 305(C).
    9. Swisher, Philip & Murcia Leon, Juan Pablo & Gea-Bermúdez, Juan & Koivisto, Matti & Madsen, Helge Aagaard & Münster, Marie, 2022. "Competitiveness of a low specific power, low cut-out wind speed wind turbine in North and Central Europe towards 2050," Applied Energy, Elsevier, vol. 306(PB).
    10. Sneum, Daniel Møller & González, Mario Garzón & Gea-Bermúdez, Juan, 2021. "Increased heat-electricity sector coupling by constraining biomass use?," Energy, Elsevier, vol. 222(C).
    11. Olauson, Jon, 2018. "ERA5: The new champion of wind power modelling?," Renewable Energy, Elsevier, vol. 126(C), pages 322-331.

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