Bilevel Natural Gas Cash-Out Problems: Deterministic and Stochastic Approaches

被引:0
|
作者
Kalashnikov, Vyacheslav [1 ,2 ,3 ]
Kalashnykova, Nataliya [4 ]
Castillo-Perez, Felipe J. [1 ]
机构
[1] Tecnol Monterrey, Sch Sci & Engn, Monterrey 64849, Nuevo Leon, Mexico
[2] Cent Econ & Math Inst, Moscow 117418, Russia
[3] Sumy State Univ, UA-40007 Sumy, Ukraine
[4] Univ Autonoma Nuevo Leon, Fac Ciencias Fis Matemat, San Nicolas De Los Garza 66450, Nuevo Leon, Mexico
来源
2016 SECOND INTERNATIONAL SYMPOSIUM ON STOCHASTIC MODELS IN RELIABILITY ENGINEERING, LIFE SCIENCE AND OPERATIONS MANAGEMENT (SMRLO) | 2016年
关键词
Bilevel programming; natural gas cash-out problem; stochastic approach; COMPLEMENTARITY MODEL; OPTIMIZATION;
D O I
10.1109/SMRLO.2016.96
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
We study a special bilevel programming problem that arises in transactions between a Natural Gas Shipping Company and a Pipeline Operator. Because of the business relationships between these two actors, the timing and objectives of their decision-making process are different. In order to model that, bilevel programming was traditionally used in previous works. The problem theoretically studied to facilitate its solution; this included linear reformulation, heuristic approaches, and branch-and-bound techniques. We present a linear programming reformulation of the latest version of the model, which is easier and faster to solve numerically. This reformulation makes it easier to theoretically analyze the problem, allowing us to draw some conclusions about the nature of the solution. Since elements of uncertainty are definitely present in the bilevel natural gas cash-out problem, its stochastic formulation is developed in form of a bilevel multi-stage stochastic programming model with recourse. After reducing the original formulation to a bilevel linear problem, a stochastic scenario tree is defined by its node events, and time series forecasting is used to produce stochastic values for data of natural gas price and demand. Numerical experiments were run to compare the stochastic solution with the perfect information solution and the expected value solutions.
引用
收藏
页码:544 / 555
页数:12
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