A Market-Clearing-Based Sensitivity Model for Locational Marginal and Average Carbon Emission

Zelong Lu;Lei Yan;Jianxue Wang;Chongqing Kang;Mohammad Shahidehpour;Zuyi Li
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Abstract

This letter proposes a market-clearing-based locational marginal carbon emission (LMCE) metric to assess the marginal carbon emission effect of nodal load demand. Unlike the prevalent carbon emission flow (CEF) method that relies on a hypothetical power-flow tracking process, the proposed LMCE metric depends on a novel sensitivity analysis of market-clearing results, capable of revealing both energy-dependent and network-dependent impacts on emissions. Additionally, we introduce a locational average carbon emission (LACE) metric, derived from LMCE, to effectively measure the general emission effect. It offers insights into demand-side carbon emission effects, such as a negative LMCE and LACE indicating emission reduction even as load increases. It can also prevent excessive demand-side emission allocations. Overall, the proposed method provides a clear perspective for the ongoing decarbonization policies.
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基于市场出清的区位边际和平均碳排放敏感性模型
本文提出了一个基于市场清算的区位边际碳排放(LMCE)指标来评估节点负荷需求的边际碳排放效应。与普遍的碳排放流(CEF)方法不同,该方法依赖于假设的功率流跟踪过程,而拟议的LMCE指标依赖于对市场清算结果的新颖敏感性分析,能够揭示能源依赖性和网络依赖性对排放的影响。此外,我们引入了从LMCE衍生而来的区位平均碳排放(LACE)指标,以有效衡量总体排放效应。它提供了对需求侧碳排放影响的见解,例如负的LMCE和LACE表明即使负荷增加也会减少排放量。它还可以防止过度的需求侧排放分配。总的来说,所提出的方法为正在进行的脱碳政策提供了一个清晰的视角。
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2024 Index IEEE Transactions on Energy Markets, Policy and Regulation Vol. 2 Table of Contents IEEE Power & Energy Society Information IEEE Transactions on Energy Markets, Policy, and Regulation Information for Authors Blank Page
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