Tsuguhiro Takahashi

New optical-waveguide pockels sensor for measuring electric fields

An optical electric field sensor using a Pockels crystal which has the advantage of directly measuring the electric field in a space with limited disturbance of its distribution has been studied. We present an optical waveguide technique which has been developed to miniaturize the sensor. In a prototype sensor a light beam is propagated along a z-direction waveguide in a y-cut LiNbO3 crystal. The width of the waveguide is 7 µ m and its length is 4.39 mm. The sensor is not based on an interferometer but on a single waveguide. The sensor has a simple and optimum configuration, and its output has good linearity to applied electric fields. Its frequency and temperature characteristics are presented. A new and smaller sensor with a waveguide 1 mm in length has been developed. It has almost the same configuration as the prototype sensor except for a smaller size. Results of measurement of ac and step electric fields using this sensor are presented.

Study of maintenance strategy support tools for electric power apparatus

The development of decision support tools for creating a maintenance strategy for electric power equipment based on asset management technique has become very intensive to reduce maintenance costs due to the liberalization of the power industry. In recent years, many papers have been presented about asset management in this area, but there have not yet been many concrete proposals. In this article, we introduce two approaches of decision support tool development for power equipment in CRIEPI. One is to support the evaluation of dissolved gas analysis for oil-immersed transformers. The tool provides comparison with data obtained from the same kind of transformers, and gives criteria among them. The other approach is to evaluate the average annual maintenance cost of equipment by considering the overhaul effect and failure risk, which provides an optimum overhaul strategy with suitable parameters.

Structural learning approach to replacing unreliable units in a power system

Power supply failure will cause major social loss. Therefore, power supply systems have been required to be highly reliable. This research deals with a significant and effective method to decide the investment in a power system damage of the power supply on the society. In CMD2007 Korea, we proposed mean-variance approach to replacing unreliable units in a power system. This paper extends the method so as to solve a problem efficiently. In this research, we will propose the structural learning of a mutual connective neural network. The proposed method enables us to solve the problem defined in terms of mixed integer quadratic programming. In this research, an analysis is performed by using the concepts of the reliability and risks of units evaluated using a variance-covariance matrix and also the effect and expenses of replacement are measured. Mean-variance analysis is formulated as a mathematical programming with two objectives to minimize the risk and maximize the expected return. Finally, we employ a Boltzmann machine to solve the meanvariance analysis efficiently. The result of our method is exemplified using a power network system in Tokyo Metropolitan. By using this method, a more effective selection of results is obtained. In other words, the decision makers can select the expected investment rate and risk of each ward depending on the given total budget. For this reason, the effectiveness of the decision making process can be enhanced.

Development of asset management support tools for electric power equipment

To establish maintenance strategies to reduce costs is one of the crucial issues of electric power industry. So asset management support tools are expected to be developed. The authors have developed support tools for asset management of several kinds of electric power equipment, such as transformers, gas-insulated switchgears, overhead transmission lines. In this report, some of the tools are explained and some important points to develop those tools based on the authors experiences during development processes of those tools. Those tools are aimed to give the minimum maintenance cost over target time interval such as 30 years based on the maintenance cost data. The authors also develop an evaluation model for typical maintenance methods, CM (corrective maintenance), TBM (time based maintenance) and CBM (condition based maintenance) which utilizes several input information, such as equipment age distribution, life time probability density distribution and accuracy of life time diagnosis. This model can evaluates annual and average maintenance cost during operation period of equipment, and these maintenance methods are compared each other.

Development of pre-breakdown discharge detection test for aged XLPE cable to find a deteriorating water tree

XLPE cables have been widely used in power transmission and distribution system especially in urban areas, since about 40 years ago. Nowadays, some XLPE cables have been operated for about 30 years, which is designed lifetime in their production. Therefore, understanding voltage withstand stress of aged XLPE cable is important for reliable operation and optimized replacement planning for the aged XLPE cable. CRIEPI has been investigating ac voltage withstand level and the degradation cause for aged XLPE cables that are removed from actual power grid due to replacement. This paper introduces the outline of the pre-breakdown discharge detection test system and some development of testing technique, and a characteristic result.