Transmission Capacity Allocation in Zonal Electricity Markets

Ignacio Aravena (), Quentin Lété (), Anthony Papavasiliou () and Yves Smeers ()
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Ignacio Aravena: Lawrence Livermore National Laboratory, Livermore, California 94550
Quentin Lété: Center for Operations Research and Econometrics (CORE), Université catholique de Louvain, 1348 Louvain-la-Neuve, Belgium
Anthony Papavasiliou: Center for Operations Research and Econometrics (CORE), Université catholique de Louvain, 1348 Louvain-la-Neuve, Belgium
Yves Smeers: Center for Operations Research and Econometrics (CORE), Université catholique de Louvain, 1348 Louvain-la-Neuve, Belgium

Operations Research, 2021, vol. 69, issue 4, 1240-1255

Abstract: We propose a novel framework for modeling zonal electricity markets, based on projecting the constraints of the nodal network onto the space of the zonal aggregation of the network. The framework avoids circular definitions and discretionary parameters, which are recurrent in the implementation and study of zonal markets. Using this framework, we model and analyze two zonal market designs currently present in Europe: flow-based market coupling (FBMC) and available-transfer-capacity market coupling (ATCMC). We develop cutting-plane algorithms for simulating FBMC and ATCMC while accounting for the robustness of imports/exports to single element failures, and we conduct numerical simulations of FBMC and ATCMC on a realistic instance of the Central Western European system under the equivalent of 100 years of operating conditions. We find that FBMC and ATCMC are unable to anticipate the congestion of branches interconnecting zones and branches within zones and that both zonal designs achieve similar overall cost efficiencies (0.01% difference), whereas a nodal market design largely outperforms both of them (5.09% better than FBMC). These findings raise the question of whether it is worth it for more European countries to switch from ATCMC to FBMC, instead of advancing directly toward a nodal market design.

Keywords: natural resources: energy; government: energy policies; programming: integer: applications; programming: large scale systems; Environment; Energy; and Sustainability; electricity markets; robust programming; cutting plane algorithms; policy analysis (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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