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Researches on the unit commitment with transmission network have been reported recently. However, most of these researches mainly discussed the security constrained unit commitment, while the relationship between unit commitment and transmission losses was not considered. However, from the standpoint of operating reserve for ensuring power supply reliability, a unit commitment considering transmission losses is required. Further, under the deregulation and liberalization of the electric power industry, not only the line's security but also transmission losses are expected to play an important role in calculating the network access charge, and unit commitment taking into account transmission losses is also desired from this viewpoint. In this paper, a unit commitment approach with both transmission losses and line flow constraint is presented. Based on a heuristic iterative optimization method, first, an initial schedule is created by using a successively decommitting unit approach that is proposed in this paper. Then, we determine constraints included in the unit commitment schedule by a heuristic iterative optimization approach, in which an algorithm able to get rid of line overload by DC optimal power flow is developed. Through numerical simulations on two test power systems, the effectiveness of the proposed method is shown. © 2003 Wiley Periodicals, Inc. Electr Eng Jpn, 142(4): 9–19, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.10116 [ABSTRACT FROM AUTHOR]

This paper describes a new parameter tuning method for an elevator group control system. In such a system, tuning parameters describing elevator use and the building environment are important. The new tuning method uses improved genetic algorithms to follow environment changes and to give robustness. Keeping diversity is important in following environment changes. The paper also describes the addition of the random chromosome method and addition of other estimation methods to maintain diversity. Their effects are shown by simulations. © 1998 Scripta Technica, Electr Eng Jpn, 124(1), 55–64, 1998 [ABSTRACT FROM AUTHOR]

Power system analysis is the basis of operation and planning. Since power systems are very large and complex, however, long computation time is required for the analysis. Development of a fast calculation method for stability analysis is desirable. Recently, the method using multiple time-scale numerical integration algorithm was developed for analyzing long-term dynamics. This method has the problem of calculation time since the coefficient matrix is very large. It is expected that calculation time can be shortened using parallel processing. In order to increase the efficiency of parallel processing, the coefficient matrix must be divided since solution of a set of linear equations is the main part of stability analysis. In this paper, coefficient matrix is converted into BBDF matrix for effective calculation of parallel processing. Each subnetwork block can be divided again since it is sparse. The algorithm discussed in this paper was implemented on the nCUBE2S parallel processing computer system. The computing time is measured so that it can be compared to the computer time of a single-processor system. © 1997 Scripta Technica, Inc. Electr Eng Jpn, 120(4): 14–22, 1997 [ABSTRACT FROM AUTHOR]

It is very important to maintain supply reliability in the deregulated environment. The transient stability problem is one of the major concerns in studies of planning and operation of power systems. Time domain simulation is currently the best available tool for allowing the use of detailed models and for providing reliable results. The main limitations of this approach involve long computation times. Therefore, this paper proposes a transient stability evaluation method using minimum transient kinetic energy of postfault trajectories. This method can estimate critical clearing times with only two points of the minimum transient kinetic energy, regardless of whether the trajectories after the clearing time are stable or unstable. The validity of the proposed method is shown by simulation studies with the IEEJ EAST 10-machine 47-bus system. © 2010 Wiley Periodicals, Inc. Electr Eng Jpn, 174(3): 18-24, 2011; Published online in Wiley Online Library (). DOI 10.1002/eej.21018 [ABSTRACT FROM AUTHOR]

In this paper, a learning algorithm combining memory-less learning and memory-based learning is proposed for agents operating under POMDP. In the first stage of the proposed algorithm, memory-less learning is applied. The stochastic gradient method is employed as a memory-less learning algorithm. In the first stage, a state-action set series that accomplishes the task is stored in memory. In the second stage, memory-based learning is applied. In this process, only the series obtained in the first stage is used, so that this method is able to reduce significantly the amount of required memory. The proposed algorithm is applied to three simulations for comparison with the memory-less learning algorithm. Through computer simulations, it is shown that the proposed algorithm works more effectively in POMDP than ordinary memory-less learning. © 2010 Wiley Periodicals, Inc. Electr Eng Jpn, 173(1): 32–40, 2010; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20963 [ABSTRACT FROM AUTHOR]

In this paper, the Voltage Magnitude Constrained OPF (VMC-OPF) algorithm to determine the reactive power injection from compensating equipment to load bus is developed. By introducing the proposed VMC-OPF to the real power related Unit Commitment (UC) [1], a novel daily UC method taking into account the reactive power to secure bus voltage magnitude is presented. The Transmission Access Charge (TAC) and Ancillary Services Charge (ASC) are included in the objective function for considering costs of using transmission network and supplying reactive power to maintain the voltage. Using the proposed UC, the difference between two schedules based on benefit maximization and cost minimization is also discussed. To ascertain the effectiveness of the proposed UC method, we demonstrate various simulation results for a model power system of IEEE-118 bus system. © 2007 Wiley Periodicals, Inc. Electr Eng Jpn, 162(3): 17–26, 2008; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20590 [ABSTRACT FROM AUTHOR]

Blind deconvolution is a method of recovering transmitted signals from only received signals. The probability distribution method is one of the blind deconvolution methods. This method has two problems: it has slower convergence and its reliability is lower. In this paper, we propose a new algorithm for solving these two problems. The proposed algorithm is as follows. (1) It is based on the adaptive processing with each sample. (2) Kurtosis is adaptively estimated by recovered signals with each sample. (3) Cost function is decided by kurtosis. (4) Transmitted signals are recovered by received signals using decided cost function on the sample time. We confirm the validity of the new algorithm by computer simulation. © 2007 Wiley Periodicals, Inc. Electr Eng Jpn, 162(1): 56–65, 2008; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20317 [ABSTRACT FROM AUTHOR]

We have proposed the multirate discrete Fourier transform (MR-DFT) as one of the DFT algorithms. The feature of the MR-DFT is that only one multiplication is used for each Fourier coefficient. Therefore, the number of multiplications can be decreased compared with the conventional DFT. In this paper, for applications of the MR-DFT, we consider how the noise affects the estimation performance of the MR-DFT. Then we propose two improved algorithms of the estimation performance, that is, a shifted multirate discrete Fourier transform (SMR-DFT) and a parallel shifted multirate discrete Fourier transform (PSMR-DFT). The SMR-DFT prevents an aliasing of the additive noise by a frequency modulation. The PSMR-DFT performs the parallel processing of the SMR-DFT with different sample points using the periodicity of an input signal. The estimation performances of the proposed algorithms are compared with MR-DFT by computer simulations. The SMR-DFT could prevent the degradation of the estimation performance of the MR-DFT in the lower components caused by the wide bandwidth noise. Hence its estimation variance could become 0.61 times that of the MR-DFT. Furthermore, the PSMR-DFT could improve the estimation variance of the SMR-DFT to 0.46 times. Comparing the number of operations of the proposed algorithms with the MR-DFT, the number of additions has increased, however, the number of multiplications has the same complexity. © 2004 Wiley Periodicals, Inc. Electr Eng Jpn, 150(2): 20–27, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20044 [ABSTRACT FROM AUTHOR]

Power systems have become very large, and in addition the forthcoming open electricity market will make power system operation more complex. Therefore, power system operation must become more efficient and flexible. Very fast power system simulation is a means of achieving more sophisticated power system on-line monitoring and control, and parallel computing is a key technology for very fast power system simulation. This paper proposes an efficient and fast parallel network calculation algorithm that will contribute to the development of fast power system simulation programs. Numerical examples show that the proposed method using six processors is about 4.0 times as fast as the usual serial algorithm when applied to a large-scale radial power system and about 3.2 times as fast when applied to a large-scale loop power system. © 2001 Scripta Technica, Electr Eng Jpn, 135(3): 26–36, 2001 [ABSTRACT FROM AUTHOR]

Frequency domain subspace identification algorithms have been studied recently by several researchers in the literature, motivated by the significant development of the more popular time domain counterparts. Usually, this class of methods are focused on discrete-time models, since in the case of continuous-time models, the data matrices often become ill-conditioned if we simply rewrite the Laplace operator s as s = jω, where ω denotes the frequency. This paper proposes an efficient and convenient approach to frequency domain subspace identification for continuous-time systems. The operator w = (s-α)/(s+α) is introduced to avoid the ill-conditioned problem. Hence, the system can be identified based on a state-space model in the w-operator. Then the estimated w-operator state-space model can be transformed back to the common continuous-time state-space model. An instrumental variable matrix in the frequency domain is also proposed to obtain consistent estimates of the equivalent system matrices in the presence of measurement noise. Simulation results are included to verify the efficiency of the proposed algorithms. © 2000 Scripta Technica, Electr Eng Jpn, 132(1): 46–56, 2000 [ABSTRACT FROM AUTHOR]