In this letter, we propose an efficient hybrid sampling method for microwave component modeling and optimization. The sampling method adaptively chooses samples from global and local samples to form a data set. The local samples are obtained using a greedy-like sampling method to exploit potential optimal solutions. The global samples are chosen using random sampling with minimum distance rejection to ensure the uniformity of the samples in the design space. The obtained data set is used to establish a surrogate model using the artificial neural networks (ANNs), and the optimal design parameters are obtained by optimizing the ANN model. A bandstop microstrip filter is taken as an example to verify the performance of the sampling method. The results show that the ANN model based on the proposed method achieves better modeling performance and yields better optimal design than the ANN model based on conventional sampling methods.

This communication presents a novel surrogate-assisted Quasi-Newton enhanced global optimization algorithm. In this proposed method, the heuristic hypersphere sampling method is used to obtain representative samples. The surrogate model is built based on the low-fidelity model. The Quasi-Newton enhanced differential evolution method is designed to optimize the surrogate model. Finally, the optimal design of a high-fidelity model is obtained through a space mapping procedure. The proposed algorithm is verified through two antenna design examples including a dipole antenna with balun and a SIW cavity-backed slot antenna. The results show that the proposed algorithm finds a more accurate minimum value with less computational time than direct optimization using differential evolution.

A grounding grid is essential to the lightning protection of power systems. This paper presents a modified partial element equivalent circuit method for predicting the transient behavior of the grounding grid. The frequency-dependent parameters of the grounding grid are obtained first by using the image method. Both modified nodal formulation and vector fitting techniques are applied to derive an extended equivalent network for time-domain simulation. In this method, the soil ionization effect is considered using a nonlinear resistance. The proposed method is verified with experimental results available in the literature. Finally, lightning transients in the grounding grid of a radio base station is presented. The ionization and propagation effects on grounding grid performance are discussed.

Improving the accuracy of transformer dissolved gas analysis is always an important demand for power companies. However, the requirement for large numbers of fault samples becomes an obstacle to this demand. This article creatively uses a large number of health data, which is much easier to obtain by power companies, to improve diagnosis accuracy. Comprehensive investigations from the view of both data set and methodology to deal with this problem are presented. A data set consists of 9595 health samples and 993 fault samples is used for analysis. The characteristics of the data set and the influence of the health data on diagnostic accuracy are discussed. The performance of many state‐of‐art algorithms that handle the imbalanced problem is evaluated. Meanwhile, an efficient fault diagnosis algorithm named self‐paced ensemble (SPE) is presented. In SPE, classification hardness is proposed to include the data characteristic in the classification. This method can guarantee the diversity of the data set and keep high performance. According to the experiment results, the superior of SPE is confirmed and also proves that involving more health samples can improve transformer diagnosis when fault data are limited.

Photovoltaic (PV) systems are susceptible to lightning strikes. During a lightning strike, an induced overvoltage is generated in the PV system. This overvoltage can damage the inverters connected to the dc cables. In this article, a comprehensive study is presented to address the installation issues that will influence the induced voltage between the +dc and –dc cables in the PV system. By using the partial element equivalent circuit method, the skin effect and ferromagnetic property of the mounting structures are well modeled. The wiring in the PV module is also considered in the simulation. The influences of the mounting systems, lightning protection systems, PV frames, and dc cable arrangements are thoroughly investigated. The simulation results and discussions provide guidance for PV structure design for maximizing lightning protection performance without adding additional protective devices.