• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.12 no.3
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• pp.9-16
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• 2016

This study had the purpose on feasibility judgment through performance forecast of wind power generation system using the cross flow vertical type wind power turbine for the situation of domestic small size wind power technology development. Wind power generation system uses the principle of venturi tube that gathers the wind through the first guide vane, and second guide vein changes the angle of the wind simultaneously by playing the role of venturi tube. After this, wind got out from the second guide vane spins the wind power turbine and has the meaning of judging on the aspect of numerical interpretation the feasibility for the small size wind power generation through wind power generation system that comes out from the back.

• Plant Journal
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• v.16 no.4
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• pp.26-32
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• 2020

The performance monitoring system in the power plant should have the capability to estimate power generation efficiency accurately. Several power generation efficiency models have been proposed for the combined heat and power (CHP) plant which produces both electricity and process steam(or heating energy, hereinafter expressed by process steam only). However, most of the models are not sufficiently accurate due to the wrong evaluation of the process steam value. The study suggests Electricity Conversion Efficiency (ECE) model with determination of the heat rate of process steam using operational data. The suggested method is applied to the design data and the resulted trajectory curve of power generation efficiency meets the data closely with R2 99.91%. This result confirms that ECE model with determination of the model coefficient using the operational data estimate the efficiency so accurately that can be used for performance monitoring of CHP plant.

• 한국신재생에너지학회:학술대회논문집
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• 2007.06a
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• pp.688-692
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• 2007

Solar thermal power generation allows additional benefits of cheap thermal storage and easy hybridization with other fossil fuel-driven power generation. KIER has been performing the project for solar thermal chemical reaction hybrid power generation. The project is to build and operate the first solar thermal chemical reaction hybrid power generation system in Korea. For concentrating solar thermal energy $m^2$ dish type concentrator was adapted and a heliostat is installed for reflecting horizontal insolation to the dish concentrator. At the moment building the dish concentrator including mirror and heliostat with sun tracking system was completed and it's performance are being closely evaluated. This paper will introduce some detailed designs and construction procedures which we have experienced so far.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3735-3740
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• 2012

In this paper, the performance of power generation for the energy harvesting block with a combination of piezoelectric technology and electromagnetic technology among various energy harvesting technologies was investigated. The goal of this study is to evaluate on the applicability of our developed energy harvesting block into the field of urban & housing. First, we carried out a finite element vibration analysis and evaluated the performance of power generation for the multi-layer energy harvester at laboratory scale. Second, we described the features of our developed prototype module that includes amplification technologies to improve power density per module and evaluated the performance of power generation for the energy harvesting block in a variety of ways. Finally, we suggested the direction for the improvement of the energy harvesting block module.

• Land and Housing Review
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• v.7 no.3
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• pp.131-136
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• 2016

The aim of this study was to improve the performance of hybrid energy harvesting block merge the vibrations and the pressure developed in the previous study. The power generation performance of the energy block improved in this manner was measured and compared with the energy performance of the products previously developed. In previous models, the center has placed a piezoelectric, the two sides had arranged a vibration applying electromagnetic inducing type. Improved model was disposed three in a row of three unit modules for one block. We change the design in the following way. That is, a unit module has been placed the upper piezoelectric body, the lower portion were arranged three electron donation. In laboratory conditions, the power generation performance evaluation results of the improved energy block is as follows. Once when the vibration, power generation was determined to 1.066W. When compared with previous studies, and power generation performance is improved up to 235%. When the vibration in a row 5, power generation was determined to 1.830W. When compared with previous studies, the performance is improved to 177%. The purpose of developing a hybrid energy block is intended to produce electricity by the pressure and vibration when a vehicle passes through the energy block installed in the car park the mouth portion. Electricity produced will try to take advantage of for the purpose of operating a guiding beacon and LED signage in the parking lot entrance. Therefore, it is determined that there is a need in the experiment to compare the performance of the power generation in the field.

• Journal of the Korean Society of Combustion
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• v.18 no.3
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• pp.1-8
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• 2013

Thermodynamic and economic analyses of various types of gas turbine combined cycle power plants have been performed to establish criteria for optimization of power plants. The concept of efficiency, in terms of the difference in energy levels of electricity and heat, was introduced. The efficiency of power and heat generation by power plants with other purposes was estimated, and power generation costs were figured out for various types of combined heat and power plants(i.e., fired and unfired, condensing and non-condensing modes, single or double pressure HRSG).

• Transactions of the Korean hydrogen and new energy society
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• v.31 no.5
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• pp.436-443
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• 2020

The performance prediction model of a solid oxide fuel cell stack has been developed using deep neural network technique, one of the machine learning methods. The machine learning has been received much interest in various fields, including energy system mo- deling. Using machine learning technique can save time and cost requried in developing an energy system model being compared to the conventional method, that is a combination of a mathematical modeling and an experimental validation. Results reveal that the mean average percent error, root mean square error, and coefficient of determination (R2) range 1.7515, 0.1342, 0.8597, repectively, in maximum. To improve the predictability of the model, the pre-processing is effective and interpolative machine learning and application is more accurate than the extrapolative cases.

• Atmosphere
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• v.34 no.2
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• pp.177-185
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• 2024

As increasing global interest in renewable energy due to the ongoing climate crisis, there is a growing need for efficient technologies to manage such resources. This study focuses on the predictive skill of daily solar power generation using weather observation and forecast data. Meteorological data from the Korea Meteorological Administration and solar power generation data from the Korea Power Exchange were utilized for the period from January 2017 to May 2023, considering both inland (Daejeon) and coastal (Busan) regions. Temperature, wind speed, relative humidity, and precipitation were selected as relevant meteorological variables for solar power prediction. All data was preprocessed by removing their systematic components to use only their residuals and the residual of solar data were further processed with weighted adjustments for homoscedasticity. Four models, MLR (Multiple Linear Regression), RF (Random Forest), DNN (Deep Neural Network), and RNN (Recurrent Neural Network), were employed for solar power prediction and their performances were evaluated based on predicted values utilizing observed meteorological data (used as a reference), 1-day-ahead forecast data (referred to as fore1), and 2-day-ahead forecast data (fore2). DNN-based prediction model exhibits superior performance in both regions, with RNN performing the least effectively. However, MLR and RF demonstrate competitive performance comparable to DNN. The disparities in the performance of the four different models are less pronounced than anticipated, underscoring the pivotal role of fitting models using residuals. This emphasizes that the utilized preprocessing approach, specifically leveraging residuals, is poised to play a crucial role in the future of solar power generation forecasting.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.23-30
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• 2022

Deep learning analyzes data to discover a series of rules and anticipates the future, helping us in various ways in our lives. For example, prediction of stock prices and agricultural prices. In this research, the results of solar photovoltaic power generation accompanied by weather are analyzed through deep learning in situations where the importance of solar energy use increases, and the amount of power generation is predicted. In this research, we propose a model using LSTM(Long Short Term Memory network) that stand out in time series data prediction. And we compare LSTM's performance with CNN(Convolutional Neural Network), which is used to analyze various dimensions of data, including images, and CNN-LSTM, which combines the two models. The performance of the three models was compared by calculating the MSE, RMSE, R-Squared with the actual value of the solar photovoltaic power generation performance and the predicted value. As a result, it was found that the performance of the LSTM model was the best. Therefor, this research proposes predicting solar photovoltaic power generation using LSTM.

• Journal of Power Electronics
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• v.13 no.5
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• pp.798-805
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• 2013

This paper presents the control and implementation of the dual-stator-winding induction generator for variable frequency AC (VFAC) generating system. This generator has two sets of stator windings embedded into the stator slots. The power winding produces the VFAC power to feed the loads, and the control winding is connected to the static excitation controller to control the generator for output voltage regulation with speed and load variations. On the basis of the idea of power balance, an instantaneous slip frequency control (ISFC) strategy using the information of both the output voltage and the output power is used in this system. A series of experiments is carried out on a 15 kW prototype for verification. Results show that the system has good static and dynamic performance in a wide speed range, which demonstrates that the ISFC strategy is suitable for this system.