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论文编号：	11432
作者编号：	2320170614
上传时间：	2019/12/15 20:58:21
中文题目：	S公司LNG接收站考虑调峰能力的库存管理研究
英文题目：	Research on Inventory Management Considering Peak Shaving Capacity of S Company LNG Terminal
指导老师：	张建勇
中文关键字：	LNG接收站；调峰能力；库存管理；订货计划；优化
英文关键字：	LNG receiving station; peak shaving capacity; inventory management; order planning; optimization
中文摘要：	近年来随着我国天然气消费量和对外依存度的快速增加，LNG接收站作为LNG供应链的重要环节，是LNG接收、储存、中转、气化、外输及储备调峰的重要基础设施，其战略地位更加突显。为保障LNG接收站的安全平稳运行，必须匹配好接收站的外输量、库存水平与订货计划之间的关系，同时还要考虑运行成本的经济性，因此有必要从LNG接收站库存管理的角度出发，建立一套科学系统的订货计划制定方法，寻求安全供气和降低总交易成本这两个目标之间的平衡。与此同时，天然气市场本身具有季节性矛盾突出的特点，我国天然气消费量的增加，使天然气市场的储气保供能力凸显不足，导致季节性矛盾愈发突出，冬季天然气保供成为重中之重。LNG接收站具有周转快、供气能力强、具有一定储备量的特有运行优势，在这种环境下，其日益成为中国天然气储备调峰的生力军。因此，以往保证安全供气和降低总的交易成本的LNG接收站库存研究已经不能满足接收站运行的要求，有必要对LNG接收站的储备调峰能力进行研究，将调峰能力作为LNG接收站库存研究的重要组成部分，对库存管理进行优化。基于以上分析，本文对以下几个方面进行了研究：首先，将库存管理与控制理论、运筹学理论与S公司LNG接收站的实际运营相结合，研究制定了LNG接收站库存三级动态管理基本策略，建立了LNG接收站库存三级动态管理模型，通过求解模型，对S公司LNG接收站订货计划进行三级动态优化管理，实现成本最优。然后，对S公司LNG接收站调峰模型进行了定性分析，对调峰能力进行了定量研究，将研究成果与库存三级动态管理模型相结合，对原模型进行优化，使订货计划融入调峰影响因子，进一步得到优化调整。最后将研究成果运用于S公司LNG接收站，带入工艺参数、需求预测值、调峰量预测值，求解出最优订货计划，与实际情况进行对比分析，以验证模型的可靠程度。同时，将研究成果在实际库存管理中进行应用，并对应用情况进行分析。
英文摘要：	In recent years, with the rapid increase of natural gas consumption and external dependence in China, LNG receiving terminal, as an important link of LNG supply chain, is an important infrastructure for LNG receiving, storage, transit, gasification, export and peak shaving, and its strategic position is more prominent. In order to ensure the safe and stable operation of LNG receiving terminal, it is necessary to match the relationship between the outgoing volume, inventory level and order plan of LNG receiving terminal, and also to consider the economy of operation cost. Therefore, it is necessary to establish a scientific and systematic method of order plan formulation from the point of view of inventory management of LNG receiving terminal in order to seek balance between gas supply safety and transaction cost reduction. At the same time, the natural gas market itself has the characteristics of seasonal contradictions. The increase of natural gas consumption in China makes the gas storage and supply capacity of the natural gas market inadequate, leading to seasonal contradictions becoming more prominent. In winter, natural gas supply has become the most important. LNG receiving terminal has the unique operation advantages of fast turnover, strong gas supply capacity and a certain amount of reserves. In this environment, LNG receiving terminal has increasingly become the main force of peak shaving of natural gas reserves in China. Therefore, the previous research on LNG receiving terminal inventory to ensure safe gas supply and reduce the total transaction cost can no longer meet the requirements of receiving terminal operation. It is necessary to study the reserve peak-shaving capacity of LNG receiving station, and take peak-shaving capacity as an important part of LNG receiving station inventory research to optimize inventory management. Based on the above analysis, this paper studies the following aspects: Firstly, combining the theory of inventory management and control, operational research and the actual operation of LNG receiving terminal of S Company, the three-level dynamic inventory management basic strategy of LNG receiving terminal is studied and formulated, and the three-level dynamic inventory management model of LNG receiving terminal is established. By solving the model, the three-level dynamic optimization of the order plan of LNG receiving terminal of S Company is carried out. The best cost will be achieved. Then, qualitative analysis is made on the peak shaving model of LNG receiving terminal of S Company. Quantitative research is carried out on the peak shaving capacity. The research results are combined with three-level inventory dynamic management model to optimize the original model, so that the order plan can be integrated into the peak shaving impact factor and further optimized and adjusted. Finally, the research results are applied to the LNG receiving Terminal, and the process parameters, demand forecasting value and peak shaving forecasting value are brought in to solve the optimal ordering plan, which is compared with the actual situation to verify the reliability of the model. At the same time, the research results will be applied in the actual inventory management, and the application situation is analyzed.
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