• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.8
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• pp.398-402
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• 2002

The ELD computation has been based upon the so-called B-coefficient which uses a quadratic approximation of system loss as a function of generation output. Direct derivation of system loss sensitivity based on the Jacobian-based method was developed in early 1970s', which could eliminate the dependence upon the approximate loss formula. However, both the B-coefficient and the Jacobian-based method require a complicated Procedure for calculating the system loss sensitivity included in the constraints of the optimization problem. In this paper, an ELD formulation in which only the bus power equations are defined as the constraints has been introduced. Derivation of the partial derivatives of the system loss with respect to the generator output and calculation of the penalty factors for individual generators are not required anymore in proposed method. A comprehensive solution procedure including calculation of the Jacobians and Hessians of the formulation has been presented in detail. Proposed ELD formulation has been tested on a sample system and the simulation indicated a satisfactory result.

• Journal of the Society of Naval Architects of Korea
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• v.37 no.4
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• pp.11-18
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• 2000

This paper is concerned with the generation of an optimal forward hull form by a nonlinear programming method. A Rankine source panel method based on the inviscid and potential flow approximation is employed to calculate the wave-making resistance and SQP method is also used for the optimization. The hull form is represented by a spline function. The forward hull form of a minimum wave resistance with the given design constraints is generated. In addition, the forward hull form of a minimum total resistance by considering the frictional resistance together with an empirical form factor is produced and compared with the former result.

• Journal of Korea Water Resources Association
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• v.41 no.1
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• pp.35-47
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• 2008

The low flow analysis is an important part in water resources engineering. Also, the results of low flow frequency analysis can be used for design of reservoir storage, water supply planning and design, waste-load allocation, and maintenance of quantity and quality of water for irrigation and wild life conservation. Especially, for identification of the uncertainty in frequency analysis, the Bayesian approach is applied and compared with conventional methodologies in at-site low flow frequency analysis. In the first manuscript, the theoretical background for the Bayesian MCMC (Bayesian Markov Chain Monte Carlo) method and Metropolis-Hasting algorithm are studied. Two types of the prior distribution, a non-data- based and a data-based prior distributions are developed and compared to perform the Bayesian MCMC method. It can be suggested that the results of a data-based prior distribution is more effective than those of a non-data-based prior distribution. The acceptance rate of the algorithm is computed to assess the effectiveness of the developed algorithm. In the second manuscript, the Bayesian MCMC method using a data-based prior distribution and MLE(Maximum Likelihood Estimation) using a quadratic approximation are performed for the at-site low flow frequency analysis.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.4
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• pp.343-350
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• 2000

In this paper, we propose the Multi-FPNN(Fuzzy Polynomial Neural Networks) model based on FNN and PNN(Polyomial Neural Networks) for optimal system identifacation. Here FNN structure is designed using fuzzy input space divided by each separated input variable, and urilized both in order to get better output performace. Each node of PNN structure based on GMDH(Group Method of Data handing) method uses two types of high-order polynomials such as linearane and quadratic, and the input of that node uses three kinds of multi-variable inputs such as linear and quadratic, and the input of that node and Genetic Algorithms(GAs) to identify both the structure and the prepocessing of parameters of a Multi-FPNN model. Here, HCM clustering method, which is carried out for data preproessing of process system, is utilized to determine the structure method, which is carried out for data preprocessing of process system, is utilized to determance index with a weighting factor is used to according to the divisions of input-output space. A aggregate performance inddex with a wegihting factor is used to achieve a sound balance between approximation and generalization abilities of the model. According to the selection and adjustment of a weighting factor of this aggregate abjective function which it is acailable and effective to design to design and optimal Multi-FPNN model. The study is illustrated with the aid of two representative numerical examples and the aggregate performance index related to the approximation and generalization abilities of the model is evaluated and discussed.

• Ocean Systems Engineering
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• v.5 no.3
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• pp.139-160
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• 2015

The global performance of the 5MW OC4 semisubmersible floating wind turbine in random waves was numerically simulated by using the turbine-floater-mooring fully coupled and time-domain dynamic analysis program FAST-CHARM3D. There have been many papers regarding floating offshore wind turbines but the effects of second-order wave-body interactions on their global performance have rarely been studied. The second-order wave forces are actually small compared to the first-order wave forces, but its effect cannot be ignored when the natural frequencies of a floating system are outside the wave-frequency range. In the case of semi-submersible platform, second-order difference-frequency wave-diffraction forces and moments become important since surge/sway and pitch/roll natural frequencies are lower than those of typical incident waves. The computational effort related to the full second-order diffraction calculation is typically very heavy, so in many cases, the simplified approach called Newman's approximation or first-order-wave-force-only are used. However, it needs to be justified against more complete solutions with full QTF (quadratic transfer function), which is a main subject of the present study. The numerically simulated results for the 5MW OC4 semisubmersible floating wind turbine by FAST-CHARM3D are also extensively compared with the DeepCWind model test results by Technip/NREL/UMaine. The predicted motions and mooring tensions for two white-noise input-wave spectra agree well against the measure values. In this paper, the numerical static-offset and free-decay tests are also conducted to verify the system stiffness, damping, and natural frequencies against the experimental results. They also agree well to verify that the dynamic system modeling is correct to the details. The performance of the simplified approaches instead of using the full QTF are also tested.