Papers
Topics
Authors
Recent
Search
2000 character limit reached

Challenges in Finding Stable Price Zones in European Electricity Markets: Aiming to Square the Circle?

Published 9 Apr 2024 in econ.GN and q-fin.EC | (2404.06489v4)

Abstract: The European day-ahead electricity market is split into multiple bidding zones with a uniform price. The increase in renewables leads to a growing number of interventions in the generation of energy sources and increasing redispatch costs. To ensure efficient congestion management, the EU Commission mandated a Bidding Zone Review (BZR) to reevaluate the configuration of European bidding zones. An integral part of this process was a locational marginal pricing study. Based on these prices, alternative bidding zone configurations were proposed. These bidding zones shall be stable and robust over time. For Germany, four configurations were suggested. We analyzed the proposed configurations considering different clustering algorithms and periods based on the publicly released data set in the context of the BZR, and found that the configurations do not reduce the price standard deviations within zones much, and the average prices across zones are similar. Other configurations identified based on clustering the prices lead to lower price variance but they are not geographically coherent. Independent of the clustering features and algorithms used, the resulting clusters are not stable over time. Interestingly, the effect of a split on prices would be low based on an analysis of the BZR data set.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (26)
  1. ACER (2020). ACER Decision on the methodology and assumptions that are to be used in the bidding zone review process and for the alternative bidding zone configurations to be considered Annex I. Methodology and assumptions that are to be used in the bidding zone review process . https://acer.europa.eu/sites/default/files/documents/Official_documents/Acts_of_the_Agency/Individual%20decisions%20Annexes/ACER%20Decision%20No%2029-2020_Annexes/ACER%20Decision%2029-2020%20on%20the%20BZR%20-%20Annex%20I%20_%20%20BZR%20methodology.pdf. Accessed: 2024-02-09.
  2. ACER (2021). High-level approach to identify alternative bidding zone configurations for the bidding zone review. https://acer.europa.eu/en/Documents/Presentations%20Webinars/20210624_Public_webinar_alternative_BZ_configurations.pdf. Accessed: 2024-02-09
  3. ACER (2022a). ACER’s Decision on the alternative bidding zone configurations to be considered in the bidding zone review process. Annex I. List of alternative bidding zone configurations to be considered for the bidding zone review. https://www.acer.europa.eu/Individual%20Decisions_annex/ACER%20Decision%2011-2022%20on%20alternative%20BZ%20configurations%20-%20Annex%20I.pdf. Accessed: 2023-12-01.
  4. ACER (2022b). ACER’s Decision on the alternative bidding zone configurations to be considered in the bidding zone review process. Annex IV. Description of the clustering algorithms. https://www.acer.europa.eu/Individual%20Decisions_annex/ACER%20Decision%2011-2022%20on%20alternative%20BZ%20configurations%20-%20Annex%20IV.pdf. Accessed: 2024-02-09.
  5. Managing and Mining Graph Data (1st ed.). Springer Publishing Company, Incorporated.
  6. Endogenous price zones and investment incentives in electricity markets: An application of multilevel optimization with graph partitioning. Energy Economics, 92, 104879.
  7. K-means++: The advantages of careful seeding. Proceedings of the Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA ’07, 1027–1035.
  8. Constrained k-means clustering. Technical Report MSR-TR-2000-65. https://www.microsoft.com/en-us/research/publication/constrained-k-means-clustering/
  9. Review of the mathematic models to calculate the network indicators to define the bidding zones. 2019 54th International Universities Power Engineering Conference (UPEC), 1–6. https://doi.org/10.1109/UPEC.2019.8893576
  10. Determination of alternative bidding areas based on a full nodal pricing approach. 1–5. https://doi.org/10.1109/PESMG.2013.6672466
  11. A clustering approach to the definition of robust, operational and market efficient delineations for european bidding zones. IET Generation, Transmission & Distribution.
  12. Burstedde, B. (2012). From nodal to zonal pricing: A bottom-up approach to the second-best. 2012 9th International Conference on the European Energy Market, 1–8. https://doi.org/10.1109/EEM.2012.6254665
  13. Commission, E. (2015). Commission regulation (eu) 2015/1222 of 24 july 2015 establishing a guideline on capacity allocation and congestion management (text with eea relevance). Official Journal of the European Union. Accessed: 2024-01-19.
  14. Commission, E. (2019). Regulation (eu) 2019/943 of the european parliament and of the council of 5 june 2019 on the internal market for electricity (recast) (text with eea relevance.). Official Journal of the European Union. Accessed: 2024-01-19.
  15. A cluster separation measure. IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-1(2), 224–227. https://doi.org/10.1109/TPAMI.1979.4766909
  16. Energywende (2018). The german electricity grid: notoriously swamped? https://energytransition.org/2018/03/the-german-electricity-grid-notoriously-swamped. Accessed: 2024-01-18.
  17. ENTSO-E (2022). Report on the locational marginal pricing study of the bidding zone review process. https://eepublicdownloads.blob.core.windows.net/public-cdn-container/clean-documents/Publications/Market%20Committee%20publications/ENTSO-E%20LMP%20Report_publication.pdf. Accessed: 2024-02-09
  18. ENTSO-E (2023). Bidding zone review. https://www.entsoe.eu/network_codes/bzr/. Accessed: 2024-01-18.
  19. Consistent and robust delimitation of price zones under uncertainty with an application to central western europe. Energy Economics, 75, 583–601. https://doi.org/https://doi.org/10.1016/j.eneco.2018.09.012
  20. A zonal congestion management approach using real and reactive power rescheduling. IEEE Transactions on Power Systems, 19(1), 554–562. https://doi.org/10.1109/TPWRS.2003.821448
  21. The scheme of a novel methodology for zonal division based on power transfer distribution factors. IECON 2014 - 40th Annual Conference of the IEEE Industrial Electronics Society, 3598–3604. https://doi.org/10.1109/IECON.2014.7049033
  22. Lloyd, S. (1982). Least squares quantization in pcm. IEEE Transactions on Information Theory, 28(2), 129–137. https://doi.org/10.1109/TIT.1982.1056489
  23. Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. http://www.jstor.org/stable/2332142
  24. Five indicators for assessing bidding area configurations in zonally-priced power markets. 2015 IEEE Power & Energy Society General Meeting, 1–5.
  25. Stoft, S. (1997). Transmission pricing zones: simple or complex? The Electricity Journal, 10(1), 24–31. https://doi.org/https://doi.org/10.1016/S1040-6190(97)80294-1
  26. Zinke, J. (2023). Two prices fix all? on the robustness of a german bidding zone split. Technical report, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
Citations (1)

Summary

No one has generated a summary of this paper yet.

Paper to Video (Beta)

No one has generated a video about this paper yet.

Whiteboard

No one has generated a whiteboard explanation for this paper yet.

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Continue Learning

We haven't generated follow-up questions for this paper yet.

Tweets

Sign up for free to view the 5 tweets with 0 likes about this paper.