Insulators play a crucial role in electric power systems by isolating high-voltage currents and supporting conductors. However, insulators exposed to outdoor conditions for extended periods are susceptible to faults caused by contamination, aging, and damage, leading to flashovers that may result in grid outages and economic losses. Accurate assessment of insulator condition is paramount for the safe operation of power systems. Non-contact monitoring methods, which do not interfere with the normal operation of the power system, have become mainstream in insulator condition monitoring, contrasting with traditional contact-based detection. Among these methods, optical imaging technology has garnered significant attention due to its non-contact, non-destructive, high sensitivity, and intuitive characteristics. Optical imaging technology captures reflections, transmissions, and absorptions in different spectral bands to gather information about the surface and interior of insulators, thereby determining the type of faults they may exhibit. This article reviews optical imaging detection methods applied in the field of insulator condition assessment, including infrared thermography, ultraviolet imaging, visible light imaging, and some promising optical monitoring technologies. Additionally, the advantages and limitations of these methods under various insulator fault conditions are analyzed, and challenges in industrial applications are discussed. The purpose of this review is to provide a comprehensive and systematic reference for the application of optical imaging technology in insulator condition assessment, aiming to enhance the efficiency and safety of power system operation and maintenance.

So far, silicone rubber (SiR) insulators have been widely used in the power industry all over the world, due to their outstanding insulation properties with high reliability. In practice, some of the insulators are applied in the remote places with harsh environmental conditions such as high altitude, high temperature and high humidity etc. Herein, the currently-existing aging mechanisms have been investigated, as some novel insights into these testing and evaluation methods have been proposed. Via the investigation, it can be found that thermal oxygen aging tends to occur, when insulators are exposed to an environment surrounded by hot air. To analyse the different aging mechanisms of SiR insulator sheds, four types of aging testing and evaluation methods have been systematically summarized, based on the surface structural, chemical, optical, and electrical properties. The conclusion is that non-destructive and non-contact methods, such as HSI, along with the multi - source information fusion methods, are becoming increasingly popular in the assessment of silicone rubber insulator sheds aging. These research efforts provide assurance for reducing the incidence of pollution flashover accidents in power transmission lines and ensuring the safe and stable operation of power transmission and transformation equipment.

Composite insulators are prone to accelerated aging in coastal and industrially polluted environments, leading to flashovers, power grid outages, and economic losses. Traditional detection methods either require power grid shutdown or lack adequate evaluation capabilities. This research introduces a pixel-level assessment of the aging status of composite insulators using hyperspectral imaging (HSI) technology. And proposed a least squares support vector machine (LSSVM) based on Improved Beluga Whale Optimization (IBWO) algorithm to evaluate the aged levels of composite insulators. First, artificial accelerated aged samples are categorized into aging levels I-VI using the static contact angle. Hyperspectral data in the 400 nm–1040 nm wavelength range are acquired using a HSI device, followed by preprocessing steps involving denoising and dimensionality reduction. Subsequently, the IBWO algorithm is employed to identify the optimal parameters ( C , σ ) for LSSVM. The performance of IBWO was compared with other optimization algorithms on test functions, demonstrating that IBWO exhibits the optimal convergence speed and optimization accuracy, effectively enhancing the classification and generalization ability of LSSVM. In this study, the proposed method was compared with other algorithms using k-fold cross validation, resulting in overall accuracy of 96.83% and demonstrating its superior classification capability. The presented method enables pixel-level assessment of the aging degree and visualizes the distribution of aging states in composite insulators. It provides valuable guidance for studying the aging characteristics and structural design in diverse complex environments, holding significant potential for noncontact evaluation of other electrical equipment.

When photovoltaic, wind, energy storage batteries, and other new forms of energy are connected to the grid, power electronic converters are needed, and there are a lot of nonlinear devices in the grid. The characteristics of sustainable energy generation determine the variability and intermittency, which will produce harmonic components. Active power filters (APF) are commonly used in industry for harmonic compensation, so it is of great significance to control APF quickly and effectively. The multi-objective, single-factor, multistep finite control set model predictive control (FCS-MPC) of an APF proposed in this paper is suitable for a multi-objective, multi-level converter control. This method is applied to the three-level APF structure, which changes the traditional three-level FCS-MPC control method. The traditional three-level FCS-MPC includes four control objectives, stable control of the DC-side voltage, power grid harmonic currents generated under non-linear loads, and balance of the capacitor voltage on the DC side when switching frequency. This method uses the redundant switching state of the three-level structure to achieve the voltage balance of the two capacitors on the DC side, which reduces the difficulty of target optimisation caused by the selection of weight factors. Based on the multi-step prediction, power feedback control is added on the DC side to increase the DC side’s reaction speed, eliminate the influence of uncertainty, and realise better dynamic performance. According to the simulation results, we can observe that the proposed method has good followability, can compensate for the harmonics of the power grid, reduces the harmonic content to less than 5%, and can balance the DC-side capacitor voltage.