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

V. Kalashnikov, N. Kalashnykova, Felipe J. Castillo-Pérez
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Abstract

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.
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双层天然气套现问题:确定性和随机方法
本文研究了天然气运输公司和管道运营商之间的交易中出现的一个特殊的双层规划问题。由于这两个参与者之间的业务关系,他们的决策过程的时间和目标是不同的。为了对其建模,在以前的工作中传统地使用了双层编程。从理论上研究问题以促进其解决,这包括线性重构,启发式方法和分支定界技术。我们提出了一个线性规划的最新版本的模型,这是更容易和更快的数值求解。这种重新表述使从理论上分析问题变得更容易,使我们能够得出关于解决方案性质的一些结论。由于双层天然气套现问题中肯定存在不确定性因素,因此将其随机公式建立为带追索权的双层多阶段随机规划模型。将原公式简化为双层线性问题,通过节点事件定义随机情景树,利用时间序列预测对天然气价格和需求数据生成随机值。通过数值实验对随机解与完全信息解和期望值解进行了比较。
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