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A pulsed electric field (PEF) produces pasteurized liquid foods with fresh and nutritional properties. The treatment chamber is a crucial part of the PEF processing system where a high voltage is applied, producing an electric field to treat the liquid foods. The proper construction of the treatment chamber regulates the distribution of the electrical field inside the treatment zone. Mixing of liquid inside the treatment zone is an effective tool to overcome this heterogeneous effect. The coaxial treatment chamber offers a heterogeneous electric field and temperature distribution inside the treatment zone. A helical insulator inside the coaxial treatment chamber provides a mixing effect. In this research, a numerical simulation was done to measure the electric field in different geometries of treatment chambers at different flow rates. The simulation aimed to optimize the new coaxial treatment chamber design. The modelling findings showed homogeneous electrical field strength in the helical treatment chamber. This study provides new insights for industrial-scale setup using multiple helical chambers in a continuous flow PEF treatment.

Cross‐linked polyethylene (XLPE) is commonly used as an insulation material in power cables. Due to the recent advancements in the field of high voltage power transmission and distribution, there is a need for novel cable insulation materials that have high performance, recyclability and high working temperature as alternatives for the conventional XPLE‐based insulation materials. Polypropylene (PP) shows excellent properties and has drawn considerable attention as a potential high voltage direct current (HVDC) insulation material. Therefore, the development of PP‐based HVDC cable insulation with improved electrical, thermal and mechanical properties is important in discovering a potentially recyclable cable insulation material. Due to the remarkable development in the field of nanodielectrics, nanotechnology can be a promising solution for enhancing the overall dielectric properties of PP‐based insulation materials. This review presents the important aspects of PP‐based nanocomposites for HVDC cable insulation with a special focus on understanding the effects of various parameters of nanofillers on the dielectric properties of PP‐based HVDC cable insulation. Based on the gathered information, future perspectives for improving the dielectric properties of PP‐based nanocomposites for HVDC cable are provided.

Background Sustainable food supply is a primary concern for food industries, governments, and international agencies worldwide. Food industries are under continuous pressure to develop processing technologies that simultaneously preserve the nutritional value of foods, improve the bio-accessibility of nutrients, environment friendly and meet consumers' demands of sensory attributes. Furthermore, increasing population and inadequate cultivable land also demand transformations in the existing food processing techniques. Therefore, minimizing food wastages, sustainable developments in preservation, nutrient security, and food safety are essential elements for future requirements. Scope and approach This study refers to the roles of the pulsed electric field (PEF) in sustainable food processing systems. It also discusses the effects of this emerging technology on achieving the critical industrial goals of enhanced food quality, decreased water usage, reduced emissions, increased energy efficiency, and the ability to utilize by-products from waste food. The current study also emphasizes the need to understand factors that may limit this emerging technology's industrial uptake. Key findings and conclusions A combined multi-dimensional methodology through the entire food supply is essential to meet the worldwide food processing challenges. A limited worldwide food resource must have a balanced methodology for raw material, water, energy, and nutrient content. PEF technology fulfils significant needs for sustainable food processing as requires fewer resources to produce quantities of existing foods that are nutritionally suitable for advancing health and wellbeing, long shelf lives, and transportable.

Dissolved gas analysis is the most common and well-established method used in identifying internal faults of power transformers. However, an onsite analysis using this method accuracy still need to be improved while the laboratories analysis process takes longer time. New alternative onsite and online method are most urgently need to be studied. Power transformer faults identification based on extended application of polarization and depolarization current (PDC) measurement data on oil sample from in-service power transformer was investigated in this research. The changes in the molecular properties of the insulating oil due to different fault conditions found had influenced the initial time response of the PDC measurement (from 0 to 100 s). In this research, the unique characteristic pattern of each condition was determined by a single unique numerical dimensionless quantity known as depolarization ratio index (DRI). DRI is used to express the changes of depolarization current shape with different fault conditions. The ratio of depolarization current between 5/100 and 10/100 s was found to have a better correlation at least more than 90% on the incipient fault in power transformer. Indeed, the DRI at 5/100 also was observed has higher accuracy especially on units with normal, overheating and arcing condition. In addition, a graphical representation of DRI value at 5/100 and 10/100 s was proposed for fault recognition in power transformer. Both DRI and graphical representation are well validated, and the proposed interpretation techniques have accuracy of more than 90% and able to identify and classify the normal, overheating and arcing condition of the in-service power transformer.

Daily human activities generate greenhouse gases. The total emission of greenhouse gases is called the carbon footprint and is expressed in carbon dioxide equivalent (CO2e) units. As a new educational institution, Universiti Teknologi Malaysia (UTM) began to take part in an Intergovernmental Panel on Climate Change (IPCC) programme that supports the reduction in carbon emissions. In this study, the total amount of CO2 produced from UTM during 4 years was measured under three categories: (1) the emissions from the fleet of university vehicles for public transportation, (2) the electricity and water emissions, and (3) the emissions produced by staff and student transportation, waste generation, paper, and maintenance by contractors. The special evaluation method is an alternative method to calculate greenhouse gases and measures all elements/sources of greenhouse gases under the same functional unit. This reference helps the assessor to avoid the double measurement of anthropogenic gases. The study results demonstrated that air transportation utilised by university students and employees and electricity usage contributed to 34.74%, 19.37%, and 18.19% of the carbon emissions, respectively. The total CO2 emissions from the three sources over 4 years were 48.442 MT. The data on the carbon footprint of the university can form the basis for monitoring, evaluation, and regulation of greenhouse gas emissions in Malaysia. Moreover, the university constructed and operates a smart house, a large solar parking lot with a capacity of 10 MW, uses solar and wind-powered lighting, and encourages the use of bicycles and electric scooters to achieve an annual reduction in the total CO2 emissions intensity. The results of this study suggested that a carbon reduction project could encourage university members and public society to an understanding of the environment and allowing UTM to become a centre of excellence for the operation of a green campus for urban areas.

This paper reports on an investigation into the effects of different multi-element oxide nanofillers on the structure and dielectric properties of polypropylene (PP)-based nanocomposites. Magnesium aluminate (MgAl2O4), calcium carbonate (CaCO3) and surface-modified calcium carbonate (CaCO3T) have been added to the PP to determine their effects on thermal properties, structural changes, dielectric response and breakdown strength. The results show that PP nanocomposites containing MgAl2O4 possess lowered breakdown strength compared to unfilled PP. In contrast, adding CaCO3 to PP results in a higher breakdown strength of the nanocomposites compared to nanocomposites containing MgAl2O4. Meanwhile, nanocomposites containing CaCO3T possess the highest breakdown strength among the systems considered. Possible mechanisms governing these dielectric property changes under alternating current and direct current electric fields are discussed.

Background Pulsed electric field (PEF) is an attractive and efficient non-thermal technology that can advance functionality, extractability, and retrieval of nutritionally beneficial compounds. For industrial PEF food processing, high electric field consistency is of importance for continuous operation and an economical return-of-investment within a short period. Scope and approach The technology uptake at an industrial scale is still low due to the shortage of reliable and more practical electrical systems. Therefore, designing an application-specific and cost-effective electrical system is essential for commercial use of this novel technology. This review describes the requirements and developments of the electrical systems employed in PEF food processing. Key findings and conclusion The process parameters and control variables of the PEF system are not only critical for the designing of the electrical systems but also for the experts of the food sciences. Inadequate or insufficient description of different engineering aspects of experimental procedures is a hindrance in allowing the work to be reproduced in other laboratories. This review describes the critical process parameters and the designing methodology of the specialized equipment required in food processing as a guide for the designers and the researchers of this technology.

Sulphur hexafluoride (SF6) gas insulated switchgear (GIS) is widely used in electrical power supply system and therefore needs regular preventive maintenance. Prediction and diagnosis analysis of faults in GIS using SF6 gas by-products was introduced previously by using 4 to 8 types of by product gases. As latest development on gas analyser, more by-product gases can be detected and used for condition monitoring of the GIS. The type, number, concentration and chemical stability of by-product gases of SF6 GIS are found to be closely correlated to the type of defect. However, the number of by-product gases used increases, the pattern for faults classification become more complex. Thus, further analysis on increasing number of by product gases using intelligent techniques such as pattern recognition is required. In this article, 12 significant by-products captured due to various sources of partial discharge fault in GIS were used. Random Forest (RF) was selected in this work as a multi-class classification technique. The analyses using RF pattern recognition with eight algorithms based on the presence and concentration of the gas by-products were carried out. The RF algorithm successfully recognises a given defect with an accuracy of 87.5% for all defects fault classification. The performance of the RF algorithm is 1.5 times better than the decision table algorithm which is the next best algorithm. This research illustrates the feasibility and applicability of an effective GIS diagnostic using gas by-products analyses, and in particular, using the RF pattern recognition.

Considering recent developments in photovoltaic (PV) systems, storage, and electrical vehicles, not unexpected that one day smart homes will also take part in energy markets directly. In this regard, the presented paper proposes a stochastic programming approach to manage the consumption of a smart home according to intermittent PV system production and uncertain energy prices to make the smart home available for taking part in the local day-ahead (DA) energy market. A battery storage system is integrated to make flexibility against price fluctuations. Furthermore, modeling of plug-in electric vehicles (PEV) is also provided, where the traveling pattern is modeled through scenarios. The goal is to maximize the daily profit of the smart home while the welfare of the inhabitants is satisfied by considering comfort constraints. In addition, the conditional value at risk (CVaR) risk index is considered to manage associated risk with gained profit. The obtained results show the effectiveness of the optimization framework, in which the expected daily profit of the homeowner can reach $1.72 per day in the risk-neutral condition.

In this paper, a unique approach based on electrical characteristics observed from measurements of contaminated polymeric insulators was established to calculate the electric field distribution over their surfaces. A case study using two different 33 kV polymeric insulator geometric profiles was performed to highlight the benefits of the proposed modeling approach. The conductance of the pollution layer was tested to establish a nonlinear field-dependent conductivity for pollution modeling. The leakage current (LC) of the polluted insulator was measured in a laboratory under clean and wet conditions. Then, using the finite element method (FEM), the electric field and current density distributions along the insulator were computed. The results showed that the insulators experienced an increase in the electric field (EF) magnitude ranging from 0.3 kV/cm to 3.6 kV/cm for the insulator with similar sheds (type I) and 2.2–4.5 kV/cm for the insulator with alternating sheds (big and small, type II) under the high rain condition with a flow rate of 9 L/h. Meanwhile, the highest electric field under fog was 1.74 kV/cm for the insulator with similar sheds and 2.32 kV/cm for an insulator with alternating sheds. Due to the larger diameter on the big shed and the longer leakage distance on the insulator with alternating sheds, the EF on the insulator with alternating sheds is higher than the EF on the insulator with similar sheds. The proposed modeling and simulation provided a detailed field condition estimation around the insulators. This is critical for forecasting the emergence of dry bands and the commencement of flashover on the surfaces of the insulators.

The current work contributes an estimate of the time-frequency characteristics of a leakage current in assessing the health condition of a polluted polymeric insulator. A 33 kV polymer insulator string was subjected to a series of laboratory tests under a range of environmental conditions, including pollution, wetting rate (WR), non-soluble deposit density (NSDD), and non-uniform distribution pollution (FT/B). The temporal and frequency features of the leakage current were then extracted and used as assessment indicators for insulator conditions based on laboratory test findings. Two indices were generated from the leakage current waveform in the time domain: the curve slope index (F1), which is determined by measuring the inclination of the curve between two successive time peaks of the leakage current, and the crest factor indicator (F2). The frequency domain of the leakage current signal was used to calculate the other two indices. These are the odd harmonic indicators derived from the odd frequency harmonics of the leakage current up to the 9th component (F3) and the 5th to 3rd harmonics ratio (F4). The findings showed that the suggested indicators were capable of evaluating insulator conditions. Finally, the confusion matrix for the experimental and prediction results obtained with the proposed indices was used to assess which indicator performed the best. Therefore, the analysis suggests an alternative and effective method for estimating the health condition of a polluted insulator through leakage current characteristics obtained in the time and frequency domains.

Electroporation is a simple but effective and sustainable food processing way of treating cell membranes with an electric field. It is employed in a variety of ways in the food industry, ranging from shelf-life extension to green extraction. Despite its wide range of applications, electroporators are out of reach for many labs due to their high development costs, and different electroporators have been tailored to specific applications. The designing sequence of an electroporator that takes the geometry of a treatment chamber and its electrical resistance into account for the design of a pulse generator has not been addressed in published literature. To meet this demand, this study presents a straightforward way to develop a simple, affordable, and portable electroporator for liquid food pasteurisation. The proposed electroporator comprises a coaxial treatment chamber with static mixers and a high-voltage Marx bank based on insulated-gate bipolar transistors (IGBTs). The generator has a 4.5 kV output voltage and a peak current rating of 1 kA; however, the modular design allows for a wide range of voltage and current ratings. Treated orange juice using thermal pasteurisation (65 °C, 30 min) was also used for comparison. The performance of the electroporator was studied using chemical and microbial tests. A significant log reduction (5.4 CFU·mL−1) was observed in both the PEF-treated samples with sieves. Additionally, the treated juice visual and chemical color analysis showed that the PEF-treated sample extended the shelf-life after 9 days of storage at 4 °C. This research also examines the energy conversion in these two processing steps. This study assists in developing further electroporators for other food applications with different treatment chambers without compromising the product’s quality.

Power systems are exposed to various physical threats due to extreme events, technical failures, human errors, and deliberate damage. Physical threats are among the most destructive factors to endanger the power systems security by intelligently targeting power systems components, such as Transmission Lines (TLs), to damage/destroy the facilities or disrupt the power systems operation. The aim of physical attacks in disrupting power systems can be power systems instability, load interruptions, unserved energy costs, repair/displacement costs, and even cascading failures and blackouts. Due to dispersing in large geographical areas, power transmission systems are more exposed to physical threats. Power systems operators, as the system defenders, protect power systems in different stages of a physical attack by minimizing the impacts of such destructive attacks. In this regard, many studies have been conducted in the literature. In this paper, an overview of the previous research studies related to power systems protection against physical attacks is conducted. This paper also outlines the main characteristics, such as physical attack adverse impacts, defending actions, optimization methods, understudied systems, uncertainty considerations, expansion planning, and cascading failures. Furthermore, this paper gives some key findings and recommendations to identify the research gap in the literature.

Various energy consumers, such as large energy consumers (LEC), are targeted to procure the demanded energy from various power markets such as the pool market and different energy resources, including renewable energy resources (RES), and conventional energy resources optimize the traded energy. In this article, a novel decision-making framework is proposed to schedule the LEC. The proposed technique in this article is based on the second-order stochastic dominance (SSD) to investigate the uncertainty in the total operation cost of the LEC. It is assumed that the market price, pool price, electricity load, and the power output of renewable energy sources (RES), including PV and WT, are uncertain parameters. In the proposed SSD-constrained stochastic programming, demand response programming (DRP) is provided to decrease the operation cost of the LEC. A case study is used to illustrate the effectiveness and efficiency of the novel SSD approach. According to the simulation results, the operation cost of LEC is remarkably decreased from 62,960 to 59,550 in the risk-neutral case (without including risk factor) and SSD case (worst case) with considering DRP, respectively.

Energy Consumption has been increasing at an alarming rate due to the growing energy need. More and more non-renewable sources are harvested to fulfill the energy demand resulting in and rising environmental health issues. However, harvesting Solar and Wind energy is considered as the best alternative in generating energy as these resources are renewable. Hybrid Renewable Energy System (HRES) has been grabbed the attention recently, as it involves with renewable, environmentally friendly sources to generate energy. The limitation of single Renewable Energy (RE) system is overcome by systems such as HRES. Even though it has been introduced different sizing and optimization techniques, due to the lack of system function, it had posed issues in calculating the optimized cost of a hybrid system considering the solar, wind resources and load demand as the optimization of the system cannot be predicted accurately. The aim of this research was to obtain optimization of a Hybrid PV-wind system in term of sizing and cost over the 20 years of the period of interest. The simulation of the PV-Wind Hybrid system using MATLAB for the verification purpose. This work includes detailed calculation using the Life Cycle Cost method for identifying all possible combinations. The combination of eleven Solar Panels, one Wind Turbine and nine Batteries was identified as the optimal Combination with LCC of RM 221,329.97 and has been verified using simulation results. Lastly, a sensitivity test was carried out using the exiting results of verified by the simulation to identify the most deterministic system in affecting LCC of the Hybrid system. Further, total Cost distribution for the Optimized hybrid PV-Wind system was conducted and identified that 50% of system cost was contributed by the Wind turbine. Determination of LCC, was done as a combination of Component and Operation costs. It was identified that Replacement cost contributed the highest while Wind turbine showed the highest Operation cost from the system cost. Thus, this work was included with the sensitivity test assuming 10% price increment for each component and it was concluded that price changes in Wind turbine results the greatest difference in LCC while further verified with the results of the simulation.