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Proposal of a regional grid cluster model for analysis of electrical power network performance

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper provides a method for simplified description of a regional power grid model aimed to deliver a grid reduction, and improve grid performance observability. The derived power grid model can be used to analyze the regional allocation of the decentralized energy generation and consumption. The expansion of wind and solar generation in the power system affects the residual load. The power balance between electricity consumption and generation was calculated and analyzed based on the temporal and spatial scales. The proposed grid clustering method is a useful approach for performance analysis in systems with a growing share of renewable generation.
Rocznik
Strony
601--613
Opis fizyczny
Bibliogr. 29 poz., rys., tab.
Twórcy
autor
  • Brandenburg University of Technology Cottbus-Senftenberg, Department of Energy Distribution and High Voltage Engineering, 03046 Cottbus, Germany
  • Wrocław University of Science and Technology, Department of Electrical Engineering Fundamentals, 50-377 Wrocław, Poland
  • Brandenburg University of Technology Cottbus-Senftenberg, Department of Energy Distribution and High Voltage Engineering, 03046 Cottbus, Germany
  • Brandenburg University of Technology Cottbus-Senftenberg, Department of Energy Distribution and High Voltage Engineering, 03046 Cottbus, Germany
Bibliografia
  • [1] Gielen D., Boshell F., Saygin D., Bazilian M., Wagner N., Gorini R., The role of renewable energy in the global energy transformation, Energy Strategy Reviews, vol. 24, pp. 38–50 (2019), DOI: 10.1016/j.esr.2019.01.006.
  • [2] Yu B., Fang D., Yu H., Zhao C., Temporal-spatial determinants of renewable energy penetration in electricity production: Evidence from EU countries, Renewable Energy, vol. 180, pp. 438–451 (2021), DOI: 10.1016/j.renene.2021.08.079.
  • [3] Schwarz H., Cai X., Integration of renewable energies, flexible loads and storages into the German power grid: Actual situation in German change of power system, Frontiers in Energy, vol. 11, pp. 107–118 (2017), DOI: 10.1007/s11708-017-0470-x.
  • [4] Heuck K., Dettmann K.D., Schulz D., Elektrische Energieversorgung, Vieweg Teubner Publisher (2007).
  • [5] https://www.bundesnetzagentur.de/DE/Sachgebiete/ElektrizitaetundGas/Unternehmen_Institutionen/ErneuerbareEnergien/ZahlenDatenInformationen/start.html, accessed December 2021.
  • [6] Suresh G., Prasad D., Gopila M., An efficient approach based power flow management in smart grid system with hybrid renewable energy sources, Renewable Energy Focus, vol. 39, pp. 110–122 (2021), DOI: 10.1016/j.ref.2021.07.009.
  • [7] Shair J., Li H., Hu J., Xie X., Power system stability issues, classifications and research prospects in the context of high-penetration of renewables and power electronics, Renewable and Sustainable Energy Reviews, vol. 145, DOI: 10.1016/j.rser.2021.111111.
  • [8] Chen C., Xue B., Cai G., Thomas H., Stückrad S., Comparing the energy transitions in Germany and China: Synergies and recommendations, Energy Reports, vol. 5, pp. 1249–1260 (2019), DOI: 10.1016/j.egyr.2019.08.087.
  • [9] Federal Ministry of Economic Affairs and Energy (BMWi), Final Report of Coal Commission: Kommission Wachstum, Strukturwandel und Beschäftigung (2019).
  • [10] Schwarz H., Will Germany move into a situation with unsecured power supply, Frontiers in Energy, pp. 551–570 (2019), DOI: 10.1007/s11708-019-0641-z.
  • [11] German National Grid Agency, National Grid Development Plan NEP 2035, Version 2021, second draft, BNetzA (2021).
  • [12] https://www.netztransparenz.de/EEG/Jahresabrechnungen, accessed December 2021.
  • [13] https://www.foederal-erneuerbar.de/uebersicht/bundeslaender/, accessed December 2021.
  • [14] https://www.umweltbundesamt.de/bild/anteil-erneuerbarer-energien-am-0, accessed December 2021.
  • [15] Bett P., Thornton H., The climatological relationships between wind and solar energy supply in Britain, Renewable Energy, vol. 87, part 1, pp. 96–110 (2016), DOI: 10.1016/j.renene.2015.10.006.
  • [16] Beer M., Regionalisiertes Energiemodell zur Analyse der flexiblen Betriebsweise von Kraft-Wärme Kopplungsanlagen, PhD Thesis, Faculty of Electrical Engineering and Information Technology, Technical University of Munich, Munich (2012).
  • [17] Schmid T., Dynamische und kleinräumige Modellierung der aktuellen und zukünftigen Energienach frage und Stromerzeugung aus Erneuerbaren Energien, PhD Thesis, Faculty of Electrical Engineering and Information Technology, Technical University of Munich, Munich (2019).
  • [18] Alhamwi A., Medjroubi W., Vogt T., Agert C., Modelling urban energy requirements using open source data and models, Applied Energy, vol. 231, pp. 1100–1108 (2018), DOI: 10.1016/j.apenergy.2018.09.164.
  • [19] Medjroubi W., Müller U., Scharf M., Matke C., Kleinhans D., Open Data in Power Grid Modelling: New Approaches Towards Transparent Grid Models, Energy Reports, vol.3, pp. 14–21 (2017), DOI: 10.1016/j.egyr.2016.12.001.
  • [20] Biener W., Rosas K., Grid reduction for energy system analysis, Electric Power Systems Research, vol. 185 (2020), DOI: 10.1016/j.epsr.2020.106349.
  • [21] Alhamwi A., Medjroubi W., Vogt T., Agert C., Development of a GIS-based platform for the allocation and optimisation of distributed storage in urban energy systems, Applied Energy, vol. 251 (2019), DOI: 10.1016/j.apenergy.2019.113360.
  • [22] Wu Q., Zheng J., Jing Z., Zhou X., Large-Scale Integrated Energy Systems, Springer Nature Singapore Pte Ltd. (2019).
  • [23] Amanpour S., Huck D., Kuprat M., Schwarz H., Integrated energy in Germany – A critical look at the development and state of integrated energies in Germany, Frontiers in Energy, vol. 12, pp. 493–500 (2018), DOI: 10.1007/s11708-018-0570-2.
  • [24] Jérémy A., Sabouret N., Haradji Y., Multi-agent simulation of collective self-consumption: Impacts of storage systems and large-scale energy exchanges, Energy and Buildings, vol. 254 (2021), DOI: 10.1016/j.enbuild.2021.111543.
  • [25] Wu K., Zhou H., A multi-agent-based energy-coordination control system for grid-connected large scale wind–photovoltaic energy storage power-generation units, Solar Energy, vol. 107, pp. 245–259 (2014), DOI: 10.1016/j.solener.2014.05.012.
  • [26] Azeroual M., Lamhamdi T., El Moussaoui H., Markhi H., Intelligent energy management system of a smart microgrid using multiagent systems, Archives of Electrical Engineering, vol. 69, no. 1, pp. 23–38 (2020), DOI: 10.24425/aee.2020.131756.
  • [27] Rugles T.H., Caldeira K., Wind and solar generation may reduce the inter-annual variability of peak residual load in certain electricity systems, Applied Energy, vol. 305 (2022), DOI: m10.1016/j.apenergy.2021.117773.
  • [28] Su H., Chi L., Zio E., An integrated, systematic data-driven supply-demand side management method for smart integrated energy systems, Energy, vol. 235 (2021), DOI: 10.1016/j.energy.2021.121416.
  • [29] https://www.marktstammdatenregister.de/MaStR, accessed December 2021
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-340f98ea-72e9-4797-9087-6135df4a6b24
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