Štádlerová Šárka, Jena Sanjay Dominik, Schütz Peter
Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology, Trondheim, Norway.
School of Management, Université du Québec à Montréal, Montreal, Canada.
Comput Manag Sci. 2023;20(1):10. doi: 10.1007/s10287-023-00445-3. Epub 2023 Mar 1.
Hydrogen is considered a solution to decarbonize the transportation sector, an important step to meet the requirements of the Paris agreement. Even though hydrogen demand is expected to increase over the next years, the exact demand level over time remains a main source of uncertainty. We study the problem of where and when to locate hydrogen production plants to satisfy uncertain future customer demand. We formulate our problem as a two-stage stochastic multi-period facility location and capacity expansion problem. The first-stage decisions are related to the location and initial capacity of the production plants and have to be taken before customer demand is known. They involve selecting a modular capacity with a piecewise linear, convex short-term cost function for the chosen capacity level. In the second stage, decisions regarding capacity expansion and demand allocation are taken. Given the complexity of the formulation, we solve the problem using a Lagrangian decomposition heuristic. Our method is capable of finding solutions of sufficiently high quality within a few hours, even for instances too large for commercial solvers. We apply our model to a case from Norway and design the corresponding hydrogen infrastructure for the transportation sector.
氢气被视为交通运输部门脱碳的解决方案,这是满足《巴黎协定》要求的重要一步。尽管预计未来几年氢气需求将增加,但随着时间推移的确切需求水平仍是不确定性的主要来源。我们研究在何处以及何时建设氢气生产厂以满足未来不确定客户需求的问题。我们将该问题表述为两阶段随机多周期设施选址与容量扩展问题。第一阶段决策与生产厂的选址和初始容量相关,必须在客户需求已知之前做出。这些决策包括为选定的容量水平选择具有分段线性、凸短期成本函数的模块化容量。在第二阶段,做出关于容量扩展和需求分配的决策。鉴于该表述的复杂性,我们使用拉格朗日分解启发式方法来解决该问题。我们的方法能够在数小时内找到质量足够高的解决方案,即使对于商业求解器而言规模过大的实例也是如此。我们将我们的模型应用于挪威的一个案例,并为交通运输部门设计相应的氢气基础设施。