计及碳流的工业企业能源系统运行策略分析

为实现对工业企业能源系统中碳流轨迹的精确追踪，并制定有效的降碳运行策略，本文采用考虑网损的极坐标下的牛顿—拉夫逊迭代法，建立潮流稳态模型，用于分析系统中各节点和支路的有功潮流状态，以及网络损耗对系统性能的影响。此外，通过回归分析法对历史能耗数据进行建模，确定了燃煤发电机组的碳排放强度向量。进一步，建立了一个系统碳流分析模型，利用碳流与系统潮流的依赖关系，分析了各支路、负荷、以及网损的碳流率，以及各个节点的碳势。为了实证所提方法的有效性，采用IEEE 14节点系统为某工业企业构建了一个5机14节点的需求响应模型。通过仿真分析，研究了企业各用能环节的碳排放强度，实现了碳流的精确追踪。最后，为了优化工业企业能源系统的运行策略，采取了安装碳捕集装置和实施就地无功补偿两种措施，并通过模拟实验验证了这些措施降低系统碳排放的有效性。

Analysis of Energy System Operation Strategy of Industrial Enterprises Considering Carbon Flow

To accurately track the carbon flow trajectory in the energy system of industrial enterprises and formulate an effective carbon reduction operation strategy, this paper uses the Newton-Raphson iterative method in polar coordinates considering network loss to establish a power flow steady-state model, which is used to analyze the active power flow state of each node and branch in the system and the impact of network loss on system performance. In addition, the historical energy consumption data was modeled by regression analysis to determine the carbon emission intensity vector of coal-fired power generation units. Furthermore, a system carbon flow analysis model was established, and the carbon flow rate of each branch, load, and network loss, as well as the carbon potential of each node, were analyzed by using the dependence between carbon flow and system power flow. In order to verify the effectiveness of the proposed method, a 5-machine 14-node demand response model was constructed for an industrial enterprise using the IEEE 14-node system. Through simulation analysis, the carbon emission intensity of each energy consumption link of the enterprise was studied, and the accurate tracking of carbon flow was realized. Finally, in order to optimize the operation strategy of the energy system of industrial enterprises, two measures were adopted: the installation of carbon capture device and the implementation of in-situ reactive power compensation, and the effectiveness of these measures in reducing the carbon emission of the system was verified by simulation experiments.