The Impact of the Level of Detail in the Distributed Parameter Model of a Transmission Line on Its Frequency Characteristics

One of the most widely used methods for assessing electric power quality is based on modeling and simulation of electrical system operating modes, which enables a detailed analysis of system behavior without interfering with real-world operation. This approach is effective both during the operational phase of the grid and in its planning and development stages—especially when real measurement data is unavailable, or when it is necessary to evaluate the impact of different scenarios on the system. Simulation makes it possible to predict how specific nonlinear loads, inverter-based interfaces, or asymmetric events will affect grid stability and power quality parameters. However, for this method to yield meaningful and reliable results, it is essential to accurately model the system components. Each element must be represented with its electrical, dynamic, and frequency-dependent characteristics. Without high precision, the model fails to reflect the risks and behaviors that may arise under real-world conditions. It is particularly important to consider that the influence of harmonics, rapid voltage variations, and phase asymmetries manifests differently across various frequency ranges; thus, these dependencies must be integrated into the component models. An inadequately modeled system results in inaccurate predictions and leads to suboptimal technical or financial decisions. This paper examines the impact of the level of detail in distributed-parameter modeling of high-voltage transmission lines on their frequency characteristics, which is a critical issue for ensuring accuracy and reliability in simulations of high-frequency phenomena. The depth of model granularity directly affects the model’s ability to accurately reflect frequency-domain components, especially harmonic contents and fast transient voltage/current impulses. A high degree of model granularity, which means modeling the transmission line using smaller and more numerous segments, allows the simulation to more accurately reflect real physical behavior. This is especially important in dynamic conditions involving nonlinear loads and inverter-based generation. Such detailed modeling captures frequency-dependent characteristics more precisely, including resonances, damping effects, and frequency-related losses. However, increased granularity also leads to higher computational demands and longer simulation times. As a result, one of the main objectives of this study is to determine the optimal level of model granularity. This level is not fixed and depends significantly on the purpose of the analysis and the technical characteristics of the simulated scenarios. In general, this type of optimization seeks to define a level of detail that provides sufficient accuracy for the specific task while maintaining an efficient simulation process.