Two-Stage Stochastic Programming Model for Market Clearing With Contingencies

被引：26

作者：

Saric, Andrija T. ^{[1
]}

Murphy, Frederic H. ^{[2
]}

Soyster, Allen L. ^{[3
]}

Stankovic, Aleksandar M. ^{[1
]}

机构：

[1] Northeastern Univ, Coll Engn, Boston, MA 02115 USA

[2] Temple Univ, Fox Sch Business & Management, Philadelphia, PA 19122 USA

[3] Natl Sci Fdn, Arlington, VA 22230 USA

来源：

IEEE TRANSACTIONS ON POWER SYSTEMS | 2009年 / 24卷 / 03期

基金：

美国国家科学基金会;

关键词：

Locational marginal prices (LMPs); optimization methods; power system economics; power system security; stochastic approximation; uncertainty; INTERIOR-POINT METHODS; DECOMPOSITION; SECURITY; ENERGY; OPTIMIZATION; FORMULATION; RESERVES; SYSTEMS;

D O I：

10.1109/TPWRS.2009.2023267

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：

Planning for contingencies typically results in the use of more expensive facilities before disruptions. It leads to different prices and energy availability at various network locations depending on how the contingency analysis is performed. In this paper we present a two-stage stochastic programming model for incorporating contingencies. The model is computationally demanding, and made tractable by using an interior-point log-barrier method coupled with Benders decomposition. The second-stage optimal recourse function (RF) defines the most economically efficient actions in the post-contingency state for returning the system back to normal operating conditions. The approach is illustrated with for two examples: small (with 8 buses/11 branches) and IEEE medium- scale (with 300 buses/411 branches).

引用

页码：1266 / 1278

页数：13

共 31 条

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