• 전기의세계
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• v.15 no.3
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• pp.1-7
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• 1966

The past several years have strongly anticipated the advent of a more integrated system control combining active power and voltage-reactive power controls. This paper presents a new approach to the intergrated system control with primary emphasis on the development of a new control method which combines the conventional economical load dispatching(ELD) and voltage-reactive power controls. The control method, in its fundamental principle, first determines the optimal active power allocation in accordance with the conventional ELD controller. By a proper manipulation of the remaining reactive power sources in the system, the control method then reduces the transmission losses of the system by the adjustment of system voltage distribution and also by the proper allotment of reactive power flows.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.2
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• pp.83-92
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• 1989

This paper presents a load frequency control by optimal linear tracking, which can be well adapted to practical power systems with successive load disturbances. Conventional Load Frequency Controls (LEC's) have a feedback control scheme of the state error deviated from the post-disturbance steady state. This requires the modification of reference everytime the system encounters load changes. In this study, a new feedback scheme of LEC is developed by using the optimal linear tracking method with a fixed reference. As a result, the proposed LFC, which requires no reference modification, can be efficiently applied to power systems with successive disturbances such as load changes due to the on-off operations of reclosers or feeder switches. Another feature of the proposed LFC is that it adopts an algorithm to calculate an optimal post-fault steady state with the consideration of control input changes. The proposed LFC has been tested for a 2-area power system, which shows that it can be well adapted to successive load disturbances with good frequency response.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.137-144
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• 1998

This paper proposed a optimal scale factors technique of a fuzzy-neural network for a load frequency control of two areas power system. The optimal scale factors control technique is optimize from an initial fuzzy logic control rule, and then is learned with an error back propagation learning algorithm of the fuzzy-neural network. In application two areas the load frequency control of the power system, it hopes to have response characteristic better than optimal control technique which is the conventional control technique and to show to minimize a frequency deviation and reaching and settling time of a tie line power flow deviation

• 전기의세계
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• v.31 no.5
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• pp.375-382
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• 1982

The optimum control of voltage and reactive power in large system requires large amounts of complicated calculation. If the large power system is controlled by the centralized control scheme, the necessary computing time, memory requirments and data transmission channels increase exponetially, and computer control of the system becomes difficult. Piecewise method which aims at the reduction of the difficulties of centralized control scheme is to decompose a large power system into several subsystems, each of which is controlled by a local computer and the control efforts of each subsystem are coordinated by a central computer. Unless sufficient coordination is made between subsystems, the control quality may become very poor. This paper describes how piecewise method can be applied in the optimal control of voltage and reactive power in large system, and presents effective calaulating algorithm for the solution of the problem. The numerical example for model system is presented here.

• Transactions of The Korea Fluid Power Systems Society
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• v.4 no.1
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• pp.1-6
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• 2007

The typical hydraulic system of hoist is composed of a hydraulic supply unit, a directional control valve, two pilot operated check valves, two flow control valves. The capacity coefficients of flow control valves should be adjusted for the hoist to operate at moderate speed and minimize the hydraulic energy loss. However, it is difficult to adjust the four capacity coefficients of flow control valves by trial and error for optimal operation. The steady state model of the hoist hydraulic system is derived and the optimal capacity coefficients of flow control valves are obtained using the complex method that is one kind of constrained direct search method.

• Journal of Electrical Engineering and Technology
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• v.9 no.1
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• pp.80-89
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• 2014

A stochastic optimal power flow (S-OPF) model considering uncertainties of load and wind power is developed based on chance constrained programming (CCP). The difficulties in solving the model are the nonlinearity and probabilistic constraints. In this paper, a limit relaxation approach and an iterative learning control (ILC) method are implemented to solve the S-OPF model indirectly. The limit relaxation approach narrows the solution space by introducing regulatory factors, according to the relationship between the constraint equations and the optimization variables. The regulatory factors are designed by ILC method to ensure the optimality of final solution under a predefined confidence level. The optimization algorithm for S-OPF is completed based on the combination of limit relaxation and ILC and tested on the IEEE 14-bus system.

• Nuclear Engineering and Technology
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• v.35 no.5
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• pp.399-411
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• 2003

A model predictive control method is applied to design an automatic controller for thermal power control in a reactor core. The basic concept of the model predictive control is to solve an optimization problem for a finite future at current time and to implement as the current control input only the first optimal control input among the solutions of the finite time steps. At the next time step, the second optimal control input is not implemented and the procedure to solve the optimization problem is then repeated. The objectives of the proposed model predictive controller are to minimize the difference between the output and the desired output and the variation of the control rod position. The nonlinear PWR plant model (a nonlinear point kinetics equation with six delayed neutron groups and the lumped thermal-hydraulic balance equations) is used to verify the proposed controller of reactor power. And a controller design model used for designing the model predictive controller is obtained by applying a parameter estimation algorithm at an initial stage. From results of numerical simulation to check the controllability of the proposed controller at the $5\%/min$ ramp increase or decrease of a desired load and its $10\%$ step increase or decrease which are design requirements, the performances of this controller are proved to be excellent.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.9
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• pp.4610-4615
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• 2013

In this study, optimal operation strategies to save the electric energy and power price in the building central cooling system is researched by experiments. The optimal strategies of demand response control and outdoor temperature reset control algorithms are applied by consideration the electric energy and power price according to the energy consumption characteristics. The suggested optimal control method shows better responses in the power price and energy consumption in comparison with the conventional one and saves energy consumption by 9.5% and electronic price by 15.7%, respectively.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.155-159
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• 1993

In this paper, we consider the problem of a stochastic optimal switching control, which can be applied to the control of a system with uncertain demand such as a control problem of a power plant. The dynamic programming method is applied for the formulation of the optimal control problem. We solve the system of Quasi-Variational Inequalities(QVI) using an algoritlim which involves the finite difference approximation and contraction mapping method. A mathematical example of the optimal switching control is constructed. The actual performance of the algorithm is also tested through the solution of the constructed example.

• Transactions of The Korea Fluid Power Systems Society
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• v.7 no.3
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• pp.20-27
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• 2010

A vehicle suspension system performs two functions, the ride quality and the stability, which conflict with each other. An active suspension system has an external energy source, from which energy is always supplied to the system for continuous control of vehicle motion. Therefore, an active suspension system can have even more improved performance. Some control laws have been proposed for active suspension system, but in this paper, an optimal variable structure control(VSC) is proposed. The VSC method is well suited for a class of nonlinear system and can address the robustness issues to constant modelling errors and disturbances. This paper develops an optimal VSC controller and compares its performance to those of a passive suspension system and an active suspension system with an optimal controller. The transient and frequency responses are analyzed respectively.