It is necessary for polymeric materials to have superior tracking resistance against various stress conditions for outdoor applications. In this study, the effect of nano-sized alumina tri-hydrate (ATH) particles on the tracking resistance of silicone rubber (SiR) is studied. Specimens with filler loadings of 1, 3, 5, 10, and 20 wt % are used for performance characterization. From the inclined plane test (IPT) results, apparent improvement in tracking resistance was achieved by mixing 3 wt % of nano-sized fillers, compared to unfilled specimens. ATH/SiR nanocomposites with 5 wt % loading showed comparable tracking performance to SiO₂/SiR microcomposites with 20 wt % loading. For detailed analysis, measurements of surface contact angle (SCA) and surface leakage current, and thermo-gravimetric analysis (TGA) were performed. As the nano-ATH filler concentration increased, both thermal stability and leakage current characteristics were improved. Such results agreed with the tracking resistance performance by showing that thermal decomposition and surface charge transport is inhibited in ATH/SiR nanocomposites. Furthermore, performance improvement in nanocomposites was achieved, even at low filler loadings, compared to microcomposites. Meanwhile, the change in SCA was found to be rather limited, regardless of filler loading and filler size.

In order to implement reliable and flexible power management among energy sources, a decentralized power management approach for electrical power systems (EPSs) in the more electric aircraft (MEA) is studied. Considering the increased use of electrical power for various functions, the performance of MEA would be determined by the design and operation of the EPS. By using a virtual impedance that includes both a resistive term and an inductive term, autonomous power sharing is realized. Because of the frequency dependence in the virtual impedance, different power sharing ratios between steady state and transient state can be considered. Not only the operation of various power sources is coordinated without supervision of a centralized controller, but also the operation profile of each source can be adjusted to meet output characteristics of each source. To demonstrate the effectiveness of the proposed approach, a series of simulations that consider various virtual impedance configurations were conducted. The proposed approach contributes to a higher level of operational flexibility, while enabling reliable and cost-effective management of MEAs.

Due to the increasing use of Electric Vehicles (EVs), the effect of the EV charging power demand on the reliability of the power system infrastructure needs to be addressed. In apartment complexes, which have emerged as a common residential type in metropolitan areas and highly populated districts, high charging demand could result in substantial stress to distribution networks. In this work, the effect of EV charging power demand in an apartment complex on the aging of the Distribution Transformer (DT) is studied. A methodology based on the stochastic characterization of vehicle usage profiles and user charging patterns is developed to obtain realistic EV charging demand profiles. Based on the modeled EV charging profile and the transformer thermal model, the effect of different EV penetration ratios on DT aging for an apartment complex in the Republic of Korea is studied. Results for an EV penetration ratio of up to 30% indicated that DT aging could be accelerated by up to 40%, compared to the case without EV charging. To mitigate this accelerated DT aging caused by EV charging, the effectiveness of two integration approaches of Photovoltaic (PV) sources was studied. Based on a case study that included a realistic PV generation profile, it was demonstrated that a significant contribution to DT reliability could be achieved via the operation of PV sources. A more apparent contribution of PV integration was observed with an energy storage installation at higher EV penetration ratios. At an EV penetration ratio of 30%, a maximum decrease of 41.8% in the loss-of-life probability of the DT was achieved. The effects of different PV integration approaches and power management details on DT aging were also studied. The results demonstrate that the EV charging demand could introduce a significant level of stress to DTs and that this impact can be effectively mitigated by installing PV sources. These observations are expected to contribute toward the effective planning of power system infrastructures that support the design of sustainable cities with the widespread use of EVs.

Thanks to the performance improvement introduced by micro sized functional fillers, application of epoxy composites for electrical insulation purposes has become popular. This paper investigates the dielectric properties of epoxy micro-composites filled with alumina (Al₂O₃). In particular, measurements of relative permittivity, dissipation factor, and electrical breakdown are performed, and a comprehensive statistical analysis on dielectric properties was conducted. AC breakdown strength (AC-BDS) was analyzed for normal distribution using four methods (Anderson–Darling, Shapiro–Wilk, Ryan–Joiner, and Kolmogorov–Smirnov). In addition, the AC-BDS was analyzed at risk probabilities of 1%, 5%, 10%, and 50% using Weibull distribution functions. Both normal and Weibull distributions were evaluated using the Anderson–Darling (A-D) statistic and p-value. Additionally, the log-normal, gamma, and exponential distributions of AC-BDS were examined by A-D goodness-of-fit test. The hypothesis test results of AC-BDS were fit by normal and Weibull distributions, and the compliance was evaluated by p-value and each method statistics. In addition, the experimental results of AC-BDS were fit by log-normal and gamma distributions, and the goodness-of-fit was evaluated by p-value and A-D testing. On the other hand, exponential distribution was not suitable for p-value and A-D testing. The results showed that the distributions of AC-BDS were the best using log-normal distribution. Meanwhile, statistical analysis results verified the apparent effect of temperature on dielectric properties using a paired t-test. The analysis results of this paper not only contribute to better characterization of epoxy/Al₂O₃ micro-composites but also introduce a comprehensive approach for performing statistical analysis for electrical insulation materials.

Benefits of energy storage systems (ESSs) are being investigated to figure out whether ESSs are worthwhile to install and operate. As ESSs are addressed as an effective tool to mitigate variability and uncertainty of renewable resources, measurements of their values are more emphasized. This paper examines benefits of ESSs, particularly for ESSs cooperating with solar photovoltaic (PV) or wind farms, using a stochastic unit commitment (UC) model co-optimizing energy and reserves by the ESSs with enhanced deliverability of the deployed reserves. For benefit measurements, cost savings, renewable energy generation improvements, and carbon dioxide emissions reduction are quantified and compared under different operational conditions of the ESSs. Optimal UC, energy, and upward&downward reserve schedules by the thermal generators and ESSs are provided by the proposed simulation model. The model is also designed to achieve environmental policy goals: 30% renewable energy generation and capped carbon dioxide emissions for low carbon electricity generation. The uncertainties of renewable resources–available wind and solar DNI–and electric load, are modeled as random variables, and two-stage stochastic mixed integer linear programming is applied to represent the given uncertainties in the formulation. Scenarios for random variables are generated using the autoregressive-to-anything (ARTA) process. The results show that operating the ESSs with providing downward reserves improves efficiency of UC by committing a small number of conventional generators and significantly increases benefits.

In this paper, a correction coefficient to reduce an error between 2D FEA and 3D FEA results. 2D FEA results of a flux concentrating machines such as Spoke type PMSM has considerable error compared to 3D FEA results because of 3D effects. Therefore, 3D FEA is required to predict the performances precisely for that kind of machines but it is too much time consuming task. This paper proposed the correction coefficient to get accurate results with 2D FEA. Compared to previous studies, the proposed coefficient can consider the effect of both the axial linkage flux and the axial leakage flux. Furthermore, the proposed general-purpose correction coefficient could be easily applied to any complex shaped Spoke type PMSM without complex mathematical calculations. In order to verify the proposed correction coefficient, 2D and 3D FEA analysis was performed on various models. Finally, the validity was finally verified through comparison with actual experimental results for prototypes with specific specifications.