• Proceedings of the KIEE Conference
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• 2008.11a
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• pp.22-24
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• 2008

Construction of wind power plant is rapidly increasing since Jeju is known as the most suitable regarding wind power plants in Korea. But implementing wind power generation inevitably introduces new challenges due to its intermittent nature. In the paper, it is introduced the influence analysis and Han-Kyung wind power plants contribution on Jeju power system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1246-1249
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• 1993

In this paper, we propose an algorithm of obstacle avoidance using fuzzy inferences. After the basic idea of the path generation algorithm using piecewise polynomials is described, the obstacle avoidance problem using fuzzy inferences is considered. Main concept of the avoidance algorithm is to modify intermittent point data using fuzzy inferences and to generate the collision free path based on the modified data. Finally, simulation result demonstrate the effectiveness of the proposed algorithm.

• Journal of Advanced Navigation Technology
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• v.22 no.3
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• pp.233-239
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• 2018

Since solar power generation is intermittent depending on weather conditions, it is necessary to predict the accurate generation amount of solar power to improve the efficiency and economical efficiency of solar power generation. This study proposes a short - term deep learning prediction model of solar power generation using meteorological data from Mokpo meteorological agency and generation data of Yeongam solar power plant. The meteorological agency forecasts weather factors such as temperature, precipitation, wind direction, wind speed, humidity, and cloudiness for three days. However, sunshine and solar radiation, the most important meteorological factors for forecasting solar power generation, are not predicted. The proposed model predicts solar radiation and solar radiation using forecast meteorological factors. The power generation was also forecasted by adding the forecasted solar and solar factors to the meteorological factors. The forecasted power generation of the proposed model is that the average RMSE and MAE of DNN are 0.177 and 0.095, and RNN is 0.116 and 0.067. Also, LSTM is the best result of 0.100 and 0.054. It is expected that this study will lead to better prediction results by combining various input.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.3
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• pp.513-521
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• 2017

Robust optimal operation of a microgrid is required since the increase of the penetration level of renewable generators in the microgrid raises uncertainty due to their intermittent power output. In this paper, an application of probabilistic optimization method to economical operation of a microgrid is studied. To simplify the treatment of the uncertainties of renewable generations and load, the new 'band of virtual equivalent load variation' is introduced considering their uncertainties. A simplified robust optimization methodology to generate the scenarios within the band of virtual equivalent load variation and to obtain the optimal solution for the worst scenario is presented based on Monte Carlo method. The microgrid to be studied here is composed of distributed generation system(DGs), battery systems and loads. The distributed generation systems include combined heat and power(CHP) and small generators such as diesel generators and the renewable energy generators such as photovoltaic(PV) systems and wind power systems. The modeling of the objective function for considering interruption cost by the penalty function is presented. Through the case study for a microgrid with uncertainties, the validity of proposed robust optimization methodology is evaluated.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.3
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• pp.486-492
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• 2017

In recent years, renewable energy sources have been mentioned as solution to environmental regulation and energy supply-demand. Energy storage systems are needed to mitigate the intermittent output characteristics of renewable energy sources and to operate micro grid efficiently using renewable energy generation systems. However, despite the necessity of energy storage system, this cannot secure the economical efficiency of the energy storage system by high initial cost. In this paper, a micro grid is constructed to supply electric power to industrial customers by using solar power generation system and energy storage system among renewable energy generation power sources and operated to improve energy independence. In the case study, we use photovoltaic system which is representative renewable energy generation system. Unlike conventional photovoltaic system, this system uses floating photovoltaic system with the advantage of having high output and no land area limitations. It is operated for the purpose of improving energy independence in the micro grid. In order to secure economical efficiency, the energy storage system operates a micro grid with a minimum capacity. Finally, this paper calculates the appropriate subsidy for the energy storage capacity.

• Bulletin of the Korea Photovoltaic Society
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• v.3 no.3
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• pp.56-61
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• 2017

With the appearance of the climate change concerns, energy transition to renewable energy is accelerating over the world. Korea, a latecomer to the renewable energy sector, has also been unable to avoid energy transition. The government is promoting strong goals for expansion of renewable energy. However, switching from stable and controllable conventional generation to intermittent and uncontrollable renewable generation will be a big challenge for the electric power industry. Korea Power Exchange(KPX), which is responsible for the planning and operation of the electric power industry in Korea, is trying to improve measures in various fields such as the implementation of real-time unit commitment and additional real-time markets in order to cope with the volatility and intermittency of renewable energy.

• Wind and Structures
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• v.3 no.1
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• pp.1-10
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• 2000

Recently, an efficient and practical method has been developed for the generation of univariate non-Gaussian wind pressure time histories on low building roofs; this methodology requires intermittent exponential random numbers for the simulation. On the other hand, the conventional spectral representation scheme with random phase is found suitable for the generation of univariate Gaussian wind pressure time histories on low building roofs; this simulation scheme requires uniform random numbers. The dependency of these simulation methodologies on the random number generator is one of the items affecting the accuracy of the simultion result; therefore, an attempt has been made to investigate the issue. This note presents the observed sensitivity of random number sets in repetitive simulations of Gaussian and non-Gaussian wind pressures.

• Journal of Advanced Navigation Technology
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• v.21 no.6
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• pp.643-650
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• 2017

Photovoltaic generation which has unlimited energy sources are very intermittent because they depend on the weather. Therefore, it is necessary to get accurate generation prediction with reducing the uncertainty of photovoltaic generation and improvement of the economics. The Meteorological Agency predicts weather factors for three days, but doesn't predict the sunshine and solar radiation that are most correlated with the prediction of photovoltaic generation. In this study, we predict sunshine and solar radiation using weather, precipitation, wind direction, wind speed, humidity, and cloudiness which is forecasted for three days at Meteorological Agency. The photovoltaic generation forecasting model is proposed by using predicted solar radiation and sunshine. As a result, the proposed model showed better results in the error rate indexes such as MAE, RMSE, and MAPE than the model that predicts photovoltaic generation without radiation and sunshine. In addition, DNN showed a lower error rate index than using SVM, which is a type of machine learning.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1719-1728
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• 2017

Recent concerns about environmental conditions have triggered the growing interest in using green energy resources. These sources of energy, however, bring new challenges mainly due to their uncertainty and intermittency. In order to alleviate the concerns on the penetration of intermittent energy resources, this paper investigates impacts of realizing demand-side potentials. Among different demand-side management programs, this paper considers demand response wherein consumers change their consumption pattern in response to changing prices. The research studies demand response potentials from different load sectors on generation system well-being. Consumers' sensitivity to time-varying prices is captured via self and cross elasticity coefficients. In the calculation of well-being indices, sequential Monte Carlo simulation approach is accompanied with fuzzy logic. Finally, IEEE-RTS is used as the test bed to conduct several simulations and the associated results are thoroughly discussed.

• International Journal of Computer Science & Network Security
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• v.24 no.6
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• pp.33-40
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• 2024

Introducing renewable energy sources, such as wind and photovoltaic arrays, in microgrids that supply remote regions with electricity represents a significant leap in electricity generation. Combining photovoltaic panels and diesel engines is one of the most common ways to supply electricity to rural communities. Such hybrid systems can reduce the cost of electricity generation in these remote power systems because they use free energy to balance the power generated by diesel engines. However, the combination of renewable energy sources and diesel engines tends to complicate the sizing and control of the entire system due to the intermittent nature of renewable energy sources. This study sought to investigate this issue in depth. It proposes a robust hybrid controller that can be used to facilitate optimum power sharing between a PV power source and diesel generators based on the dynamics of the available PV energy at any given time. The study also describes a hybrid PV-diesel power plant's essential functional parts that produce electricity for a microgrid using a renewable energy source. Power control needs to be adjusted to reduce the cost of power generation.