• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.6
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• pp.12-22
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• 1996

A numerous designs of PI controllers have been suggested to solve out trade-off between tracing and regulating problems. We constructed the PI controller system with two-degree-of-freedom that is more analytic and a better approach to a practical one. In the conventional H$_{2}$ design of optimal PI controllers, the cost function includes only the plant output terms due to the divergent problems. Since the platn input temr is not considered in PI controller design, occasionally, the plant input thends to be either very large or saturated. To solve the prior mentioned problems, we employed a mixed $H_2/H_{\infty}$ method that combines the H$_{2}$ design method to decide optimal parameters of PI controller and the $H_2/H_{\infty}$ design method to minimize the maximum amplitude of plant input. The calculation time of the H$_{infty}$ norm was considerably reduced by the simple scalar function obtained by the wiener-hopf factorization of non-scalar functions.

• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1571-1581
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• 2016

A novel method is proposed to construct the voltage stability boundary of power system considering different Reactive Power Control Mode (RPCM) of Doubly-Fed Induction Generator (DFIG) Wind Power Plant (WPP). It can be used for reflecting the static stability status of grid operation with wind power penetration. The analytical derivation work of boundary search method can expound the mechanism and parameters relationship of different WPP RPCMs. In order to improve the load margin and find a practical method to assess the voltage security of power system, the approximate method of constructing voltage stability boundary and the critical points search algorithms under different RPCMs of DFIG WPP are explored, which can provide direct and effective reference data for operators.

• KEPCO Journal on Electric Power and Energy
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• v.2 no.3
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• pp.409-413
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• 2016

The 500 MW rated steam turbine model in coal fired power plant is developed to be used for validation and verification of controller rather than for the education of operator. The valve, steam turbine, reheater and generator are modeled and integrated into the simulator. And the data from the plant heat balance diagram are used for estimation of the model parameters together with actual operating data. It is found that the outputs of model such as pressure, temperature and speed are similar to the operating ones. So, it is expected that the developed model will play a very big role in controller development.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.541-543
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• 2004

An optimal soot blowing system has been developed for an optimal operation of power utility boilers by both minimization of the use of steam and the number of soot blowers worked during soot blowing. Traditionally, the soot blowing system has been operated manually by operators. However, it causes the reduction of power and thermal performance degradation because all soot blowers installed in the plant should be worked simultaneously even there are lots of tubes those are not contaminated by slagging or fouling. Heat transfer area is divided into four groups, furnace, convection area including superheater, reheater and economizer, and air preheater in the present study. The condition of cleanness of the tubes is calculated by several parameters obtained by sensors. Then, a part of soot blowers works automatically where boiler tubes are contaminated. This system has been applied in a practical power plant. Therefore, comparison has been done between this system and manual operation and the results are discussed.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.127-131
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• 1993

A new learning method of both NNI and NNC by which the NNI identifies precisely the dynamic characteristics of the plant is proposed. For control of ihe nonlinear plant we use two neural networks, one -for identification and the other for control. We define a closed loop en-or which depends on identification and control error. In the proposed learning method, the closed loop en-or is utilized to train the NNI and the NNC. Computer simulation results reveal that the NNC based on proposed method is insensitive to variations of the plant parameters.

• Proceedings of the Korean Society of Plant Pathology Conference
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• 2003.10a
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• pp.105.1-105
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• 2003

The Plant growth Promoting rhizobacteria (PGPR), Pseudomonas sp. (A3) and Bacillus sp. (AT33) were isolated from the rhizosphere of Amaranthus blitum collected from soil contaminated with chromium. Both bacterial strains quantitatively reduced hexavalent chromium to trivalent chromium. Pseudomonas sp. broughter greater conversion of Cr6+ in the medium (100％) as compared to Bacillus sp.(62％). Phaseolus mungo seeds inoculated with Pseudomonas sp. or Bacillus sp. were grown under different concentration of chromium. The monitored parameters included elongation of shoot and root, fresh weight, dry weight and concentration of chromium in the shoot and root systems. As compared to non inoculated seedlings those inoculated with A3 and AT33 exhibited better growth.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05b
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• pp.683-690
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• 1996

The MIDLOOP code has been developed for the evaluation of RES pressurization transients initiated from a loss-of-Residual Heat Removal System (RHRS) during mid-loop operation after reactor shutdown. It provides a fast running and realistic tool for studying parametrically the response of important plant parameters such as pressure, temperature, and level to various plant combinations of the primary side vent, makeup, and leakage procedures and the steam generator (SG) conditions. The code consists of ten nodes representing the primary and secondary sides of a nuclear power plant and can analyze the effect of air on the primary system pressurization and primary to secondary heat transfer. The analysis results of the MIDLOOP code are in good agreement with the ROSA-IV/LSTF experiment without opening in the RCS.

• Industrial Engineering and Management Systems
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• v.15 no.2
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• pp.148-155
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• 2016

Existing power plants may consume significant amounts of fuel and require high operating costs, partly because of poor electrical power output estimates. This paper suggests a continuous conditional random field (C-CRF) model to predict more precisely the full-load electrical power output of a base load operated combined cycle power plant. We introduce three feature functions to model association potential and one feature function to model interaction potential. Together, these functions compose the C-CRF model, and the model is transformed into a multivariate Gaussian distribution with which the operation parameters can be modeled more efficiently. The performance of our model in estimating power output was evaluated by means of a real dataset and our model outperformed existing methods. Moreover, our model can be used to estimate confidence intervals of the predicted output and calculate several probabilities.

• 전기의세계
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• v.30 no.12
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• pp.822-831
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• 1981

Many different schemes of the adaptive observer and controller have been developed for both continuous and discrete systems. In this paper we have presented a new scheme of the reduced order adaptive observer for the single input discrete linear time invariant plant. The output equation of the plant, is transformed into the bilinear form in terms of system parameters and the states of the state variable filters. Using the plant output equation the discrete implicit adaptive observer based on the similar philosophy to Nuyan and Carroll is derived and the parameter adaptation algorithm is derived based on the exponentially weighted least square method. The adaptive model following control system is also constructed according to the proposed observer scheme. The proposed observer and controller are rather than simple structure and have a fast adaptive algorithm, so it may be expected that the scheme is suitable to the practical application of control system design. The effectiveness of the algorithm and structure is illustrated by the computer simulation of a third order system. The simulation results show that the convergence speed is proportinal to the increasing of weighting factor alpha, and that the full order and reduced order observer have similar convergence characteristics.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.36 no.10
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• pp.748-754
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• 1987

A robustness analysis for model reference adaptive control(MRAC) system with plant uncertainty is discussed in this paper. The adaptive control system is designed under assumptions that the controlled plant is represented by a lst order nominal model and that the system is drived by a constant reference signal. When using general gradient method(GGM), it is shown that unmodelled dynamics in plant model can cause the instability of the overall control loop during the adaptation process. However, as the algorithm of least square method(LSM) is introduced, the global stability of the system can be hold. And it is also given that the boundedness of adjustable parameters may be verified using the concept of an equilibrium point analysis.