基于电力大数据的有限生产企业识别方法研究

Lin Zhao, Hui Wang, Zhi-Hong Ou, Zhenyu Zhang, Shu-Ming Feng, Jia-Yu Zhang, Xi-Ming Sun, Jialiang Miao
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引用次数: 0

摘要

经济的快速发展造成了巨大的能源消耗,也造成了更多的环境问题。因此,在双碳目标下,工业企业节能减排是绿色低碳可持续发展的必然路径。目前,各地针对的是相关企业。一系列减排措施也相继出台,但减排控制效果缺乏科学的衡量标准。基于此,本研究对江苏省连云港市1141家工业企业2021年采取减排措施前后的电力大数据进行分析,通过减排计划计算出企业的减产比例,并采用聚类算法,发现按要求限产的不受限制企业能够快速识别实际减排效果。实现对减排企业的排放监测和预警,为监管部门优化减排措施和制定相应的奖惩措施提供决策参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on the Identification Method of Limited Production Enterprises Based on Electric Power Big Data
The rapid development of the economy has caused huge energy consumption and caused more environmental problems. Therefore, under the dual-carbon goal, energy conservation and emission reduction of industrial enterprises is an inevitable path for green, low-carbon and sustainable development. At present, various regions target related enterprises. A series of emission reduction measures have also been introduced, but the effect of emission reduction control lacks scientific measurement standards. Based on this, this study analyzes the power big data before and after the emission reduction measures taken by 1141 industrial enterprises in Lianyungang City, Jiangsu Province in 2021, calculates the production reduction ratio of the enterprises through the emission reduction plan, and uses a clustering algorithm to find the unrestricted Enterprises that limit production according to the requirements can quickly identify the actual emission reduction effect, and realize the emission monitoring and early warning of emission reduction enterprises, so as to provide decision-making reference for the regulatory authorities to optimize emission reduction measures and formulate corresponding reward and punishment measures.
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