• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 1994.11a
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• pp.146-149
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• 1994

A nonlinear dynamic optimization has been performed for reactor power control system of CANDU 6 nuclear power plant considering xenon, fuel and moderator temperature feedback effects. Integral-of-Time-multiplied Absolute-Error (ITAE) criterion has been used as a performance index of the system behavior. Optimum controller gain are found by searching algorithm of Sequential Quadratic Programming (SQP). System models are referenced from most recent literatures. Signal flow network construction and optimization have been done by using commercial computer software package.

• Journal of Electrical Engineering and Technology
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• v.5 no.4
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• pp.530-537
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• 2010

By development of renewable energy and more efficient facilities in an increasingly deregulated electricity market, the operation cost of distributed generation (DG) is becoming more competitive. International environmental regulations of the leaking carbon become effective to reinforce global efforts for a low-carbon paradigm. Through increased DG, operators of DG are able to supply electric power to customers who are connected directly to DG as well as loads that are connected to entire network. In this situation, a community energy system (CES) with DGs is a new participant in the energy market. DG's purchase price from the market is different from the DG's sales price to the market due to transmission service charges and other costs. Therefore, CES who owns DGs has to control the produced electric power per hourly period in order to maximize profit. Considering the international environment regulations, CE will be an important element to decide the marginal cost of generators as well as the classified fuel unit cost and unit's efficiency. This paper introduces the optimal operation of CES's DG connected to the distribution network considering CE. The purpose of optimization is to maximize the profit of CES. A Particle Swarm Optimization (PSO) will be used to solve this complicated problem. The optimal operation of DG represented in this paper would guide CES and system operators in determining the decision making criteria.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.2
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• pp.545-563
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• 2015

Energy harvesting (EH) and network coding (NC) have emerged as two promising technologies for future wireless networks. In this paper, we combine them together in a single system and then present a time switching-based network coding relaying (TSNCR) protocol for the two-way relay system, where an energy constrained relay harvests energy from the transmitted radio frequency (RF) signals from two sources, and then helps the two-way relay information exchange between the two sources with the consumption of the harvested energy. To evaluate the system performance, we derive an explicit expression of the outage probability for the proposed TSNCR protocol. In order to explore the system performance limit, we formulate an optimization problem to minimize the system outage probability. Since the problem is non-convex and cannot be directly solved, we design a genetic algorithm (GA)-based optimization algorithm for it. Numerical results validate our theoretical analysis and show that in such an EH two-way relay system, if NC is applied, the system outage probability can be greatly decreased. Moreover, it is shown that the relay position greatly affects the system performance of TSNCR, where relatively worse outage performance is achieved when the relay is placed in the middle of the two sources. This is the first time to observe such a phenomena in EH two-way relay systems.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.660-664
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• 2003

The optimal thickness distribution of an active damping layer is sought so that it satisfies a certain constraint on the dynamic performance of a system minimizing control efforts. To obtain a topologically optimized configuration, which includes size and shape optimization, thickness of the active damping layer is interpolated using linear functions. With the control energy as the objective function to be minimized, the state error energy is introduced as the dynamic performance criterion for the system and used lot a constraint. The optimal control gains are evaluated from LQR simultaneously as the optimization of the layer position proceeds. From numerical simulation, the topologically optimized distribution of the active damping layer shows the same dynamic performance and cost as the Idly covered counterpart, which is optimized only in terms of control gains, with less amount of the layer.

• Korean Chemical Engineering Research
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• v.50 no.2
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• pp.270-276
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• 2012

In this study, thermally coupled distillation system and conventional two-column process were investigated for extractive distillation. The two processes were simulated and optimized using Aspen plus. Objective function for the optimization was energy consumption and optimization results to reduce energy consumption were used to get guidelines for design and operation for the two extractive distillation processes. Comparison of these two processes showed that thermally coupled distillation system provided better energy efficiency and lower capital cost than conventional distillation system.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.35 no.3
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• pp.43-48
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• 2019

Since the revision of the Rationalization of Energy Use Law, the spread of new and renewable energy in buildings has been promoted. In addition, the production of electric power and thermal energy is an important issue in the change of energy paradigm centered on the use of distributed energy. Among them, geothermal energy is attracting attention as a high-performance energy-saving technology capable of coping with heating / cooling and hot water load by utilizing the constant temperature zone of the earth. However, there is a disadvantage that the initial investment cost is high as a method of calculating the capacity of a geothermal facility by calculating the maximum load. The disadvantages of these disadvantages are that the geothermal energy supply is getting stagnant and the design of the geothermal system needs to be supplemented. In this study, optimization design of geothermal system was carried out using optimization tool. As a result of the optimization, the ground heat exchanger decreased by 30.8%, the capacity of the heat pump decreased by 7.7%, and the capacity of the heat storage tank decreased by about 40%. The simulation was performed by applying the optimized value to the program and confirmed that it corresponds to the load of the building. We also confirmed that all of the constraints used in the optimization design were satisfied. The initial investment cost of the optimized geothermal system is about 18.6% lower than the initial investment cost.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.537-539
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• 2015

considerate operation is a major issue in the equipment-intensive operation. Identifying an optimal equipment combination is important to achieve low-energy operations. An Earthwork operation planning system, which measures the energy consumption of construction operations by taking into account construction equipments' engineering attributes (e.g., weight, capacity, energy consumption rate, etc.) and operation conditions (e.g., road condition, attributes of materials to be moved, geometric information, etc.), is essential to achieve the low-energy consumption. This study develops an automated computerized system which identifies an optimal earthmoving equipment fleet minimizing the energy consumption. The system imports a standard template of earthmoving operation model and compares numerous scenarios using alternative equipment allocation plans. It finds the fleet that minimizes the energy consumption by enumerating all cases using sensitivity analysis. A case study is presented to verify the validity of the system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.10
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• pp.3321-3341
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• 2014

This paper investigates the outage performance and optimization for the four-phase two-way transmission network with an energy harvesting (EH) relay. To enable the simultaneous information processing and energy harvesting at the relay, we firstly propose a power splitting-based two-way relaying protocol (PSTWR). Then, we discuss its outage performance theoretically and derive an explicit expression for the system outage probability. In order to find the optimal system configuration parameters such as the optimal power splitting ratio and the optimal transmit power redistribution factor, we formulate an outage-minimized optimization problem. As the problem is difficult to solve, we design a genetic algorithm (GA) based algorithm for it. Besides, we also investigate the effects of the power splitting ratio, the power redistribution factor at the relay, and the source to relay distance on the system outage performance. Finally, extensive simulation results are provided to demonstrate the accuracy of the analytical results and the effectiveness of the GA-based algorithm. Moreover, it is also shown that, the relay position greatly affects the system performance, where relatively worse outage performance is achieved when the EH relay is placed in the middle of the two sources.

• Journal of the Korean Solar Energy Society
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• v.34 no.4
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• pp.23-29
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• 2014

Recently, in power system studies, Multiple Energy Carriers (MECs) such as Energy Hub has been broadly utilized in power system planners and operators. Particularly, Energy Hub performs one of the most important role as the intermediate in implementing the MECs. However, it still needs to be put under examination in both modeling and operating concerns. For instance, a probabilistic optimization model is treated by a robust global optimization technique such as multi-agent genetic algorithm (MAGA) which can support the online economic dispatch of MECs. MAGA also reduces the inevitable uncertainty caused by the integration of selected input energy carriers. However, MAGA only considers current state of the integration of selected input energy carriers in conjunctive with the condition of smart grid environments for decision making in Energy Hub. Thus, in this paper, we propose an immune algorithm based Multiple Energy Carriers System which can adopt the learning process in order to make a self decision making in Energy Hub. In particular, the proposed immune algorithm considers the previous state, the current state, and the future state of the selected input energy carriers in order to predict the next decision making of Energy Hub based on the probabilistic optimization model. The below figure shows the proposed immune algorithm based Multiple Energy Carriers System. Finally, we will compare the online economic dispatch of MECs of two algorithms such as MAGA and immune algorithm based MECs by using Real Time Digital Simulator (RTDS).

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.9
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• pp.55-61
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• 2009

This paper presents a modified Phasor Discrete Particle Swarm Optimization (PDPSO) algorithm to configure Community Energy Systems(CESs) in the distribution system. The CES obtains electric power from its own Distributed Generations(DGs) and purchases insufficient power from the competitive power market, to supply power for customers contracted with the CES. When there are two or more CESs in a network, the CESs will continue the competitive expansion to reduce the total operation cost. The particles of the proposed PDPSO algorithm have magnitude and phase angle values, and move within a circle area. In the case study, the results by PDPSO algorithm was compared with that by the conventional DPSO algorithm.