Electrical Engineering in Japan最新文献

Previously, in temperature distribution analysis inside a transformer, there was an overall analysis that simulated the core and tank. However, insulators are not taken into consideration because the analysis cost increases. Therefore, the actual oil flow differs from the analysis results, and there is a possibility that the temperature may be evaluated higher than the actual oil flow, or the location of the hot spot may differ. In this study, we first focused on the temperature change around the core and took into the insulator, which greatly contributes to the oil flow. Next, the insulation in the gap between the cores is represented by thermal resistance. This has made it possible to analyze changes in oil flow and temperature distribution inside a transformer, taking insulators into account.

Previously, in temperature distribution analysis inside a transformer, there was an overall analysis that simulated the core and tank. However, insulators are not taken into consideration because the analysis cost increases. Therefore, the actual oil flow differs from the analysis results, and there is a possibility that the temperature may be evaluated higher than the actual oil flow, or the location of the hot spot may differ. In this study, we first focused on the temperature change around the core and took into the insulator, which greatly contributes to the oil flow. Next, the insulation in the gap between the cores is represented by thermal resistance. This has made it possible to analyze changes in oil flow and temperature distribution inside a transformer, taking insulators into account.

Orthogonal-core-type variable inductors with permanent magnets can increase or decrease the line voltage without power capacitors in electric power systems. In this paper, 3-kVA orthogonal-core-type variable inductors with permanent magnets are designed based on reluctance network analysis (RNA), and verification tests are carried out. The results demonstrate that the prototypes perform as intended. Furthermore, to improve the calculation accuracy, the RNA model combined with an assumed flux path (AFP) method is proposed. The proposed method achieves a significant improvement in calculation accuracy without increasing calculation time.

To further promote renewable energy, the feed-in-premium (FIP) system was launched in April 2022 in Japan. Under the FIP scheme, renewable energy power producers and aggregators have faced new issues, which are imbalance risk due to the responsibility for planned amounts of power and market risk due to fluctuating power market prices. In order to address these issues, highly accurate renewable energy generation forecasting, imbalance reduction, and profitability enhancement technologies are required. However, comprehensive studies on the effectiveness of these necessary technologies through empirical evaluations using actual energy resources under real environments have not been sufficiently conducted. In this paper, we conduct a large-scale demonstration evaluation of the renewable energy generation forecasting technologies, the power market trading strategy technologies, and the battery control technologies using actual energy resources across the country, such as photovoltaic (PV) generators, wind power generators, and storage batteries. Through the empirical evaluations, it is clarified that the evaluated technologies contribute to reducing imbalance risk and improving profitability with respect to imbalance risk and market risk, respectively.

In this paper, we propose a new evaluation method for the spatial distribution of sensitivity to force in a cantilever-type MEMS tactile sensor developed in our laboratory. By combining the responses of two strain gauges attached to the cantilever with different coefficients, it is shown that the spatial distribution of sensitivity can be controlled, and the force application position and the magnitude of force can be predicted with high accuracy.

Electric power systems with increasing photovoltaic (PV) systems face concerns regarding degradation in frequency stability due to heightened output forecast errors. As a countermeasure, given the dynamic factors like demand, PV output, and meteorological elements, calculating the optimal reserve margin (ORM) becomes crucial for economic efficiency and resilience reinforcement. To ensure an efficient ORM, Artificial Intelligence (AI) is one of the useful strategies used to analyze the combination of all the elements. However, AI is characterized by a black box problem, and to achieve transparency, AI needs to be transformed into explainable AI. To begin with, this paper analyzed all features importance using SHapley Additive exPlanations (SHAP), adopting a Gaussian process regression model. Then, relevant explanatory variables were selected to improve the prediction accuracy of the ORM. Finally, to verify the effectiveness, this paper planned day-ahead scheduling while securing the ORM determined by the proposed method. It executed detailed demand/supply and system frequency simulations as an operation. The proposed method decreased the risk posed by PV output forecast errors and shortage of reserve margin. Also, the maximum PV capacity increased from 96.2% to 166.2% while maintaining frequency stability.

Simple and cost-effective methods for cavitation detection are required for the stable operation of pump systems. Previous researches on cavitation detection systems have used microphones or vibration sensors; however, they are costly and difficult to install. Recently, motor current signature analysis (MCSA) has been gaining attention with regard to motor fault detection. In this paper, we review the characteristics of motor current signals in a cavitation state and propose an MCSA technique for pump cavitation detection. We observed that the foot around the fundamental harmonic spectrum in the power spectral density (PSD) of current signals increased in a cavitation state. Based on these results, we propose defining an evaluation value that reflects the foot and using it for cavitation detection.

For the safe operation of a photovoltaic generating system, an insulation monitoring function, which can immediately detect deterioration of insulation between photovoltaic module strings and the earth, is indispensable. This function requires accurate measurement, low leakage current, and suppression of rising voltage against the earth. In this paper, a new insulation monitoring method of photovoltaic module strings is proposed by the improved existing self-biased method (SBM) that has an inevitable voltage rise under measurement. In this new method, both terminals of photovoltaic module strings are always connected to the ground with appropriate resistors. Theoretical discussion and experiments for this new method showed precise measurement and acceptable leakage current under various outdoor conditions. In addition, it was confirmed that this method could sufficiently decrease in the voltage rise compared with the existing SBM.

In this study, we investigated the conditions for protein synthesis by an in vitro transcription and translation (IVTT) system within giant unilamellar vesicles (GUVs) produced with a microfluidic channel. The commercial IVTT system consisted of purified components (PURE system), and DNA encoding target protein was encapsulated in GUVs and incubated to synthesize the proteins. Synthesis of green fluorescent protein (GFP) and nanopore-forming α-hemolysin were tested as the models of water-soluble protein and membrane protein, respectively. The stability of the GUVs and the efficiency of protein synthesis were assessed, focusing on variations in the concentration of the PURE system and the size of the GUVs. Our findings contribute to the development of homogeneous bioreactors and biosensors based on GUV technology.

Prediction of the risk of developing Drug-induced liver injury (DILI) is very important in drug discovery. Although animal tests usually evaluate DILI, the prediction accuracy of DILI is low because experimental animals have different metabolic pathways from humans. A few microphysiological systems (MPS) have been developed as novel evaluation systems for DILI evaluation. However, the proposed system is not yet practical due to operability, throughput issues, and prediction accuracy. Our purpose is to develop a practical DILI evaluation system. In this study, we investigate the influence of perfusion culture on hepatotoxicity tests using our previously developed Kinetic pump integrated microfluidic plate (KIM-Plate). The results of acetaminophen toxicity tests showed that perfusion culture using KIM-Plate improved the detection sensitivity of hepatotoxicity. We suggest that the liver model MPS based on KIM-Plate could be a novel DILI evaluation system that integrates highly functional liver models and coculture with immune cells.