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For ultra‐high‐voltage (UHV) systems together with high‐voltage facilities, more rationalized insulation coordination and equipment design are required. To this end, making large‐scale and long‐term field lightning‐strike observations, large amount of and practical experiments, and introducing new analysis techniques have enabled the development of advanced technologies capable of transforming conventional techniques. This paper reviews what has been developed in a Japanese electric power company in this regard. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

The Japan Electric Power Exchange (JEPX) provides a platform for the trading of electric energy in a manner similar to more traditional financial markets. As the number of market agents increase, there is an increasing need for effective price-forecasting models. Electricity price data are observed to exhibit periods of relatively stable, i.e., low-magnitude, low-variance prices interspersed with periods of higher prices accompanied by larger uncertainty. The price data time series therefore exhibits a temporal non-stationarity characteristic that is difficult to capture with typical time series modeling frameworks. In this paper, we implement models for the occurrence of price spike events where spikes are defined as observing prices above a predefined threshold set here at 25 JPY/kWh. This value corresponds to about the 90th percentile of observed prices during peak trading periods. The price spikes time series is observed to be rare events that occur in clusters. We therefore propose to model the data as a Hawkes process whereby the occurrence of a spike event increases the probability of observing more spikes in the period immediately following a price spike event. We test two variations of the classical Hawkes model: the first variation models the change in the magnitude of the underlying intensity as a function of the magnitude of the price spike while the second variation models the change in the decay rate of the underlying intensity as a function of the magnitude of the price spike. An analysis of the performance of the models based on the mean absolute error (MAE) of the spike occurrence probability, a weighted accuracy index, and the Matthews correlation coefficient (MCC) metrics shows the effectiveness of the variable magnitude variation of the Hawkes model in generating short-term forecasts of the occurrence of price spike events. The modified Hawkes model especially outperforms other candidate models as the length of the forecasting horizon increases. [ABSTRACT FROM AUTHOR]

The electric power propulsion is becoming the important development direction of ship propulsion technology recent years, as it is conducive to the realization of automation, intelligence, reduced noise, enhanced propulsion efficiency, high power density, flexible arrangement, and energy saving. The good fault‐tolerant capacity and robustness of the fault‐tolerant permanent magnet motor (FTPMM) make it a potentially highly effective and economical propulsion motor in the electric power propulsion ship than other alternatives. In this paper, the structure and mathematical model of FTPMM are analyzed and the improved sliding mode observer (SMO) is constructed according to the deviation between the observed currents and actual currents. Combined with model reference adaptive control (MRAC) method and the phase‐lock loop (PLL), the switch function is replaced by the continuous Sigmoid function to reduce the chattering and finally the rotor position estimated accuracy is improved. When the motor winding open‐circuit and short‐circuit fault occur, the current vector fault‐tolerant control strategy is introduced into the improved SMO algorithm, and the rotor position is estimated accurately under faulty conditions. Finally, the proposed improved SMO position estimation algorithm under healthy and faulty conditions is verified in Matlab/Simulink. The FTPMM position sensorless technology would play a critical role in the electric power propulsion ship, and may have a profound impact on the high‐performance advanced ships and green shipping industry as well. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Load forecasting is an essential task in the operation management of a power system. Electric power companies utilize short-term load forecasting (STLF) technology to make reasonable power generation plans. A forecasting model with low prediction errors helps reduce operating costs and risks for the operators. In recent years, machine learning has become one of the most popular technologies for load forecasting. In this paper, a two-stage STLF model based on long short-term memory (LSTM) and multilayer perceptron (MLP), which improves the forecasting accuracy over the entire time horizon, is proposed. In the first stage, a sequence-to-sequence (seq2seq) architecture, which can handle a multi-sequence of input to extract more features of historical data than that of single sequence, is used to make multistep predictions. In the second stage, the MLP is used for residual modification by perceiving other information that the LSTM cannot. To construct the model, we collected the electrical load, calendar, and meteorological records of Kanto region in Japan for four years. Unlike other LSTM-based hybrid architectures, the proposed model uses two independent neural networks instead of making the neural network deeper by concatenating a series of LSTM cells and convolutional neural networks (CNNs). Therefore, the proposed model is easy to be trained and more interpretable. The seq2seq module performs well in the first few hours of the predictions. The MLP inherits the advantage of the seq2seq module and improves the results by feeding artificially selected features both from historical data and information of the target day. Compared to the LSTM-AM model and single MLP model, the mean absolute percentage error (MAPE) of the proposed model decreases from 2.82% and 2.65% to 2%, respectively. The results demonstrate that the MLP helps improve the prediction accuracy of seq2seq module and the proposed model achieves better performance than other popular models. In addition, this paper also reveals the reason why the MLP achieves the improvement. [ABSTRACT FROM AUTHOR]

The growing demand for electricity, driven by factors such as the shift to carbon neutrality and economic growth, is a challenge shared by South Korea and Japan. South Korea, a peninsula nation, and Japan, an island country, which are both heavily dependent on foreign energy sources and have manufacturing-based industrial structures, are actively working to secure stable power supplies for their economic development. This article carries out a quantitative analysis of the roles of the South Korean and Japanese electric power sectors (EPSs) in their respective economies, seeking to identify differences and generate actionable insights for decision making and policy formulation. Utilizing the input–output (IO) technique with the latest available data, the analysis includes a demand-side model, a supply-side model, and a price-side model to examine various effects of the EPSs. The key findings reveal differences in the production-inducing, value-added creation, and job-creation effects between the two countries, highlighting operational disparities in their electricity sectors. Additionally, South Korea exhibits higher wage-inducing, supply shortage, and price-side effects than Japan, because of its public enterprise-oriented high-wage structure and a substantial manufacturing sector. These quantitative results provide valuable reference material for future government decisions and policy development in the EPS and emphasize the significant role and impact of the power sector in both countries. [ABSTRACT FROM AUTHOR]

Short‐circuit accidents hinder the supply of electric power in distribution lines. If a short‐circuit occurs, the power supply is interrupted and can be resumed only after the short‐circuit point is repaired. Identifying the short‐circuit point is time consuming because it is necessary to confirm whether the overcurrent passage indicator is operating and visually confirm the short‐circuit point. Therefore, we propose a method of installing an abnormal detection line under the high‐voltage line and identifying the short‐circuit point based on the current ratio before and after the short‐circuit flowing to the current‐measuring devices installed at both ends of the abnormal detection line. Because the current flowing in a high‐voltage distribution line at the time of the short‐circuit depends on the short‐circuit resistance value, the range of application of the short‐circuit resistance value is also discussed. We show that the method using abnormal‐detection lines can be applied to estimate the high‐resistance ground faults and disconnection points, and the ability to estimate short‐circuit points leads to the efficient use of the method using abnormal detection lines. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

This article examines recent controversies in Japan surrounding access to the power grid by renewable energy producers to think through the possibilities of a political ecology of socio-technical systems. Beginning in summer 2016, regional power utilities across Japan began denying applications from renewable energy producers seeking access to the grid because it was "at capacity." Questions about what constituted "capacity," how and by whom capacity was determined, and what energy sources were given preferential access to the grid were significant topics of contention among renewables developers, solar advocates, power utility administrators, and central government bureaucrats. On days with excess sun or wind and low power demand, renewables producers have also been denied access to maintain grid stability. Bringing together literature on the material politics of socio-technical systems and the political economy of electric power, this article examines the grid as a networked infrastructure with its own intrinsic materiality that shapes the trajectories of renewable energy transitions. It draws on interviews with central government policymakers, utility representatives, and renewables advocates to argue that regional grid operators appeal to technical constraints to restrict the amount of renewable energy on the power grid and safeguard fixed capital investments in nuclear power. It highlights the role of expertise and counter-expertise in these disputes and calls for greater attention to how the materiality of the power grid shapes the political dynamics of renewable energy transitions. [ABSTRACT FROM AUTHOR]

The history of the use of electricity in Japan began as telecommunication, which started in 1869, one year after the Meiji Restoration. The first electric arc lamp shone in Ginza, Tokyo, in 1882, the same year as the start of operation of Edison's Pearl Street Power Plant in New York. Only four years later (1886), Tokyo Electric Light Company, one of the predecessors of Tokyo Electric Power Company Holdings, started its business as the first electric power company in Japan. Many similar companies started their businesses in the following several years. In these early days, electric power companies in eastern Japan imported 50-Hz generators from Allgemeine Elektricitäts-Gesellschaft (AEG) in Germany, and those in western Japan imported 60-Hz generators from General Electric Company in the United States. From this historical background, AC 50 Hz is still used in eastern Japan and 60 Hz in western Japan. [ABSTRACT FROM AUTHOR]