• Journal of Institute of Control, Robotics and Systems
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• v.12 no.12
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• pp.1163-1168
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• 2006

Manufacturing technology for the production of high value-added fine chemical products is emphasized and getting more attention as the diversified interests of customers and the demand of high quality products are getting bigger and bigger everyday. Thus, the development of advanced batch processes, which is the preferred and most appropriate way of producing these types of products, and the related technologies are becoming more important. Therefore, high-precision batch distillation is one of the important elements in the successful manufacturing of fine chemicals, and the importance of the process operation strategy with quality assurance cannot be overemphasized. Accordingly, proposing a process structure explanation and operation strategy of such processes including batch processes and batch distillation would be of great value. We investigate optimal operation strategy and production planning of multi-purpose plants consisting of batch processes and batch distillation for the manufacturing of fine chemical products. For the short-term scheduling of a sequential multi-purpose batch plant consisting of batch distillation under MPC and UIS policy, we proposed a MILP model based on a priori time slot allocation. Also, we consider that the waste product of being produced on batch distillation is recycled to the batch distillation unit for the saving of raw materials. The developed methodology will be especially useful for the design and optimal operations of multi-purpose and multiproduct plants that is suitable for fine chemical production.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.2
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• pp.149-154
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• 2013

Short term load forecasting for electric power demand is essential for stable power system operation and efficient power market operation. High accuracy of the short term load forecasting can keep the power system more stable and save the power market operation cost. We propose an optimal coefficient selection method for exponential smoothing model in short term load forecasting on weekdays. In order to find the optimal coefficient of exponential smoothing model, load forecasting errors are minimized for actual electric load demand data of last three years. The proposed method are verified by case studies for last three years from 2009 to 2011. The results of case studies show that the average percentage errors of the proposed load forecasting method are improved comparing with errors of the previous methods.

• Water for future
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• v.29 no.4
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• pp.131-138
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• 1996

The objective of this study is to develop an optimal operation model for the sewage treatment plants using nonlinear programming (NLP) technique and the QUAL2E model. The model finds the minimum-cost operation of sewage treatment plants while satisfying all design constraints and water quality (BOD) standard. The model is applied to four sewage treatment plants in Han River for the city of Seoul. It has been found that optimal operation schedule for the sewage treatment plants can be computed and it is more economic to operate the plants according to the schedule which satisfies the water quality constraints in the river. In addition, the water quality in the river can be predicted using the model under the treatment policy.

• Proceedings of the SAREK Conference
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• 2006.06a
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• pp.669-674
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• 2006

The optimal control of heat pump performance for heating mode operation was investigated. Fuzzy logic was applied to control the heating performance of heat pump system and superheat at compressor discharge was taken as a control variable. Regression model was adapted to determine the optimal points where COP is maximized. Optimization of fuzzy rule table was investigated to improve operation performance of heat pump system. Experiments were carried out using original fuzzy table and the modified fuzzy rule table for heating mode operation of heat pump system. The results show that control performance of heat pump system with the modified fuzzy rule table was better than that with the original rule table.

• Proceedings of the KSME Conference
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• 2007.05b
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• pp.3359-3364
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• 2007

The smart energy system is the integrated power system in which the power components including central station generation, distributed generation, renewable power generation, energy storage, and communications and controls are complexly connected with each other. In smart energy system, it is very important how to configure the diverse power generations and how to determine the operation mode of the chosen components with economic feasibility. In this study, we introduce the optimal planning method based on both economic feasibility and load profiles and its applications for the smart energy system in apartment. This method was considered very useful to determine the configuration and to decide the optimal operation mode of the smart energy system.

• Journal of IKEEE
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• v.13 no.2
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• pp.175-180
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• 2009

This paper compare the operation characteristic and optimal design of Photovoltaic system by computer simulation. The operation characteristic of Photovoltaic system are evaluated and analyzed considering system parameters of specifications, installations, inclination, azimuth and surrounding conditions etc. From the basis of these results, this study will intend to develop an evaluation, analysis tool and construct database for optimal design of PV system.

• Journal of Power Electronics
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• v.17 no.2
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• pp.323-333
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• 2017

This paper proposes a model-based optimal control algorithm for the clamp switch of a zero-voltage switching (ZVS) bidirectional DC-DC converter. The bidirectional DC-DC converter (BDC) can accomplish the ZVS operation using the clamp switch. The minimum current for the ZVS operation is maintained, and the inductor current is separated from the input and output voltages by the clamp switch in this topology. The clamp switch can decrease the inductor current ripple, switching loss, and conduction loss of the system. Therefore, the optimal control of the clamp switch is significant to improve the efficiency of the system. This paper proposes a model-based optimal control algorithm using phase shift in a micro-controller unit. The proposed control algorithm is demonstrated by the results of PSIM simulations and an experiment conducted in a 1-kW ZVS BDC system.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.611-613
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• 2004

This paper is concerned with the simulation and determination of the input voltage and frequency for the optimal efficiency operation of induction motors. In general, induction motors have a specific character that operation efficiency is dropped sharply at the light roads condition. Consequently, if the induction motor is controlled by high efficiency using the VVVF(variable voltage variable frequency) control methods at optimal values, the entire system can obtain the substantial energy savings from the efficiency improvement in induction motors. In this paper, optimal slip is derived from the modeling of an induction motor and the optimal hybrid-control method is suggested by the simulation of the proposed algorithm for a 3-phase induction motor.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.482_483
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• 2009

This paper presents a method of finding the optimal operating point minimizing a given objective function with 3 phase power flow equations and operational constraints, called 3 phase optimal power flow. 3 phase optimal power flow can provide operation and control strategies for the distribution systems with distributed generation assets, which might be frequently in unbalanced conditions assuming that high penetration rate of renewable energy sources in the systems. As the solution technique, this paper adopts a standard particle swarm optimization (PSO).

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.2
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• pp.197-205
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• 1994

Security of a power system refers to its robustness relative to a set of imminent disturbances (contingencies) during operation. The socially optimal solution for the actuall level of generation/consumption has been well-known spot pricing at shot-run marginal cost. The main disadvantage of this approach arises because serious contingencies occur quite infrequently. Thus by establishing contractual obligations for contingency offering before an actual operation time through decision feedback we can obtain socially optimal level of system security. Under probabilistic precontract pricing the operating point is established at equal incremental cost of the expected short-run and collapse cost of each participant. Rates for power generation/consumption and for an offer to use during a contingency, as well as information on the probability distribution of contingency need for each participant, are derived so that individual optimization will lead to the socially optimal solution in which system security is optimized and the aggregate benefit is maxmized.