| 引用本文: | 邓国丰,李志刚,李艺宣,苏珈,白翔,郑杰辉.基于扩展关联矩阵的电力系统碳排放流计算方法[J].电力自动化设备,2025,45(9):183-189,207. |
| DENG Guofeng,LI Zhigang,LI Yixuan,SU Jia,BAI Xiang,ZHENG Jiehui.Calculation method of carbon emission flow in power system based on extended correlation matrix[J].Electric Power Automation Equipment,2025,45(9):183-189,207. |
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| 基于扩展关联矩阵的电力系统碳排放流计算方法 |
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邓国丰1, 李志刚2, 李艺宣3,4, 苏珈3,4, 白翔3,4, 郑杰辉1
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1.华南理工大学 电力学院，广东 广州 510641;2.香港中文大学(深圳)理工学院，广东 深圳 518172;3.山西省能源互联网研究院，山西 太原 030000;4.能源互联网山西省重点实验室，山西 太原 030000
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| 摘要: |
| 为了直观掌握电力系统碳排放流分布情况，完善碳排放核算和责任分摊体系，提出了基于扩展关联矩阵的电力系统碳排放流计算方法。根据基尔霍夫定律构建拓展关联矩阵并利用其对电流的虚部和实部分别进行电流分解，得到注入电流和负荷电流的分配系数矩阵。在电流分解基础上，定量分析电源、负荷、电源-线路的碳排放转移追踪，从而得到网络、负荷对电源碳排放的分摊比例。在IEEE 14节点系统和某市实际主网系统中验证了算法的有效性。算例分析结果表明，所提方法能够有效避免传统方法中的比例共享原则和有效解决因负荷功率因数差异较大导致计算结果出现负碳流率的问题，并以对角占优矩阵取逆的形式计算，极大简化了计算复杂度。 |
| 关键词: 扩展关联矩阵 潮流追踪 碳排放流 电流分解 分配系数矩阵 |
| DOI：10.16081/j.epae.202507022 |
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| 基金项目:国家自然科学基金面上项目(52177086)；山西省能源互联网研究院重点科研项目(SXEI2023B004) |
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| Calculation method of carbon emission flow in power system based on extended correlation matrix |
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DENG Guofeng1, LI Zhigang2, LI Yixuan3,4, SU Jia3,4, BAI Xiang3,4, ZHENG Jiehui1
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1.School of Electric Power Engineering, South China University of Technology, Guangzhou 510641, China;2.School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen 518172, China;3.Shanxi Energy Internet Research Institute, Taiyuan 030000, China;4.Shanxi Key Laboratory of Energy Internet, Taiyuan 030000, China
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| Abstract: |
| To intuitively understand the distribution of carbon emission flow in power system and improve the carbon emission accounting and responsibility allocation system, a calculation method of carbon emission flow in the power system based on extended correlation matrix is proposed. Based on Kirchhoff’s laws, an extended correlation matrix is constructed and used to decompose the imaginary and real parts of the current respectively, resulting in an allocation coefficient matrix for injection current and load current. Based on the current decomposition, a quantitative analysis is conducted to track the transfer of carbon emission among power sources, loads, and power source-lines, which helps determine the carbon emission allocation ratios for the network and load relative to the power sources. The effectiveness of the algorithm is validated using the IEEE 14-bus system and the actual main network of a city. Case studies show that the proposed method can effectively avoid the proportional sharing principle used in traditional methods and effectively resolve the issue of negative carbon flow rate in the calculation results caused by the large difference of load power factors. The method also simplifies the computational complexity by calculating the inverse of a diagonally dominant matrix. |
| Key words: extended correlation matrix power flow tracking carbon emission flow current decomposition distribution coefficient matrix |
