Efficient Global Sensitivity Analysis for Carbon Flow in Hybrid AC-DC Power Systems

Zongwei Liu; Yibo Li; Zexi Chen; Yijun Xu; Wei Gu; Changli Shi; Shuai Lu; Mert Korkali

doi:10.23919/PCMP.2025.000388

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Efficient Global Sensitivity Analysis for Carbon Flow in Hybrid AC-DC Power Systems

更新时间：2026-09-21

- Efficient Global Sensitivity Analysis for Carbon Flow in Hybrid AC-DC Power Systems
- Efficient Global Sensitivity Analysis for Carbon Flow in Hybrid AC-DC Power Systems
- 现代电力系统保护与控制（英文） 2026年11卷第5期页码：67-83
- 作者机构：
  
  1. Electrical Engineering Department, Southeast University,Nanjing,China
  2. State Grid Beijing Electric Power Research Institute,Beijing,China
  3. China Datang Corporation Technology Innovation Co., Ltd.,Baoding,China
  4. Department of Electrical Engineering and Computer Science, University of Missouri,MO,Columbia,USA
- 作者简介：
- 基金信息：
- DOI：10.23919/PCMP.2025.000388
  中图分类号：
- 纸质出版：2026-09-01
- 稿件说明：
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Zongwei Liu, Yibo Li, Zexi Chen, 等. Efficient Global Sensitivity Analysis for Carbon Flow in Hybrid AC-DC Power Systems[J]. 现代电力系统保护与控制（英文）, 2026,11(5):67-83.

Zongwei Liu, Yibo Li, Zexi Chen, et al. Efficient Global Sensitivity Analysis for Carbon Flow in Hybrid AC-DC Power Systems[J]. Protection and Control of Modern Power Systems, 2026, 11(5): 67-83.
Zongwei Liu, Yibo Li, Zexi Chen, 等. Efficient Global Sensitivity Analysis for Carbon Flow in Hybrid AC-DC Power Systems[J]. 现代电力系统保护与控制（英文）, 2026,11(5):67-83. DOI： 10.23919/PCMP.2025.000388.

Zongwei Liu, Yibo Li, Zexi Chen, et al. Efficient Global Sensitivity Analysis for Carbon Flow in Hybrid AC-DC Power Systems[J]. Protection and Control of Modern Power Systems, 2026, 11(5): 67-83. DOI： 10.23919/PCMP.2025.000388.

摘要

Abstract

Although carbon flow is a powerful tool for assigning emission responsibility to consumers

it has not been explored in hybrid AC-DC systems. This paper presents a novel probabilistic carbon-flow model to quantify the distribution of carbon intensity in such systems. To further characterize the importance of uncertain inputs

such as renewable energy and loads

on probabilistic carbon flow

a global sensitivity analysis (GSA) strategy is introduced. To alleviate the computational burden of traditional Monte Carlo methods in quantifying these metrics

it incorporates an adaptive polynomial chaos expansion (PCE)-based surrogate model. This significantly reduces the computing burden while maintaining high statistical accuracy. Simulations validate the proposed carbon flow model in the hybrid AC-DC system and reveal the excellent performance of the PCE-based GSA method.

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