基于线性规划的碳排放优化

Vithursan Magenthirarajah, A. Gamage, S. Chandrasiri
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引用次数: 0

摘要

在这个快速发展的现代化进程中,过量的碳排放在气候变化中起着至关重要的作用。以可持续的碳中和和管理方式为目标并进行试验,是迈向绿色社会的途径。数据显示,工厂和工业在碳排放和管理方面占有很高的市场份额。在行动中,各国政府为每个组织规定了碳排放限额,称为碳信用。每个组织都必须关注减少碳排放。这是每个组织的关键任务,在某些情况下,仍然不可能探索其他可持续的选择。针对上述情况提出的一个创新解决方案是实施一个实时平台,该平台可以提供对组织最新排放统计数据的见解。本文以最简单的形式提供了先进的分析和精确的主动计划和行动,并讨论了关于结论的未来阐述和见解。通过寻找每个排放源的最小最优排放值,组织可以在不超过其碳信用的情况下保持碳排放。此外,工业和工厂如何创建一个智能碳优化系统,从而创造一个更绿色的社会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Carbon Emission Optimization Using Linear Programming
In this fast-growing modernization, excess carbon emission plays a crucial role in climate change. Targeting and experimenting with sustainable ways of Carbon neutrality and management is the pathway toward a greener society. Data show that factories and industries take a high market stake in carbon emission and management. In actions, Governments defined a limit for carbon emissions to each organization which is called carbon credit. Every organization must focus on reducing carbon emissions. This is a critical task for each organization, In some cases, it is still not possible to explore other sustainable options. An innovative solution proposed for the above scenario is to implement a real-time platform that can provide insights into the most up-to-date emission statistics of the organization. This paper provides advanced analytics and precise proactive planning and actions in the simplest form and a discussion on future elaborations and insights about conclusions. By finding the minimum optimal emission values of each emission source, organizations can maintain carbon emissions without exceeding their carbon credit. Also, how industries and factories can create a smart carbon optimization system that can create an even greener society.
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