Marginal profit maximization estimation of supply chains by waste energy decrement: a case study of the power industry

M. Pouralizadeh
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Abstract

Economic growth and excessive fossil energy consumption have direct effects on environmental destruction and greenhouse gas increments. The existing appropriate pattern for economic performance increase as well as pollution emissions abatement is a basic issue in industry activities. In this paper, a data envelopment analysis (DEA) model is introduced for estimating the directional marginal profit maximization of supply chain divisions based on wasted energy and power losses. The purpose of this study is to estimate the directional marginal productivity in the supply chain, which enables us to find the optimal direction of efficient divisions on the frontier. This makes the allocation of resources create a marginal profit increase and the pollution emissions be abated simultaneously. Indeed, the proposed model considers the synergistic effects of each input on MP estimation in predetermined directions. The model is able to estimate the marginal profit maximization of desirable output and undesirable output decrease for each input simultaneously. The results suggested that the gas field division of one of the supply chains had fundamental capacities for energy production increments and flare gas decrements. Furthermore, the gas field division of this supply chain also had a considerable structure for the marginal profit maximization of outputs based on flare gas decreases. Additionally, the distribution lines of 0.80% supply chains provided wasted energy reduction by adding one extra unit to the line's capacity in the determined direction. Especially, there were supply chains that had investment opportunities for an acceptable abatement of power losses. This not only enables divisions to respond to fluctuations in demand as they produce more energy in critical situations like climate change but also decreases harmful emissions as wasted energy in supply chain divisions.
通过废能递减估算供应链边际利润最大化:电力行业案例研究
经济增长和化石能源的过度消耗直接影响到环境破坏和温室气体的增加。现有的既能提高经济效益又能减少污染排放的适当模式是工业活动中的一个基本问题。本文介绍了一种数据包络分析(DEA)模型,用于估算基于能源浪费和电力损耗的供应链部门的定向边际利润最大化。本研究的目的是估算供应链中的定向边际生产率,从而找到前沿上有效分工的最优方向。这使得资源配置在创造边际利润增长的同时,也减少了污染排放。事实上,所提出的模型考虑了每项投入对预定方向的 MP 估算的协同效应。该模型能够同时估算出每种投入的理想产出和不理想产出减少的边际利润最大化。结果表明,其中一条供应链的气田分部具有增加能源生产和减少燃烧气体的基本能力。此外,该供应链的气田部门还具有基于火炬气减少的产出边际利润最大化的重要结构。此外,0.80% 供应链的配电线路通过在确定方向上增加一个额外单位的线路容量来减少能源浪费。特别是,有些供应链有投资机会,以可接受的方式减少电力损耗。这不仅能使各部门在气候变化等危急情况下生产更多能源,从而应对需求波动,还能减少供应链部门浪费能源所造成的有害排放。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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