4.7 Article

Uncertain bidding zone configurations: The role of expectations for transmission and generation capacity expansion

Journal

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
Volume 285, Issue 1, Pages 343-359

Publisher

ELSEVIER
DOI: 10.1016/j.ejor.2020.01.024

Keywords

OR in energy; Stochastic programming; Uncertainty modeling; Electricity market modeling; Multilevel programming

Funding

  1. Bavarian State Government
  2. Emerging Field Initiative (EFI) of the Friedrich-Alexander-Universitat Erlangen-Nurnberg
  3. Emerging Talents Initiative (ETI) of the Friedrich-Alexander-Universitat Erlangen-Nurnberg
  4. Deutsche Forschungsgemeinschaft [Sonderforschungsbereich/Transregio 154]
  5. Dr. Theo and Friedl Scholler Research Center through a Scholler Fellowship
  6. UK Engineering and Physical Sciences Research Council [EP/P001173/1]

Ask authors/readers for more resources

Ongoing policy discussions on the reconfiguration of bidding zones in European electricity markets induce uncertainty about the future market design. This paper deals with the question of how this uncertainty affects market participants and their long-run investment decisions in generation and transmission capacity. Generalizing the literature on pro-active network expansion planning, we propose a stochastic multilevel model which incorporates generation capacity investment, network expansion, and market operation, taking into account uncertainty about the future bidding zone configuration. Using a stylized two-node network, we disentangle different effects that uncertainty has on market outcomes. If there is a possibility that future bidding zone configurations provide improved regional price signals, welfare gains materialize even if the change does not actually take place. As a consequence, welfare gains of an actual change of the bidding zone configuration are substantially lower due to those anticipatory effects. Additionally, we show substantial distributional effects in terms of both expected gains and risks, between producers and consumers and between different generation technologies. (C) 2020 Elsevier B.V. All rights reserved.

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