본 논문에서는 계통을 분할하여 측정시스템을 설계하는 계층적 알고리즘을 제시 하였다. 계통이 대규모화 함에 따라 최적측정시스템을 위한 기존의 알고리즘들은 과다한 컴퓨터 기억용량을 여구하게 되었다. 본 알고리즘은 이 문제점을 해결하기 위해 계통을 분할하여 계통 분할시 발생되는 경계측정점을 등가화하는 계층적 방법을 이용하였다. 이 방법을 측정 시스템 설계에 적용한 결과 계산시간과 컴퓨터 기억용량에서 상당한 감소 효과를 보았으며 대규모 계ㅖ통적용에 잇어서도 만족할 만한 정확도를 얻었다. 또한 제시된 알고리즘을 여러 계통에 적용하여 성계총 적용 가능성을 보였다.

The problem of optimal transmission system planning is to find the most economical locations and time of transmission line construction under the various constraints such as available rights-of-way, finances, the technical characteristics of power system, and the reliability criterion of power supply, and so on. In this paper the constraint of right-of-way is represented as a finite set of available rights-of-way. And the constructed for a unit period. The electrical constraints are represented in terms of line overload and steady state stability margin. And the reliability criterion is dealt with the suppression of failure cost and with single-contingency analysis. In general, the transmission planning problem requires integer solutions and its objective function is nonlinear. In this paper the objective function is defined as a sum of the present values of construction cost and the minimum operating cost of power system. The latter is represented as a sum of generation cost and failure cost considering the change of yearly load, economic dispatch, and the line contingency. For the calculation of operating cost linear programming is adopted on the base of DC load flow calculation, and for the optimization of main objective function nonlinear Branch-and-Bound algorithm is used. Finally, for improving the efficiency of B & B algorithm a new sensitivity analysis algorithm is proposed.

A Multi-grid method is introduced to Finite Element Analysis of electromagnetic field problems in order to reduce the computational time. The puropse of this work is to study how to intermix discretization and solving process, thereby making the process more effective and to find the optimal factors of Multi-grid method. Several numerical experiments with linear models of uniform and nonuniform grids confirm that the proposed algorithm can reduce the computational time very effectively as compared with con ventional iterative methods. The best results are obtained with V cycle and S.O.R. with the acce leration factor of 1.3-1.4 for smoothing.

In this paper, the analysis of a generating torque characteristics of 2-phase induction motor driven with the phase control method is presented. The generating torque equations which represent average torque and pulsating torque are derived from the elementary machine model. The calculating equations which can get the values of average torque and pulsating torque is expressed by the parameters of the equivalent circuit of 2-phase induction motor. According to the calculating equations, these performance characteristics are investigated under various conditions. Finally, a strategy to eliminate non-linearity and pulsating torque generated in driving 2-phase induction motor with the phase control method is presented.

An adaptive control problem for a plant with unmodelled dynamics is studied. The upper bounds of the output due to the unmodelled dynamics and measurement noise is assumed to be known. This problem was studied by Middleton et al. They used a modified form of the least square method in estimating the plant paramaters. In this paper, the bounds of the parameters are estimated by linear programming and the parameters are estimated by the projetion type algorithm incorporating the bounds of the parameters. The stability of the proposed adaptive control system can be proved in nearly the same way as the proof of Middleton. The performance of the proposed method is found to be much better than the method of Midlleton's with respect to the parameter convergence and plant output in computer simulations.

In the presence of unmodeled dynamics, the robustness of adaptive pole assignment control using new pseudo-plant is presented. The pseudo-plant proposed by Donati et al. is modified as the gain of low pass filter can be set from zero to one. This modified pseudo-plant results in the reduction of modeling error. It is shown that not only this approach is insensitive to input frequency but also it improves the conic condition developed by Ortega et al. which is required to assure stability of adaptive control system despite the model-plant mismatch. A simple method to compensate the tracking error due to the use of pseudo-plant is considered.