IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i15p3949-d393231.html
   My bibliography  Save this article

Transmission Power System Modeling by Using Aggregated Distributed Generation Model Based on a TSO—DSO Data Exchange Scheme

Author

Listed:
  • Srđan Skok

    (Department of Electrical Engineering, University North, 42000 Varaždin, Croatia)

  • Ahmed Mutapčić

    (Public Enterprise Electric Utility of Bosnia and Herzegovina, 71000 Sarajevo, Bosnia and Herzegovina)

  • Renata Rubesa

    (Croatian Transmission System Operator, 10000 Zagreb, Croatia)

  • Mario Bazina

    (Schneider Electric d.o.o., 10000 Zagreb, Croatia)

Abstract

By integrating distributed energy resources (DER, mostly renewable energy sources) in the depth of the distribution network transmission system operators (TSOs), planning and control of transmission systems has been greatly hindered due to the lack of knowledge about the circumstances at the transmission and distribution network’s interface and the lack of coordination with the distribution system operator (DSO). By adopting the Commission Regulation (EU) 2017/1485 (System Operational Guideline—SOGL) establishing a guideline on electricity transmission system operation, harmonized rules on system operation for TSOs, DSOs and significant grid users (SGUs) are set out, inter alia, in order to provide a clear legal framework for the exchange of necessary data and information between the aforementioned subjects. In this paper, the methodology of DER representation at the interface of the transmission and distributed system is presented, with the indicated interactive data exchange between TSO and DSO, for running and analyzing the operation of the entire power system (PS) in real and extended real time. The proposed methodology was tested on a real model of the Croatian transmission PS and with representative DER in the depth of the distribution network.

Suggested Citation

  • Srđan Skok & Ahmed Mutapčić & Renata Rubesa & Mario Bazina, 2020. "Transmission Power System Modeling by Using Aggregated Distributed Generation Model Based on a TSO—DSO Data Exchange Scheme," Energies, MDPI, vol. 13(15), pages 1-15, August.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:15:p:3949-:d:393231
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/15/3949/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/15/3949/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. David Wozabal & Christoph Graf & David Hirschmann, 2016. "The effect of intermittent renewables on the electricity price variance," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 38(3), pages 687-709, July.
    2. Giuditta Pisano & Nayeem Chowdhury & Massimiliano Coppo & Nicola Natale & Giacomo Petretto & Gian Giuseppe Soma & Roberto Turri & Fabrizio Pilo, 2019. "Synthetic Models of Distribution Networks Based on Open Data and Georeferenced Information," Energies, MDPI, vol. 12(23), pages 1-24, November.
    3. Grossi, Luigi & Nan, Fany, 2019. "Robust forecasting of electricity prices: Simulations, models and the impact of renewable sources," Technological Forecasting and Social Change, Elsevier, vol. 141(C), pages 305-318.
    4. Loßner, Martin & Böttger, Diana & Bruckner, Thomas, 2017. "Economic assessment of virtual power plants in the German energy market — A scenario-based and model-supported analysis," Energy Economics, Elsevier, vol. 62(C), pages 125-138.
    5. Shayegan-Rad, Ali & Badri, Ali & Zangeneh, Ali, 2017. "Day-ahead scheduling of virtual power plant in joint energy and regulation reserve markets under uncertainties," Energy, Elsevier, vol. 121(C), pages 114-125.
    6. Notton, Gilles & Nivet, Marie-Laure & Voyant, Cyril & Paoli, Christophe & Darras, Christophe & Motte, Fabrice & Fouilloy, Alexis, 2018. "Intermittent and stochastic character of renewable energy sources: Consequences, cost of intermittence and benefit of forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 87(C), pages 96-105.
    7. Liu, Yingqi, 2017. "Demand response and energy efficiency in the capacity resource procurement: Case studies of forward capacity markets in ISO New England, PJM and Great Britain," Energy Policy, Elsevier, vol. 100(C), pages 271-282.
    8. Lakshmanan, Venkatachalam & Marinelli, Mattia & Kosek, Anna M. & Nørgård, Per B. & Bindner, Henrik W., 2016. "Impact of thermostatically controlled loads' demand response activation on aggregated power: A field experiment," Energy, Elsevier, vol. 94(C), pages 705-714.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Francesco Gulotta & Edoardo Daccò & Alessandro Bosisio & Davide Falabretti, 2023. "Opening of Ancillary Service Markets to Distributed Energy Resources: A Review," Energies, MDPI, vol. 16(6), pages 1-25, March.
    2. Talal Alazemi & Mohamed Darwish & Mohammed Radi, 2022. "TSO/DSO Coordination for RES Integration: A Systematic Literature Review," Energies, MDPI, vol. 15(19), pages 1-26, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Diego Aineto & Javier Iranzo-Sánchez & Lenin G. Lemus-Zúñiga & Eva Onaindia & Javier F. Urchueguía, 2019. "On the Influence of Renewable Energy Sources in Electricity Price Forecasting in the Iberian Market," Energies, MDPI, vol. 12(11), pages 1-20, May.
    2. Fianu, Emmanuel Senyo & Ahelegbey, Daniel Felix & Grossi, Luigi, 2022. "Modeling risk contagion in the Italian zonal electricity market," European Journal of Operational Research, Elsevier, vol. 298(2), pages 656-679.
    3. Nallapaneni Manoj Kumar & Aneesh A. Chand & Maria Malvoni & Kushal A. Prasad & Kabir A. Mamun & F.R. Islam & Shauhrat S. Chopra, 2020. "Distributed Energy Resources and the Application of AI, IoT, and Blockchain in Smart Grids," Energies, MDPI, vol. 13(21), pages 1-42, November.
    4. Zhai, Chengwei & Chen, Thomas Ying-jeh & White, Anna Grace & Guikema, Seth David, 2021. "Power outage prediction for natural hazards using synthetic power distribution systems," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    5. Meyabadi, A. Fattahi & Deihimi, M.H., 2017. "A review of demand-side management: Reconsidering theoretical framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 367-379.
    6. Ghosh, Sourav & Yadav, Sarita & Devi, Ambika & Thomas, Tiju, 2022. "Techno-economic understanding of Indian energy-storage market: A perspective on green materials-based supercapacitor technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    7. Sara Bellocchi & Michele Manno & Michel Noussan & Michela Vellini, 2019. "Impact of Grid-Scale Electricity Storage and Electric Vehicles on Renewable Energy Penetration: A Case Study for Italy," Energies, MDPI, vol. 12(7), pages 1-32, April.
    8. Lu, Qing & Yu, Hao & Zhao, Kangli & Leng, Yajun & Hou, Jianchao & Xie, Pinjie, 2019. "Residential demand response considering distributed PV consumption: A model based on China's PV policy," Energy, Elsevier, vol. 172(C), pages 443-456.
    9. Costa, Marcelo Azevedo & Ruiz-Cárdenas, Ramiro & Mineti, Leandro Brioschi & Prates, Marcos Oliveira, 2021. "Dynamic time scan forecasting for multi-step wind speed prediction," Renewable Energy, Elsevier, vol. 177(C), pages 584-595.
    10. Paletta, Quentin & Arbod, Guillaume & Lasenby, Joan, 2023. "Omnivision forecasting: Combining satellite and sky images for improved deterministic and probabilistic intra-hour solar energy predictions," Applied Energy, Elsevier, vol. 336(C).
    11. Xiukang Wang, 2022. "Managing Land Carrying Capacity: Key to Achieving Sustainable Production Systems for Food Security," Land, MDPI, vol. 11(4), pages 1-21, March.
    12. Russo, Marianna & Bertsch, Valentin, 2020. "A looming revolution: Implications of self-generation for the risk exposure of retailers," Energy Economics, Elsevier, vol. 92(C).
    13. Pawlak-Kruczek, Halina & Niedźwiecki, Łukasz & Ostrycharczyk, Michał & Czerep, Michał & Plutecki, Zbigniew, 2019. "Potential and methods for increasing the flexibility and efficiency of the lignite fired power unit, using integrated lignite drying," Energy, Elsevier, vol. 181(C), pages 1142-1151.
    14. Hain, Martin & Kargus, Tobias & Schermeyer, Hans & Uhrig-Homburg, Marliese & Fichtner, Wolf, 2022. "An electricity price modeling framework for renewable-dominant markets," Working Paper Series in Production and Energy 66, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    15. Behnaz Behi & Ali Baniasadi & Ali Arefi & Arian Gorjy & Philip Jennings & Almantas Pivrikas, 2020. "Cost–Benefit Analysis of a Virtual Power Plant Including Solar PV, Flow Battery, Heat Pump, and Demand Management: A Western Australian Case Study," Energies, MDPI, vol. 13(10), pages 1-24, May.
    16. Ma, Teng & Li, Ming-Jia & Xu, Jin-Liang & Cao, Feng, 2019. "Thermodynamic analysis and performance prediction on dynamic response characteristic of PCHE in 1000 MW S-CO2 coal fired power plant," Energy, Elsevier, vol. 175(C), pages 123-138.
    17. Sun, Shitong & Kazemi-Razi, S. Mahdi & Kaigutha, Lisa G. & Marzband, Mousa & Nafisi, Hamed & Al-Sumaiti, Ameena Saad, 2022. "Day-ahead offering strategy in the market for concentrating solar power considering thermoelectric decoupling by a compressed air energy storage," Applied Energy, Elsevier, vol. 305(C).
    18. Jean-Laurent Duchaud & Cyril Voyant & Alexis Fouilloy & Gilles Notton & Marie-Laure Nivet, 2020. "Trade-Off between Precision and Resolution of a Solar Power Forecasting Algorithm for Micro-Grid Optimal Control," Energies, MDPI, vol. 13(14), pages 1-16, July.
    19. Yu, Bolin & Fang, Debin & Xiao, Kun & Pan, Yuling, 2023. "Drivers of renewable energy penetration and its role in power sector's deep decarbonization towards carbon peak," Renewable and Sustainable Energy Reviews, Elsevier, vol. 178(C).
    20. Gairaa, Kacem & Voyant, Cyril & Notton, Gilles & Benkaciali, Saïd & Guermoui, Mawloud, 2022. "Contribution of ordinal variables to short-term global solar irradiation forecasting for sites with low variabilities," Renewable Energy, Elsevier, vol. 183(C), pages 890-902.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:13:y:2020:i:15:p:3949-:d:393231. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.