Segmented Sampling Least Squares Algorithm for Green's Function of Arbitrary Layered Soil

Accurate grounding parameters calculation ensures the safe and stable operation of the power equipment, and the Green's function calculation of layered soil is the basis of the grounding parameters calculation. The conventional complex image method for Green's function of layered soil mainly include the global equal interval sampling method and the Prony's fitting method, which often have 2 disadvantages: 1. The complex exponential terms of Prony's method are usually twice the number of soil layers, and the amount of calculation increases linearly with the number of soil layers; 2. The global equal interval sampling method cannot guarantee to accurately approximate the integral kernel function, causing the failure to solve Green's function of some complex layered soils. To accurately and efficiently solve the Green's function of arbitrary layered soil, this paper, taking Green's function of horizontally layered soil where the field points and source points are both on the soil surface as an example, summarizes 3 key features of the integral kernel function. Segmented sampling method based on the extreme points of the integral kernel function and the 3-order least squares method are combined to innovatively propose the segmented sampling least squares algorithm (SSLSA) for solving Green's function of layered soil. Only 6 sampling points are required for SSLSA in each sampling segment. The results show that the SSLSA can approximate the integral kernel function more accurately, solve some complicated cases that the conventional complex image method cannot, and has the advantages of good accuracy and efficiency.

[1]  F.P. Dawalibi,et al.  Computerized Analysis of Grounding Plates in Multilayer Soils , 2009, IEEE Transactions on Power Delivery.

[2]  Jun Zou,et al.  Fast Calculation of the Green Function of a Point Current Source in a Horizontal Layered Soil With a New Complex Path and Its Application in Grounding System , 2015, IEEE Transactions on Magnetics.

[3]  Lu Zhang,et al.  Influence of Deep Earth Resistivity on HVDC Ground-Return Currents Distribution , 2017, IEEE Transactions on Power Delivery.

[4]  Cui Xiang A self-adaptation sampling scheme in complex image method , 2002 .

[5]  I.F. Gonos,et al.  Estimation of multilayer soil parameters using genetic algorithms , 2005, IEEE Transactions on Power Delivery.

[6]  Luciano Martins Neto,et al.  A High-Performance Multilayer Earth Parameter Estimation Rooted in Chebyshev Polynomials , 2018, IEEE Transactions on Power Delivery.

[7]  Luciano Martins Neto,et al.  Horizontal Multilayer Soil Parameter Estimation Through Differential Evolution , 2016, IEEE Transactions on Power Delivery.

[8]  Suo Zhi-gang Model of Multi-layer Soil Structure on Complex Measurement Condition , 2011 .

[9]  Zhong‐Xin Li,et al.  The determination of frequency domain soil parameters of horizontally layered structure by using dipole‐dipole array , 2019, International Journal of Numerical Modelling: Electronic Networks, Devices and Fields.

[10]  J. Zou,et al.  Two-stage algorithm for inverting structure parameters of the horizontal multilayer soil , 2004, IEEE Transactions on Magnetics.

[11]  M. Ptacek,et al.  Sensitivity analysis of earthing system impedance for single and multilayered soil , 2017 .

[12]  Zhong‐Xin Li,et al.  Estimation of frequency domain soil parameters of horizontally multilayered earth by using Cole–Cole model based on the parallel genetic algorithm , 2019, IET Generation, Transmission & Distribution.

[13]  Luciano Martins Neto,et al.  Parameters Estimation of a Horizontal Multilayer Soil Using Genetic Algorithm , 2010, IEEE Transactions on Power Delivery.

[14]  J. J. Yang,et al.  Complex images for electrostatic field computation in multilayered media , 1991 .

[15]  Thorsten Gerber,et al.  Handbook Of Mathematical Functions , 2016 .

[16]  Zhong‐Xin Li,et al.  Transient lightning response of grounding grids in a horizontal, multilayered soil model that considers soil ionization effects with time‐domain quasi‐static complex images , 2018, International Journal of Numerical Modelling: Electronic Networks, Devices and Fields.

[17]  Zhong‐Xin Li,et al.  Frequency domain soil parameters inversion of horizontally multilayered earth model with considering high‐frequency field , 2018, IET Generation, Transmission & Distribution.

[18]  Rong Zeng,et al.  Numerical analysis of potential distribution between ground electrodes of HVDC system considering the effect of deep earth layers , 2008 .

[19]  Jinliang He,et al.  Parameter estimation of horizontal multilayer earth by complex image method , 2005, IEEE Transactions on Power Delivery.

[20]  Simon Fortin,et al.  Analysis of Grounding Systems in Horizontal Multilayer Soils Containing Finite Heterogeneities , 2015, IEEE Transactions on Industry Applications.

[21]  Guan Zhicheng RECURSIVE METHOD TO OBTAIN ANALYTIC EXPRESSIONS OF GREEN'S FUNCTIONS IN MULTI-LAYER SOIL BY COMPUTER , 2004 .