In addition to public health measures, including social distancing, masking, cleaning, surface disinfection, etc., ventilation and air filtration can be a key component of a multi-pronged risk mitigation strategy against COVID-19 transmission indoors. Electrostatic precipitators (ESP) have already proved their high performance in fluid filtration, particularly in industrial applications, to control exhaust gas emissions and remove fine and superfine particles from the flowing gas, using high-voltage electrostatic fields and forces. In this contribution, a high-voltage electrostatic sanitizer (ESS), based on the electrostatic precipitation concept, is proposed as a supportive measure to reduce indoor air infection and prevent the spread of COVID-19 coronavirus. The finite element method (FEM) is used to model and simulate the proposed ESS, taking into account three main mechanisms involving in electrostatic sanitization, namely electrostatic field, airflow, and aerosol charging and tracing, which are mutually coupled to each other and occur simultaneously during the sanitization process. To consider the capability of the designed ESS in capturing superfine particles, functional parameters of the developed ESS, such as air velocity, electric potential, and space charge density, inside the ESS are investigated using the developed FEM model. Simulation results demonstrate the ability of the designed ESS in capturing aerosols containing coronavirus, precipitating suspended viral particles, and trapping them in oppositely charged electrode plates.

With the growing requirements imposed by regulatory authorities, grid operators and power utilities firms are confronted with the challenging task of ensuring the reliability, safety, and resilience of distribution networks amid aging asset infrastructure and a lack of resources. Over the past 15 years, the health index (HI)-based analysis has become an increasingly popular asset management tool for several power utilities. This strongly focuses on HI-based analysis to consider not only factors such as the cable vintage, type, and operating conditions, but also maintenance testing data. In this regard, the best industry practices for cable maintenance testing, including VLF Tan-Delta, partial discharge (PD), and time domain reflectometry (TDR), are outlined. Moreover, online tests, such as infrared thermography, ultrasonic PD scan, and temperature monitoring, are discussed. This paper also summarizes the classic asset management strategies for underground (UG) distribution power cables. The paper offers a practical approach for cable fleet management based on authors’ experience dealing with distribution power utility cable management for North American power utilities firms in the past 10 years. The proposed approach ensures reliable cable management at the lowest total life cycle cost. The topic of fleet management for UG power cables considering various condition parameters and an overall risk assessment is outlined. The fleet management guideline of UG power cables covers both cables and their accessories, such as terminations and joints. The main contributions of the paper are to: (1) determine the key parameters and testing factors for condition assessment of cables; (2) offer a practical approach to cable management that is not only based on technical issues, but also considers risk and impact costs, such as financial impact, reliability impact, etc.; and (3) propose a methodology for translating the HI/calculated risks into GIS, making it possible to identify major degradation patterns for fleet assessment. Considering budget and resource limitations around testing UG cable installations, this paper aims to assist asset managers, engineers, and asset owners in developing an effective cable fleet management strategy.

Power transformers are vital to delivering energy in power grids and they bear considerable maintenance costs annually. One of the major issues for power transformers is the ageing of the insulation paper used in windings that affects the life of transformers significantly. Utilising an appropriate procedure for loading of transformers can reduce the ageing rate of insulation and can improve the life expectancy. Therefore, it is crucial to obtain the values for the ageing rate which are optimum and to prevent transformer fleet from accelerated ageing. Although techniques are available to calculate the ageing rate and loss of life of a single transformer, utilities looking into the transformer fleet ageing need a better tool to improve the ageing rate of all transformers together. The main contribution of this study is to provide a method for the transformer fleet ageing optimisation rather than single unit ageing approach. This study proposes a novel approach utilising different optimisation techniques that are capable of representing different factors in order to obtain an optimum ageing rate for a fleet of transformers. The optimum ageing rate can provide a technical tool for asset managers, utility engineers and owners for better power transformer fleet management.