Market design for renewable energy auctions: An analysis of alternative auction formats

被引:13
作者
Bichler, Martin [1 ]
Grimm, Veronika [2 ,3 ]
Kretschmer, Sandra [2 ,3 ]
Sutterer, Paul [1 ]
机构
[1] Tech Univ Munich, Dept Informat, Boltzmannstr 3, D-85748 Garching, Germany
[2] Friedrich Alexander Univ Erlangen Nuremberg, Dept Business & Econ, Lange Gasse 20, D-90403 Nurnberg, Germany
[3] Energy Campus Nuremberg, Fuerther Str 250, D-90429 Nurnberg, Germany
关键词
Renewable energy auction; Combinatorial auction; Market design; DISTRIBUTED GENERATION; COMPUTATIONAL ANALYSIS; COMBINATORIAL;
D O I
10.1016/j.eneco.2020.104904
中图分类号
F [经济];
学科分类号
02 ;
摘要
Auctions are widely used to determine the remuneration for renewable energies. They typically induce a high concentration of renewable energy plants at very productive sites far-off the main load centres, leading to an inefficient allocation as transmission line capacities are restricted but not considered in the allocation, resulting in an inefficient system configuration in the long run. To counteract these tendencies effectively, we propose a combinatorial auction design that allows to implement regional target capacities, provides a simple pricing rule and maintains a high level of competition between bidders by permitting package bids. By means of extensive numerical experiments we evaluate the combinatorial auction as compared to three further RES auction designs, the current German nationwide auction design, a simple nationwide auction, and regional auctions. We find that if bidders benefit from high enough economies of scale, the combinatorial auction design implements system-optimal target capacities without increasing the average remuneration per kWh as compared to the current German auction design. The prices resulting from the combinatorial auction are linear and anonymous for each region whenever possible, while minimal personalised markups on the linear prices are applied only when necessary. We show that realistic problem sizes can be solved in seconds, even though the problem is computationally hard. (C) 2020 Published by Elsevier B.V.
引用
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页数:14
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