Getting a precise estimate of electric fields around extra-high-voltage (EHV) transmission lines is essential for keeping the public safe, ensuring environmental compliance, and planning infrastructure effectively. Unfortunately, traditional numerical methods often struggle with accuracy and can be slow to converge, which makes them less suitable for large-scale projects. This study introduces a hybrid computational framework that combines the Charge Simulation Method (CSM) with the Firefly Algorithm (FA). This combination helps optimize the number, position, and strength of simulation charges, leading to better modeling accuracy and efficiency. Additionally, we have trained three artificial intelligence (AI) models: Multilayer Perceptron Neural Network (MLPNN), Adaptive Neuro-Fuzzy Inference System (ANFIS), and Least Squares Support Vector Machine (LS-SVM) on real-world field data to reliably predict electric field values. Notably, LS-SVM is being used in this context for the first time and has shown to outperform the other models in accuracy, generalization, and speed. We evaluated the proposed CSM-FA hybrid model alongside AI predictions using metrics like Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), and the coefficient of determination (R²), revealing significant improvements over traditional methods. Given the heavy computational demands of the optimization and learning phases, we utilized high-performance computing (HPC) resources for implementation. This work not only advances algorithmic innovation and AI-assisted simulation but also enhances HPC applications, providing a scalable and precise solution for real-time field monitoring and regulatory assessments. The methodology aligns well with the scientific goals of The Journal of Supercomputing and fosters advanced research in intelligent power system modeling.

By electromagnetic perturbation effect, the extra-high voltage (EHV) overhead transmission lines can cause significant induced voltages and currents on buried metallic pipelines located in the immediate vicinity. These voltages can present a source of hazard both for the structural I ntegrity of the metallic pipeline and for the safety of personnel responsible for operation and maintenance. This paper proposes the quasi-static modeling of the electromagnetic interference to which a buried metallic pipeline will be subjected nearby an extra-high voltage (EHV) overhead transmission line, under steady-state operating conditions of the power electrical grid. Using the electrical network analysis method to evaluate the induced voltage levels and its effects on the buried pipeline; also, to propose a mitigation strategy if necessary. The results obtained show that the values of the AC induced voltage on the buried pipeline are significant and exceed the limits defined by the international NACE standard. They can cause a risk of electrocution for intervention personnel and accelerate the process of metal corrosion. Therefore, the gradient control mitigation technique of the conductors and their optimal geometric arrangement of EHV transmission line using Hippopotamus Optimization (HO) algorithm were proposed to reduce AC induced voltages within the permissible safety limits, according to the requirements of the NACE Standard. Finally, it should be noted that the implementation of these mitigation approaches have led to remarkable results in eliminating potential risks.