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首页> 外文期刊>Journal of Mechanical Engineering >Comprehensive Energy Resource Management for Essential Reduction of the Total Cost
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Comprehensive Energy Resource Management for Essential Reduction of the Total Cost

机译:全面的能源管理,可大幅降低总成本

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摘要

Comprehensive energy resource management presents a kind of global optimisation, which is much more cost-effective than separate treatment of energy-demand forecasting and energy-inventory data. In this paper, a two-stage supply chain is presented where the distributor of derivate energy products (e.g., hot water, steam, electricity) shares information with its supplier of primary energy sources (e.g., coal, crude oil, gas). Different methods of energy-demand forecasting can be used, although exponential smoothing methods are most often used in practice because they are simple, fast and inexpensive. In this study we analysed a modified Holt-Winters (HW) method and we describe a method for simultaneous optimisation of a forecasting method and a stock control policy. We compared the proposed joint optimisation of total cost with the optimisation, based solely on forecasting data. The total cost presents the joint cost of the distributor and supplier. The data consisted of 756 quarterly real series from M3-Competition and 300 simulated demand patterns. We have shown that the total cost can be reduced dramatically if we use joint optimisation instead of a separate treatment of a forecasting method and an inventory model. We obtained the best result with the modified HW method; the essential reduction of total cost was reached in the case of simulated data as well as in the case of real data.
机译:全面的能源资源管理代表了一种全球优化,它比单独处理能源需求预测和能源清单数据更具成本效益。在本文中,提出了一个两阶段的供应链,其中衍生能源产品的分销商(例如,热水,蒸汽,电力)与其主要能源供应商(例如,煤炭,原油,天然气)共享信息。尽管在实践中最常使用指数平滑方法,因为它们简单,快速且廉价,但可以使用不同的能量需求预测方法。在这项研究中,我们分析了改进的Holt-Winters(HW)方法,并描述了同时优化预测方法和库存控制策略的方法。我们仅根据预测数据将建议的总成本联合优化与优化进行了比较。总成本代表了分销商和供应商的共同成本。数据包括来自M3竞争的756个季度实际序列和300个模拟需求模式。我们已经表明,如果我们使用联合优化而不是对预测方法和库存模型进行单独处理,则可以大大降低总成本。通过改进的硬件方法,我们获得了最佳结果。无论是模拟数据还是真实数据,都可以实现总成本的根本降低。

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