IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i4p1014-d499791.html
   My bibliography  Save this article

Determination of Price Zones during Transition from Uniform to Zonal Electricity Market: A Case Study for Turkey

Author

Listed:
  • Gokturk Poyrazoglu

    (Electrical & Electronics Engineering, Ozyegin University, Istanbul 34794, Turkey)

Abstract

In the electricity market, different pricing models can be applied to increase market competitiveness. Different electricity systems use different market structures. Uniform marginal pricing, zonal marginal pricing, and nodal marginal pricing methods are commonly used market structures. For markets wishing to move from a uniform pricing structure to a more competitive zonal pricing structure, the determination of price zones is critical for achieving a competitive market that generates accurate price signals. Three different pricing zone detection algorithms are analyzed in this paper including the k -means clustering and queen/rook spatially constraint clustering. Finally, the results of a case study for the Turkish electricity system are shared to compare each method.

Suggested Citation

  • Gokturk Poyrazoglu, 2021. "Determination of Price Zones during Transition from Uniform to Zonal Electricity Market: A Case Study for Turkey," Energies, MDPI, vol. 14(4), pages 1-13, February.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:4:p:1014-:d:499791
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/4/1014/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/4/1014/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shengkun Xie, 2019. "Defining Geographical Rating Territories in Auto Insurance Regulation by Spatially Constrained Clustering," Risks, MDPI, vol. 7(2), pages 1-20, April.
    2. Robert Tibshirani & Guenther Walther & Trevor Hastie, 2001. "Estimating the number of clusters in a data set via the gap statistic," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(2), pages 411-423.
    3. Zhengwei Qu & Hongwen Li & Yunjing Wang & Jiaxi Zhang & Ahmed Abu-Siada & Yunxiao Yao, 2020. "Detection of Electricity Theft Behavior Based on Improved Synthetic Minority Oversampling Technique and Random Forest Classifier," Energies, MDPI, vol. 13(8), pages 1-20, April.
    4. Gianluca Trotta & Kirsten Gram-Hanssen & Pernille Lykke Jørgensen, 2020. "Heterogeneity of Electricity Consumption Patterns in Vulnerable Households," Energies, MDPI, vol. 13(18), pages 1-17, September.
    5. Bae-Geun Lee & Joonwoo Lee & Soobae Kim, 2020. "Development of a Static Equivalent Model for Korean Power Systems Using Power Transfer Distribution Factor-Based k -Means++ Algorithm," Energies, MDPI, vol. 13(24), pages 1-12, December.
    6. Piotr F. Borowski, 2020. "Zonal and Nodal Models of Energy Market in European Union," Energies, MDPI, vol. 13(16), pages 1-21, August.
    7. Bublitz, Andreas & Keles, Dogan & Zimmermann, Florian & Fraunholz, Christoph & Fichtner, Wolf, 2019. "A survey on electricity market design: Insights from theory and real-world implementations of capacity remuneration mechanisms," Energy Economics, Elsevier, vol. 80(C), pages 1059-1078.
    8. Maher AbuBaker, 2019. "Data Mining Applications in Understanding Electricity Consumers’ Behavior: A Case Study of Tulkarm District, Palestine," Energies, MDPI, vol. 12(22), pages 1-29, November.
    9. Robert Thorndike, 1953. "Who belongs in the family?," Psychometrika, Springer;The Psychometric Society, vol. 18(4), pages 267-276, December.
    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. Moein Shamoushaki & Pouriya H. Niknam & Lorenzo Talluri & Giampaolo Manfrida & Daniele Fiaschi, 2021. "Development of Cost Correlations for the Economic Assessment of Power Plant Equipment," Energies, MDPI, vol. 14(9), pages 1-19, May.
    2. Hansol Shin & Tae Hyun Kim & Kyuhyeong Kwag & Wook Kim, 2021. "A Comparative Study of Pricing Mechanisms to Reduce Side-Payments in the Electricity Market: A Case Study for South Korea," Energies, MDPI, vol. 14(12), pages 1-19, June.
    3. Qingle Pang & Lin Ye & Houlei Gao & Xinian Li & Yang Zheng & Chenbin He, 2021. "Penalty Electricity Price-Based Optimal Control for Distribution Networks," Energies, MDPI, vol. 14(7), pages 1-16, March.
    4. Štefan Bojnec, 2023. "Electricity Markets, Electricity Prices and Green Energy Transition," Energies, MDPI, vol. 16(2), pages 1-4, January.
    5. Samar Fatima & Verner Püvi & Ammar Arshad & Mahdi Pourakbari-Kasmaei & Matti Lehtonen, 2021. "Comparison of Economical and Technical Photovoltaic Hosting Capacity Limits in Distribution Networks," Energies, MDPI, vol. 14(9), pages 1-23, April.

    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. Orietta Nicolis & Jean Paul Maidana & Fabian Contreras & Danilo Leal, 2024. "Analyzing the Impact of COVID-19 on Economic Sustainability: A Clustering Approach," Sustainability, MDPI, vol. 16(4), pages 1-30, February.
    2. Dario Cottafava & Giulia Sonetti & Paolo Gambino & Andrea Tartaglino, 2018. "Explorative Multidimensional Analysis for Energy Efficiency: DataViz versus Clustering Algorithms," Energies, MDPI, vol. 11(5), pages 1-18, May.
    3. Arévalo, Franklim & Barucca, Paolo & Téllez-León, Isela-Elizabeth & Rodríguez, William & Gage, Gerardo & Morales, Raúl, 2022. "Identifying clusters of anomalous payments in the salvadorian payment system," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 3(1).
    4. Isakov , Alexander, 2013. "Stress indicator construction for internal money market," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 30(2), pages 77-92.
    5. Mr. Emre Alper & Michal Miktus, 2019. "Digital Connectivity in sub-Saharan Africa: A Comparative Perspective," IMF Working Papers 2019/210, International Monetary Fund.
    6. Teichgraeber, Holger & Brandt, Adam R., 2022. "Time-series aggregation for the optimization of energy systems: Goals, challenges, approaches, and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    7. Anis Hoayek & Didier Rullière, 2024. "Assessing clustering methods using Shannon's entropy," Post-Print hal-03812055, HAL.
    8. Alfred Kume & Stephen G Walker, 2021. "The utility of clusters and a Hungarian clustering algorithm," PLOS ONE, Public Library of Science, vol. 16(8), pages 1-23, August.
    9. Tomislava Pavić Kramarić & Mirjana Pejić Bach & Ksenija Dumičić & Berislav Žmuk & Maja Mihelja Žaja, 2018. "Exploratory study of insurance companies in selected post-transition countries: non-hierarchical cluster analysis," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(3), pages 783-807, September.
    10. Rodolfo Metulini & Giorgio Gnecco & Francesco Biancalani & Massimo Riccaboni, 2023. "Hierarchical clustering and matrix completion for the reconstruction of world input–output tables," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 107(3), pages 575-620, September.
    11. Loukas Triantafyllopoulos & Evgenia Paxinou & Georgios Feretzakis & Dimitris Kalles & Vassilios S. Verykios, 2024. "Mapping How Artificial Intelligence Blends with Healthcare: Insights from a Bibliometric Analysis," Future Internet, MDPI, vol. 16(7), pages 1-33, June.
    12. Douglas Steinley, 2007. "Validating Clusters with the Lower Bound for Sum-of-Squares Error," Psychometrika, Springer;The Psychometric Society, vol. 72(1), pages 93-106, March.
    13. Lucas Czech & Alexandros Stamatakis, 2019. "Scalable methods for analyzing and visualizing phylogenetic placement of metagenomic samples," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-50, May.
    14. Nazim Hajiyev & Manafova Mansura & Elena Sverdlikova & Roman Safronov & Tatyana Vityutina, 2021. "Oligopoly Trends in Energy Markets: Causes, Crisis of Competition, and Sectoral Development Strategies," International Journal of Energy Economics and Policy, Econjournals, vol. 11(6), pages 392-400.
    15. Divinus Oppong-Tawiah & Jane Webster, 2023. "Corporate Sustainability Communication as ‘Fake News’: Firms’ Greenwashing on Twitter," Sustainability, MDPI, vol. 15(8), pages 1-26, April.
    16. Shengkun Xie, 2021. "Improving Explainability of Major Risk Factors in Artificial Neural Networks for Auto Insurance Rate Regulation," Risks, MDPI, vol. 9(7), pages 1-21, July.
    17. Koecklin, Manuel Tong & Longoria, Genaro & Fitiwi, Desta Z. & DeCarolis, Joseph F. & Curtis, John, 2021. "Public acceptance of renewable electricity generation and transmission network developments: Insights from Ireland," Energy Policy, Elsevier, vol. 151(C).
    18. Thiemo Fetzer & Samuel Marden, 2017. "Take What You Can: Property Rights, Contestability and Conflict," Economic Journal, Royal Economic Society, vol. 0(601), pages 757-783, May.
    19. Daniel Agness & Travis Baseler & Sylvain Chassang & Pascaline Dupas & Erik Snowberg, 2022. "Valuing the Time of the Self-Employed," Working Papers 2022-2, Princeton University. Economics Department..
    20. Khanh Duong, 2024. "Is meritocracy just? New evidence from Boolean analysis and Machine learning," Journal of Computational Social Science, Springer, vol. 7(2), pages 1795-1821, October.

    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:14:y:2021:i:4:p:1014-:d:499791. 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.