Position Optimization of Measuring Points in Voltage Non-contact Measurement of AC Overhead Transmission Lines

─ In this paper, an innovative idea is proposed to realize the voltage non-contact measurement of AC overhead transmission lines (OTLs), which is to reversely calculate the voltage characteristic parameters by using the measured AC electric field data under OTLs. The main challenge to realize the goal is the serious illposedness of the inverse problem. The condition number of the observation matrix K is the main index to reflect the ill-posedness of the inverse problem. Because the matrix K is determined by the positions of OTLs and the measuring points of electric field, it is an effective but often overlooked solution to search the optimal positions of measuring points. In this paper, an improved particle swarm optimization algorithm with the adaptive adjustment of inertia weight is developed to search the optimal measuring positions. The presented examples indicate that the selection of optimal positions for the measuring points significantly improves the accuracy and stability of the inverse solution. Meanwhile, the strong searching ability, fast convergence rate, and high stability of the proposed optimal algorithm are demonstrated as well. Index Terms ─ AC overhead transmission lines (OTLs), electric field, ill-posed problem, inverse calculation, position optimization, voltage.

[1]  C. Chiu,et al.  Solving Inverse Scattering for a Partially Immersed Metallic Cylinder Using Steady-State Genetic Algorithm and Asynchronous Particle Swarm Optimization by TE waves , 2013 .

[2]  Nazar H. Malik,et al.  A review of the charge simulation method and its applications , 1989 .

[3]  P. Angueira,et al.  Signal Injection Strategies for Smart Metering Network Deployment in Multitransformer Secondary Substations , 2011, IEEE Transactions on Power Delivery.

[5]  V. M. Catterson,et al.  The impact of smart grid technology on dielectrics and electrical insulation , 2015, IEEE Transactions on Dielectrics and Electrical Insulation.

[6]  Michael N. Vrahatis,et al.  Recent approaches to global optimization problems through Particle Swarm Optimization , 2002, Natural Computing.

[7]  Lin Xiang ULTRA-SATURATION STATE DURING TRANSFORMER SWICH-IN WITH LOAD AND ITS INFLUENCE TO TRANSFORMER DIFFERENTIAL PROTECTION , 2002 .

[8]  R. Olsen,et al.  Characteristics of low frequency electric and magnetic fields in the vicinity of electric power lines , 1992 .

[9]  J.C. Salari,et al.  Comparative Analysis of 2- and 3-D Methods for Computing Electric and Magnetic Fields Generated by Overhead Transmission Lines , 2009, IEEE Transactions on Power Delivery.

[10]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[11]  U. Hämarik,et al.  On the choice of the regularization parameter in ill-posed problems with approximately given noise level of data , 2006 .

[12]  V. V. Vasin Relationship of several variational methods for the approximate solution of ill-posed problems , 1970 .

[13]  B. Florkowska,et al.  Analysis of electric field distribution around the high-voltage overhead transmission lines with an ADSS fiber-optic cable , 2004, IEEE Transactions on Power Delivery.

[14]  H. Singer,et al.  A Charge Simulation Method for the Calculation of High Voltage Fields , 1974 .