This paper presents an overview of the next-generation power electronics technology for the Japanese-version smart grid. It focuses on a grid-level battery energy storage system, a grid-level STATCOM (STATic synchronous COMpensator), and a 6.6-kV BTB (Back-To-Back) system for power flow control between two power distribution feeders. These power electronic devices play an important role in achieving load frequency control and voltage regulation. Their circuit configurations based on modular multilevel cascade PWM converters are characterized by flexible system design, low voltage steps, and low EMI (Electro-Magnetic Interference) emission. Their downscaled laboratory models are designed, constructed, and tested to verify the viability and effectiveness of the circuit configurations and control methods.

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In this paper, the authors propose an improved identification method of the magnetizing inrush current phenomena. To improve the estimation of the saturation on/off time, the Aitken's Δ²-process is adopted. And a new index δI, which is a variation current, is introduced. The merits of Aitken's Δ²-process are the simple algorithm and the high precision to oscillation noise. Then, the proposed method is adapted to a measured data, in which the oscillation noise is caused. The proposed method gives a high precision in these cases.

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We have developed a new method to determine an optimal generator scheduling using probabilistic demand scenarios. The demand scenarios are created statistically as a set of load curves by the past demand data. Covariance matrix is used to reconstruct the distribution of the demand scenarios. Unit commitment calculation is executed for each demand scenario and the operation cost is estimated. Optimal generator scheduling is selected by the expected value of the unit price with including the additional cost to compensate the demand variation. The risk of the scenarios is also estimated to select the optimal generation scenario. The advantage of this method is that the optimum generator scheduling can be calculated in the present load dispatching system since the existing scheduling algorism can be easily adopted with a minimum modification.

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Recently, many long cable lines are under construction and planned. A reliable operation of a cable system necessitates an accurate calculation of sequence impedances of the system. It has been a common practice that those sequence impedances or currents are measured after the installation and it is difficult to predict those values beforehand. This paper derives theoretical formulas of the sequence currents for a cross-bonded cable and a normal-bonded cable. The accuracy of the proposed formulas is verified through a comparison with EMTP simulations.

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This paper proposes an efficient multi-objective meta-heuristics (MOMH) for optimal allocation of step voltage regulators. The step voltage regulators (SVRs) deal with the voltage deviations in distribution networks. Recently, the deregulated and competitive power markets bring about uncertainties such as load growths and output of renewable energy like wind power generators, etc. This paper considers the uncertainties in Monte-Carlo-simulation-based method. Also, this paper makes use of improved the strength pareto evolutionary algorithm (SPEA2) for the problems efficiently. It has the remarkable accuracy and the diversity of the solution sets in MOMH. Therefore, it allows system planners to evaluate with many high quality solutions. The proposed method is successfully applied to a sample system.

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This paper presents estimation techniques of machine parameters for power transformer using design procedure of transformer and genetic algorithm with real coding. Especially, it is very difficult to obtain machine parameters for transformers in customers' facilities. Using estimation techniques, machine parameters could be calculated from the only nameplate data of these transformers. Subsequently, EMTP-ATP simulation of the inrush current was carried out using machine parameters estimated by techniques developed in this study and simulation results were reproduced measured waveforms.

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We present a new Particle Swarm Optimization (PSO) for the optimal radial network reconfiguration. Network reconfiguration is a combinatorial problem. The combination of search space increases exponentially with the number of switches. Fixed loop coding structure is used to reduce the number of combinations. The feature of this method is to introduce mutation operation for discrete decimal problem to PSO. This method, discrete decimal PSO with mutation (DDM-PSO), is applied to both a reconfiguration problem with current constraint and a realistic loss minimization problem. For the former problem, test system with 37 nodes and 63 branches, the proposed method improves the maximum arrival number at the optimal solution from 11 to 18 compared to PSO without mutation in twenty trials. This number of DDM-PSO is also more than that of GA, 11. For the other problem, 112 branches and 102 nodes network, the average losses of the DDM-PSO generated network are less than those of the PSO without mutation by 2.3%. And the proposed method improves the maximum arrival number at the optimal solution from 2 to 17 compared to PSO without mutation in twenty trials. These results show effectiveness of the developed method.

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Massive penetration of photovoltaic generation (PV) power stations may cause some serious impacts on a power system operation due to their volatile and unpredictable output. Growth of uncertainty may require larger operating reserve capacity and regulating capacity. Therefore, in order to utilize a PV power station as an alternative for an existing power plant, improvement in controllability and adjustability of station output become very important factor. Purpose of this paper is to develop the scheduled operation technique using a battery system (NAS battery) and the meteorological forecast. The performance of scheduled operation strongly depends on the accuracy of solar radiation forecast. However, the solar radiation forecast contains error. This paper proposes scheduling method and rescheduling method considering the trend of forecast error. More specifically, the forecast error scenario is modeled by means of the clustering analysis of the past actual forecast error. Validity and effectiveness of the proposed method is ascertained through computational simulations using the actual PV generation data monitored at the Wakkanai PV power station and solar radiation forecast data provided by the Japan Weather Association.

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SCG (Superconducting Generator) has a superconducting field winding, which leads to many advantages such as small size, high generation efficiency, low impedance, and so on, and be considered as one of the candidates to meet the needs of high stability and high efficiency in the future power system networks. SCG with high response excitation is especially expected to be able to enhance the transient stability of power system by its SMES (Superconducting Magnetic Energy System) effect. The SMES effect of SCG is recognized that its behaviors are dominated by the structures and controls of its excitation system. For this reason, in order to verify exactly how the SMES effect of SCG influences on the power system stability, the electrical circuits of SCG high response excitation are modeled in detail for conducting digital simulation, and its influence on excitation voltage and active power output of SCG are discussed as well. The simulation results with a typical one machine - infinite bus power system model shows that the SMES effect can be certainly obtained when its exciting power is supplied from SCG terminal bus and may considerably lead to an improvement of power system transient stability.

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We have proposed the condition assessment method of the GIS based on the gas analysis. This method utilizes the accumulation of SF₆ decomposition gas which is generated by the partial discharge or overheating and has a advantage that does not receive the influence of electrical noise. However, the decomposition gas is adsorbed by the adsorbent that was installed at the equipment as soon as it is generated. Therefore, an efficient separation and sensitive analysis method of the decomposition gas from the adsorbent are necessary.
In this report, we proposed the simple separation and sensitive analysis method of decomposition gas. The decomposition gas in the adsorbent was separated as the aqueous solution by immersing the adsorbent in the purified water, and adsorbent aqueous solution was analyzed by water quality meter and ion chromatograph. As the result of water quality meter analysis, the characteristics of aqueous solution including the decomposition gas were greatly different from the one that doesn't contain decomposition gas. As the result of ion chromatograph analysis, the ingredient of the decomposition gas was able to be detected directly from aqueous solution. Therefore, it was shown that these proposed method are very useful for condition assessment method of GIS.

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In this paper, the lifetime estimation method was discussed in view of Weibull distribution. For the case of power capacitor, the conversion factor between model specimen and practical equipment can be calculated by using the ratio of the electrode edge length of them and the Weibull shape parameter of the normalized V-t data obtained from the model samples. The actual failure rate of the power capacitor with PP film/capacitor-paper composite dielectric system was found to agree well with the estimated failure rate from the model samples.

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