• Environmental Engineering Research
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• v.21 no.4
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• pp.409-419
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• 2016

As a major energy consumption province, the issue about the carbon emissions in Hebei Province, China has been concerned by the government. The carbon emissions can be effectively reduced due to a more rational energy consumption structure. Thus, in this paper the constraint of low carbon emissions is considered as a foundation and four energies--coal, petroleum, natural gas and electricity including wind power, nuclear power and hydro-power etc are selected as the main analysis objects of the adjustment of energy structure. This paper takes energy cost minimum and carbon trading cost minimum as the objective functions based on the economic growth, energy saving and emission reduction targets and constructs an optimization model of energy consumption structure. And empirical research about energy consumption structure optimization in 2015 and 2020 is carried out based on the energy consumption data in Hebei Province, China during the period 1995-2013, which indicates that the energy consumption in Hebei dominated by coal cannot be replaced in the next seven years, from 2014 to 2020, when the coal consumption proportion is still up to 85.93%. Finally, the corresponding policy suggestions are put forward, according to the results of the energy structure optimization in Hebei Province.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.4
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• pp.247-253
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• 2011

A sustainability of electricity supply has emerged as a critical issue for low carbon green growth in South Korea. Wind power is the fastest growing source of renewable energy. However, due to its own intermittency and volatility, the power supply generated from wind energy has variability in nature. Hence, accurate forecasting of wind speed and power plays a key role in the effective harvesting of wind energy and the integration of wind power into the current electric power grid. This paper presents a short-term wind speed prediction method based on support vector regression. Moreover, particle swarm optimization is adopted to find an optimum setting of hyper-parameters in support vector regression. An illustration is given by real-world data and the effect of model regularization by particle swarm optimization is discussed as well.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1144_1145
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• 2009

Tidal power station is using the difference of the ebb and flow and the single action tidal power is dependent on tide amplitude and basin volume. Therefore the inflow of basin in rainy season has also effect on the daily power. Also if operating units are changed then starting head too changed. Therefore the number of units are very important for the optimization model. According to our study the primary point when we make a determination of optimization is starting head and governorl control mode. On this study optimization model for tidal power station is considered all of this conditions.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.54 no.2
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• pp.61-66
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• 2005

This paper presents an unified method which solves real and reactive power dispatch problems for the economic operation of power systems using evolutionary computation such as genetic algorithms(GA), evolutionary programming(EP), and evolution strategy(ES). Many conventional methods to this problem have been proposed in the past, but most of these approaches have the common defect of being caught to a local minimum solution. The proposed methods, applied to the IEEE 30-bus system, were run for 10 other exogenous parameters and composed of P-optimization module and Q-optimization module. Each simulation result, by which evolutionary computations are compared and analyzed, shows the possibility of applications of evolutionary computation to large scale power systems.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.12
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• pp.1782-1791
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• 2017

In this paper, an optimal design of hybrid magnetic levitation(Maglev) system using intelligent optimization algorithms is proposed. The proposed maglev system adopts hybrid suspension system with permanent-magnet(PM) and electro magnet(EM) to reduce the suspension power loss and the teaching-learning based optimization(TLBO) that can overcome the drawbacks of conventional intelligent optimization algorithm is used. To obtain the mathematical model of hybrid suspension system, the magnetic equivalent circuit including leakage fluxes are used. Also, design restrictions such as cross section areas of PM and EM, the maximum length of PM, magnetic force are considered to choose the optimal parameters by intelligent optimization algorithm. To meet desired suspension power and lower power loss, the multi object function is proposed. To verify the proposed object function and intelligent optimization algorithms, we analyze the performance using the mean value and standard error of 10 simulation results. The simulation results show that the proposed method is more effective than conventional optimization methods.

• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.2125-2138
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• 2023

The printed circuit heat exchanger (PCHE) with airfoil fins has the benefits of high compactness, high efficiency and superior heat transfer performance. A novel multi-objective optimization approach is presented to design the airfoil fin PCHE in this paper. Three optimization design variables (the vertical number, the horizontal number and the staggered number) are obtained by means of dimensionless airfoil fin arrangement parameters. And the optimization objective is to maximize the Nusselt number (Nu) and minimize the Fanning friction factor (f). Firstly, in order to investigate the impact of design variables on the thermal-hydraulic performance, a parametric study via the design of experiments is proposed. Subsequently, the relationships between three optimization design variables and two objective functions (Nu and f) are characterized by an improved particle swarm optimization-backpropagation artificial neural network. Finally, a multi-objective optimization is used to construct the Pareto optimal front, in which the non-dominated sorting genetic algorithm II is used. The comprehensive performance is found to be the best when the airfoil fins are completely staggered arrangement. And the best compromise solution based on the TOPSIS method is identified as the optimal solution, which can achieve the requirement of high heat transfer performance and low flow resistance.

• Journal of Power Electronics
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• v.14 no.1
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• pp.165-174
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• 2014

The cascaded H-Bridge Dynamic Voltage Restorer (DVR) is used for protecting high voltage and large capacity loads from voltage sags. The LC filter in the DVR is needed to eliminate switching ripples, which also provides an accurate tracking feature in a certain frequency range. Therefore, the parameter optimization of the LC filter is especially important. In this paper, the value range functions for the inductance and capacitance in LC filters are discussed. Then, parameter variations under different conditions of voltage sags and power factors are analyzed. In addition, an optimized design method is also proposed with the consideration of multiple impact factors. A detailed optimization procedure is presented, and its validity is demonstrated by simulation and experimental results. Both results show that the proposed method can improve the LC filter design for a cascaded H-Bridge DVR and enhance the performance of the whole system.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.4
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• pp.143-152
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• 2016

In this paper, a MMIC double balanced mixer that can be applied to the tele-communication band is designed and LO power optimization for the mixer is discussed. The chip of the MMIC double-balanced mixer is fabricated on GaAs substrate with the size of $4{\times}4mm^2$. Optimization study of LO power for the MMIC double-balanced mixer proposed in this paper is conducted for the Input IP3 (IIP3) regarding on the linearity of the input signal. When LO power level of+16 dBm is applied to the mixer, IIP3 is obtained to be approximately 23.2 dBm, which is the most outstanding characteristic.

• ETRI Journal
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• v.43 no.1
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• pp.17-30
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• 2021

At present, multiple input multiple output radars offer accurate target detection and better target parameter estimation with higher resolution in high-speed wireless communication systems. This study focuses primarily on power allocation to improve the performance of radars owing to the sparsity of targets in the spatial velocity domain. First, the radars are clustered using the kernel fuzzy C-means algorithm. Next, cooperative and noncooperative clusters are extracted based on the distance measured using the kernel fuzzy C-means algorithm. The power is allocated to cooperative clusters using the Pareto optimality particle swarm optimization algorithm. In addition, the Nash equilibrium particle swarm optimization algorithm is used for allocating power in the noncooperative clusters. The process of allocating power to cooperative and noncooperative clusters reduces the overall transmission power of the radars. In the experimental section, the proposed method obtained the power consumption of 0.014 to 0.0119 at K = 2, M = 3 and K = 2, M = 3, which is better compared to the existing methodologies-generalized Nash game and cooperative and noncooperative game theory.

• 한국연소학회:학술대회논문집
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• 2012.11a
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• pp.225-228
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• 2012

Thermodynamic and economic analysis on various type of gas turbine combined cycle power plants was presented to build up the criteria for optimization of power plants. The efficiency considered about energy level difference between electricity and heat was introduced. The efficiency on power and heat generation of power plants whose have different purpose was estimated and power generation costs on various type of combined heat and power plants : fired/unfired, condensing/non-condensing mode, single/double pressure HRSG.