Near-Optimal Scheduling in Day-Ahead Markets: Pricing Models and Payment Redistribution Bounds

被引:19
作者
Eldridge, Brent [1 ,2 ]
O'Neill, Richard [3 ]
Hobbs, Benjamin E. [4 ]
机构
[1] Johns Hopkins Univ JHU, Environm Hlth & Engn EHE Dept, Baltimore, MD 21218 USA
[2] Fed Energy Regulatory Commiss, Washington, DC 20426 USA
[3] FERC, Washington, DC 20426 USA
[4] Johns Hopkins Univ JHU, EHE Dept, Baltimore, MD 21218 USA
基金
美国国家科学基金会;
关键词
Pricing; Schedules; Generators; Production; Software; Electricity supply industry; Standards; Unit commitment; nonconvex pricing; mixed integer programming; market design; UNIT COMMITMENT; CLEARING PRICES; FORMULATION; EQUILIBRIUM;
D O I
10.1109/TPWRS.2019.2947400
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Near-optimal unit commitment (UC) scheduling is a practical reality in wholesale electricity markets. This paper revisits previous work that has found that minor differences in cost among near-optimal schedules can result in a large redistribution of market payments (i.e., changes in generator profits and consumer surplus). It has been believed that this instability is unavoidable, but previous studies have only calculated prices using what we call the Restricted pricing model. This paper compares previous results to three additional models that are based on integer relaxation, and which we call the Partial, Tight, and Loose Dispatchable pricing models. Results are presented for a suite of test cases, including four ISO-scale cases. Similar to previous findings, the Restricted and Partial Dispatchable models both result in large payment redistributions among alternative solutions. In contrast, theoretical and experimental results for the Tight and Loose Dispatchable models show that pricing models with unconditional integer relaxation will have bounded payment redistributions, and, further, this bound can become quite small by tightening the UC problem's convex relaxation. In the presence of market power, stable financial outcomes may improve market efficiency by reducing incentives to bid strategically.
引用
收藏
页码:1684 / 1694
页数:11
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