Recent Advances in Polymer Nanocomposites Based on Polyethylene and Polyvinylchloride for Power Cables

Innovative approaches for augmenting dielectric properties in cross-linked polyethylene (XLPE): A review

Throughout the history of power systems, power cables have been used to securely and efficiently distribute electrical energy to the destined locations. Cross-linked polyethylene (XLPE), a commonly used insulator in high-voltage cables, have several desirable properties, such as low dielectric loss, high dielectric constant, high thermal conductivity, enhanced thermal stability, and superior resistance against electrical stress. However, further improvements of XLPE's performance are needed. The incorporation of large specific surface area nanoparticles, such as boron nitride nanosheets and graphene oxide, exhibited a great potential in enhancing XLPE's properties. These nanoparticles create numerous trapping sites, even at small loading levels, due to their large interfacial regions. In addition, voltage stabilisers with polar groups can scavenge high-energy electrons generated by local electric fields, thereby inhibiting the electrical tree growth. Another important aspect of enhancing XLPE's dielectric performance is the inclusion of antioxidants with phenolic groups. These antioxidants react with peroxyl radicals, mitigating their harmful effects. This review summarises the effects of nanoparticles, voltage stabilisers, antioxidants, and polymer amalgamation on dielectric performance of XLPE as an insulation material. The major challenges in dielectric insulation such as breakdown voltage strength, electrical tree growth, structural defect, space charge accumulation, and thermal aging are addressed.

Improved Insulating Properties of Polymer Dielectric by Constructing Interfacial Composite Coatings

Polymeric dielectrics exhibit remarkable dielectric characteristics and wide applicability, rendering them extensively employed within the domain of electrical insulation. Nevertheless, the electrical strength has always been a bottleneck, preventing its further utilization. Nanocomposite materials can effectively improve insulation strength, but uniform doping of nanofillers in engineering applications is a challenge. Consequently, a nanocomposite interfacial coating was meticulously designed to interpose between the electrode and the polymer, which can significantly improve DC breakdown performance. Subsequently, the effects of filler concentration and coating duration on DC breakdown performance, high field conductivity, and trap distribution characteristics were analyzed. The results indicate that the composite coating introduces deep traps between the electrode-polymer interface, which enhances the carrier confinement, resulting in reduced conductivity and enhanced DC breakdown strength. The incorporation of a composite coating at the interface between the electrode and polymer presents novel avenues for enhancing the dielectric insulation of polymers.

A Novel Polyester Varnish Nanocomposites for Electrical Machines with Improved Thermal and Dielectric Properties Using Functionalized TiO2 Nanoparticles

Recently, there has been a growing interest in polymer insulating materials that incorporate nanoscale inorganic additives, as they have shown significantly improved dielectric, thermal, and mechanical properties, making them highly suitable for application in high-voltage insulating materials for electrical machines. This study aims to improve the dielectric and thermal properties of a commercial polyester varnish by incorporating different concentrations of titanium dioxide nanoparticles (TiO2) with proper surface functionalization. Permafil 9637 dipping varnish is the varnish used for this investigation, and vinyl silane is the coupling agent used in the surface functionalization of TiO2 nanoparticles. First, nanoparticles are characterized through Fourier transform infrared spectroscopy to validate the success of their surface functionalization. Then, varnish nanocomposites are characterized through field emission scanning electron microscopy to validate the dispersion and morphology of nanoparticles within the varnish matrix. Following characterization, varnish nanocomposites are evaluated for thermal and dielectric properties. Regarding thermal properties, the thermal conductivity of the prepared nanocomposites is assessed. Regarding dielectric properties, both permittivity and dielectric losses are evaluated over a wide frequency range, starting from 20 Hz up to 2 MHz. Moreover, the AC breakdown voltage is measured for varnish nanocomposites, and the obtained data are incorporated into a finite element method to obtain the dielectric breakdown strength. Finally, the physical mechanisms behind the obtained results are discussed, considering the role of nanoparticle loading and surface functionalization.

Molecule-to-Material-to-Bio Nanoarchitectonics with Biomedical Fullerene Nanoparticles

Nanoarchitectonics integrates nanotechnology with various other fields, with the goal of creating functional material systems from nanoscale units such as atoms, molecules, and nanomaterials. The concept bears strong similarities to the processes and functions seen in biological systems. Therefore, it is natural for materials designed through nanoarchitectonics to truly shine in bio-related applications. In this review, we present an overview of recent work exemplifying how nanoarchitectonics relates to biology and how it is being applied in biomedical research. First, we present nanoscale interactions being studied in basic biology and how they parallel nanoarchitectonics concepts. Then, we overview the state-of-the-art in biomedical applications pursuant to the nanoarchitectonics framework. On this basis, we take a deep dive into a particular building-block material frequently seen in nanoarchitectonics approaches: fullerene. We take a closer look at recent research on fullerene nanoparticles, paying special attention to biomedical applications in biosensing, gene delivery, and radical scavenging. With these subjects, we aim to illustrate the power of nanomaterials and biomimetic nanoarchitectonics when applied to bio-related applications, and we offer some considerations for future perspectives.

Comparative Study of Polyethylene Films Embedded with Oxide Nanoparticles of Granulated and Free-Standing Nature

Nanocomposite polymer films are a very diverse research field due to their many applications. The search for low-cost, versatile methods, producing regulated properties of the final products, has thus become extremely relevant. We have previously reported a bulk-scale process, dispersing granulated metal oxide nanoparticles, of both unary and multi-component nature, in a low-density polyethylene (LDPE) polymer matrix, establishing a reference in the produced films’ optical properties, due to the high degree of homogeneity and preservation of the primary particle size allowed by this method. In this work, unmodified, free-standing particles, namely zinc oxide (ZnO), titanium dioxide (TiO2), aluminum oxide (Al2O3), and silicon dioxide (SiO2) are blended directly with LDPE, and the optical properties of the fabricated films are compared to those of films made using the granulation process. The direct blending process evidently allows for control of the secondary particle size and ensures a homogeneous dispersion of the particles, albeit to a lesser extent than the granulation process. Despite the secondary particle size being comparatively larger than its granulated counterpart, the process still provides a regulated degree of deagglomeration of the free-standing oxide particles, so it can be used as a low-cost alternative. The regulation of the secondary particle size tunes the transmission and reflection spectra, in both unary and mixed oxide compositions. Finally, the direct blending process exhibits a clear ability to tune the energy band gap in mixed oxides.

A Comparison of Electrical Breakdown Models for Polyethylene Nanocomposites

The development of direct current high-voltage power cables requires insulating materials having excellent electrically insulation properties. Experiments show that appropriate nanodoping can improve the breakdown strength of polyethylene (PE) nanocomposites. Research indicates that traps, free volumes, and molecular displacement are key factors affecting the breakdown strength. This study comprehensively considered the space charge transport, electron energy gain, and molecular chain long-distance movement during the electrical breakdown process. In addition, we established three simulation models focusing on the electric field distortion due to space charges captured by traps, the energy gain of mobile electrons in free volumes, the free volume expansion caused by long-distance movement of molecular chains under the Coulomb force, and the energy gained by the electrons moving in the enlarged free volumes. The three simulation models considered the electrical breakdown modulated by space charges, with a maximum electric field criterion and a maximum electron energy criterion, and the electrical breakdown modulated by the molecular displacement (EBMD), with a maximum electron energy criterion. These three models were utilized to simulate the breakdown strength dependent on the nanofiller content of PE nanocomposites. The simulation results of the EBMD model coincided best with the experimental results. It was revealed that the breakdown electric field of PE nanodielectrics is improved synergistically by both the strong trapping effect of traps and the strong binding effect of molecular chains in the interfacial regions.

Novel Hybrid Polymer Composites Based on Anthraquinone and Eco-Friendly Dyes with Potential for Use in Intelligent Packaging Materials

This study aimed to present the influence of bio-based and anthraquinone dyes and their combinations on the optical properties of ethylene-propylene (EPM) composites after thermo-oxidative and climatic aging. Therefore, the chosen polymer was filled with a natural, plant-origin flavonoid—quercetin, and with two commercial anthraquinone dyes (C.I. Solvent Yellow 163 and C.I. Solvent Red 207). The manufactured polymer composites were subjected to accelerated aging tests: weathering and thermo-oxidation, respectively. Examination of the materials’ properties indicated that the combination of synthetic and natural dyes can result in better resistance to oxidizing agents and higher thermal stability of ethylene-propylene products. Moreover, color change of quercetin-containing samples due to exposure to simulated atmospheric conditions could be a promising solution for use as aging indicators in intelligent packaging materials that will inform about the ongoing degradation process. Another interesting finding is that these samples exhibited good fungistatic activity against Candida albicans yeast and Aspergillus niger mold. Overall, this novel solution based on hybrid polymer composites containing natural and commercial dyes is a more environmentally friendly alternative to traditional materials used in the plastic packaging industry with better and more desirable properties.

An Overview of Linear Dielectric Polymers and Their Nanocomposites for Energy Storage

As one of the most important energy storage devices, dielectric capacitors have attracted increasing attention because of their ultrahigh power density, which allows them to play a critical role in many high-power electrical systems. To date, four typical dielectric materials have been widely studied, including ferroelectrics, relaxor ferroelectrics, anti-ferroelectrics, and linear dielectrics. Among these materials, linear dielectric polymers are attractive due to their significant advantages in breakdown strength and efficiency. However, the practical application of linear dielectrics is usually severely hindered by their low energy density, which is caused by their relatively low dielectric constant. This review summarizes some typical studies on linear dielectric polymers and their nanocomposites, including linear dielectric polymer blends, ferroelectric/linear dielectric polymer blends, and linear polymer nanocomposites with various nanofillers. Moreover, through a detailed analysis of this research, we summarize several existing challenges and future perspectives in the research area of linear dielectric polymers, which may propel the development of linear dielectric polymers and realize their practical application.

Novel Control Strategy for Enhancing Microgrid Operation Connected to Photovoltaic Generation and Energy Storage Systems

Recently, the penetration of energy storage systems and photovoltaics has been significantly expanded worldwide. In this regard, this paper presents the enhanced operation and control of DC microgrid systems, which are based on photovoltaic modules, battery storage systems, and DC load. DC–DC and DC–AC converters are coordinated and controlled to achieve DC voltage stability in the microgrid. To achieve such an ambitious target, the system is widely operated in two different modes: stand-alone and grid-connected modes. The novel control strategy enables maximum power generation from the photovoltaic system across different techniques for operating the microgrid. Six different cases are simulated and analyzed using the MATLAB/Simulink platform while varying irradiance levels and consequently varying photovoltaic generation. The proposed system achieves voltage and power stability at different load demands. It is illustrated that the grid-tied mode of operation regulated by voltage source converter control offers more stability than the islanded mode. In general, the proposed battery converter control introduces a stable operation and regulated DC voltage but with few voltage spikes. The merit of the integrated DC microgrid with batteries is to attain further flexibility and reliability through balancing power demand and generation. The simulation results also show the system can operate properly in normal or abnormal cases, thanks to the proposed control strategy, which can regulate the voltage stability of the DC bus in the microgrid with energy storage systems and photovoltaics.

Reliable and Robust Observer for Simultaneously Estimating State-of-Charge and State-of-Health of LiFePO4 Batteries

Batteries are everywhere, in all forms of transportation, electronics, and constitute a method to store clean energy. Among the diverse types available, the lithium-iron-phosphate (LiFePO4) battery stands out for its common usage in many applications. For the battery’s safe operation, the state of charge (SOC) and state of health (SOH) estimations are essential. Therefore, a reliable and robust observer is proposed in this paper which could estimate the SOC and SOH of LiFePO4 batteries simultaneously with high accuracy rates. For this purpose, a battery model was developed by establishing an equivalent-circuit model with the ambient temperature and the current as inputs, while the measured output was adopted to be the voltage where current and terminal voltage sensors are utilized. Another vital contribution is formulating a comprehensive model that combines three parts: a thermal model, an electrical model, and an aging model. To ensure high accuracy rates of the proposed observer, we adopt the use of the dual extend Kalman filter (DEKF) for the SOC and SOH estimation of LiFePO4 batteries. To test the effectiveness of the proposed observer, various simulations and test cases were performed where the construction of the battery system and the simulation were done using MATLAB. The findings confirm that the best observer was a voltage-temperature (VT) observer, which could observe SOC accurately with great robustness, while an open-loop observer was used to observe the SOH. Furthermore, the robustness of the designed observer was proved by simulating ill-conditions that involve wrong initial estimates and wrong model parameters. The results demonstrate the reliability and robustness of the proposed observer for simultaneously estimating the SOC and SOH of LiFePO4 batteries.

Accurate Insulating Oil Breakdown Voltage Model Associated with Different Barrier Effects

In modern power systems, power transformers are considered vital components that can ensure the grid’s continuous operation. In this regard, studying the breakdown in the transformer becomes necessary, especially its insulating system. Hence, in this study, Box–Behnken design (BBD) was used to introduce a prediction model of the breakdown voltage (VBD) for the transformer insulating oil in the presence of different barrier effects for point/plane gap arrangement with alternating current (AC) voltage. Interestingly, the BBD reduces the required number of experiments and their costs to examine the barrier parameter effect on the existing insulating oil VBD. The investigated variables were the barrier location in the gap space (a/d)%, the relative permittivity of the barrier materials (εr), the hole radius in the barrier (hr), the barrier thickness (th), and the barrier inclined angle (θ). Then, only 46 experiment runs are required to build the BBD model for the five barrier variables. The BBD prediction model was verified based on the statistical study and some other experiment runs. Results explained the influence of the inclined angle of the barrier and its thickness on the VBD. The obtained results indicated that the designed BBD model provides less than a 5% residual percentage between the measured and predicted VBD. The findings illustrated the high accuracy and robustness of the proposed insulating oil breakdown voltage predictive model linked with diverse barrier effects.

Estimating Parameters of Photovoltaic Models Using Accurate Turbulent Flow of Water Optimizer

Recently, the use of diverse renewable energy resources has been intensively expanding due to their technical and environmental benefits. One of the important issues in the modeling and simulation of renewable energy resources is the extraction of the unknown parameters in photovoltaic models. In this regard, the parameters of three models of photovoltaic (PV) cells are extracted in this paper with a new optimization method called turbulent flow of water-based optimization (TFWO). The applications of the proposed TFWO algorithm for extracting the optimal values of the parameters for various PV models are implemented on the real data of a 55 mm diameter commercial R.T.C. France solar cell and experimental data of a KC200GT module. Further, an assessment study is employed to show the capability of the proposed TFWO algorithm compared with several recent optimization techniques such as the marine predators algorithm (MPA), equilibrium optimization (EO), and manta ray foraging optimization (MRFO). For a fair performance evaluation, the comparative study is carried out with the same dataset and the same computation burden for the different optimization algorithms. Statistical analysis is also used to analyze the performance of the proposed TFWO against the other optimization algorithms. The findings show a high closeness between the estimated power–voltage (P–V) and current–voltage (I–V) curves achieved by the proposed TFWO compared with the experimental data as well as the competitive optimization algorithms, thanks to the effectiveness of the developed TFWO solution mechanism.

Towards Precise Interpretation of Oil Transformers via Novel Combined Techniques Based on DGA and Partial Discharge Sensors

Power transformers are considered important and expensive items in electrical power networks. In this regard, the early discovery of potential faults in transformers considering datasets collected from diverse sensors can guarantee the continuous operation of electrical systems. Indeed, the discontinuity of these transformers is expensive and can lead to excessive economic losses for the power utilities. Dissolved gas analysis (DGA), as well as partial discharge (PD) tests considering different intelligent sensors for the measurement process, are used as diagnostic techniques for detecting the oil insulation level. This paper includes two parts; the first part is about the integration among the diagnosis results of recognized dissolved gas analysis techniques, in this part, the proposed techniques are classified into four techniques. The integration between the different DGA techniques not only improves the oil fault condition monitoring but also overcomes the individual weakness, and this positive feature is proved by using 532 samples from the Egyptian Electricity Transmission Company (EETC). The second part overview the experimental setup for (66/11.86 kV–40 MVA) power transformer which exists in the Egyptian Electricity Transmission Company (EETC), the first section in this part analyzes the dissolved gases concentricity for many samples, and the second section illustrates the measurement of PD particularly in this case study. The results demonstrate that precise interpretation of oil transformers can be provided to system operators, thanks to the combination of the most appropriate techniques.

Optimal Estimation of Proton Exchange Membrane Fuel Cells Parameter Based on Coyote Optimization Algorithm

In recent years, the penetration of fuel cells in distribution systems is significantly increased worldwide. The fuel cell is considered an electrochemical energy conversion component. It has the ability to convert chemical to electrical energies as well as heat. The proton exchange membrane (PEM) fuel cell uses hydrogen and oxygen as fuel. It is a low-temperature type that uses a noble metal catalyst, such as platinum, at reaction sites. The optimal modeling of PEM fuel cells improves the cell performance in different applications of the smart microgrid. Extracting the optimal parameters of the model can be achieved using an efficient optimization technique. In this line, this paper proposes a novel swarm-based algorithm called coyote optimization algorithm (COA) for finding the optimal parameter of PEM fuel cell as well as PEM stack. The sum of square deviation between measured voltages and the optimal estimated voltages obtained from the COA algorithm is minimized. Two practical PEM fuel cells including 250 W stack and Ned Stack PS6 are modeled to validate the capability of the proposed algorithm under different operating conditions. The effectiveness of the proposed COA is demonstrated through the comparison with four optimizers considering the same conditions. The final estimated results and statistical analysis show a significant accuracy of the proposed method. These results emphasize the ability of COA to estimate the parameters of the PEM fuel cell model more precisely.

Promising MPPT Methods Combining Metaheuristic, Fuzzy-Logic and ANN Techniques for Grid-Connected Photovoltaic

This paper addresses the improvement of tracking of the maximum power point upon the variations of the environmental conditions and hence improving photovoltaic efficiency. Rather than the traditional methods of maximum power point tracking, artificial intelligence is utilized to design a high-performance maximum power point tracking control system. In this paper, two artificial intelligence-based maximum power point tracking systems are proposed for grid-connected photovoltaic units. The first design is based on an optimized fuzzy logic control using genetic algorithm and particle swarm optimization for the maximum power point tracking system. In turn, the second design depends on the genetic algorithm-based artificial neural network. Each of the two artificial intelligence-based systems has its privileged response according to the solar radiation and temperature levels. Then, a novel combination of the two designs is introduced to maximize the efficiency of the maximum power point tracking system. The novelty of this paper is to employ the metaheuristic optimization technique with the well-known artificial intelligence techniques to provide a better tracking system to be used to harvest the maximum possible power from photovoltaic (PV) arrays. To affirm the efficiency of the proposed tracking systems, their simulation results are compared with some conventional tracking methods from the literature under different conditions. The findings emphasize their superiority in terms of tracking speed and output DC power, which also improve photovoltaic system efficiency.