• Nuclear Medicine and Molecular Imaging
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• v.41 no.1
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• pp.1-8
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• 2007

This review discusses the production of alpha-particle-emitting radionuclides in radioimmunotherapy. Radioimmunotherapy labeled with alpha-particle is expected to be very useful for the treatment of monocellular cancer (e.g. leukemia) and micrometastasis at an early stage, residual tumor remained in tissues after chemotherapy and tumor resection, due to the high linear energy transfer (LET) and the short path length in biological tissue of alpha particle. Despite of the expected effectiveness of alpha-particle in radioimmunotherapy, its clinical research has not been activated by the several reasons, shortage of a suitable a-particle development and a reliable radionuclide production and supply system, appropriate antibody and chelator development. Among them, the establishment of radionuclide development and supply system is a key factor to make an alpha-immunotherapy more popular in clinical trial. Alpha-emitter can be produced by several methods, natural radionuclides, reactor irradiation, cyclotron irradiation, generator system and elution. Due to the sharply increasing demand of $^{213}Bi$, which is a most promising radionuclide in radioimmunotherapy and now has been produced with reactor, the cyclotron production system should be developed urgently to meet the demand.

• Proceedings of the KIPE Conference
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• 2012.07a
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• pp.498-500
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• 2012

According to the climatic characteristics of the wind power output is difficult to predict and a severe strain due to a change in output has been very influential in the grid. Jeju Hangwon wind farm, many of the wind generator is installed in a wide area because it is not have this device that artificially Smoothing is needed. In addition, By the requirements of the power company active power supply / control and improve power system reliability and energy storage during the peak demand for electricity using the energy stored in the power supply is needed. In this paper, Unit 12 in Jeju Hangwon demonstrated 0.5MW PCS and energy storage system associated with the wind through the stabilization of output and the leveling of output and test results will be introduced.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2398-2421
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• 2020

In third world countries like Pakistan, the production of electricity has been quickly reduced in past years due to rely on the fossil fuel. According to a survey conducted in 2017, the overall electrical energy capacity was 22,797MW, since the electrical grids have gone too old, therefore the efficiency of grids, goes down to nearly 17000MW. Significant addition of fossil fuel, hydro and nuclear is 64.2%, 29% and 5.8% respectively in the total electricity production in Pakistan. In 2018, the demand crossed 20,223MW, compared to peak generation of 15,400 to 15,700MW as by the Ministry of Water and Power. Country faces a deficit of almost 4000MW to 5000MW for the duration of 2019 hot summer term. Focus on one aspect considering Demand Side Management (DSM) cannot oversea the reduction of gap between power demand and customer supply, which eventually leads to the issue of load shedding. Hence, a scheduling scheme is proposed in this paper called RPSMDSM that is based on selection of those appliances that need to be only Turned-On, on priority during peak hours consuming minimum energy. The Home Energy Management (HEM) system is integrated between consumer and utility and bidirectional flow is presented in the scheme. During peak hours of electricity, the RPSMDSM is capable to persuade less power consumption and accomplish productivity in load management. Simulations show that RPSMDSM scheme helps in scheduling the electricity loads from peak price to off-peak price hours. As a result, minimization in electricity cost as well as (Peak-to-Average Ratio) PAR are accomplished with sensible waiting time.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.3
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• pp.1-7
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• 2015

Korea's electricity supply and demand policy has focusing on electricity demand side management instead of the expanding supply and a lot of effort for LED(Light Emitting Diode) at the time. This paper calculated the optimal subsidy for LED spread. For this purpose, it analyzed the impact on spread of the lighting appliances each subsidy level from BDM(Bass Diffusion Model) and predicted the number of lighting appliances according to subsidy level in the future. The case study is calculated susidy for satisfaction of LED target using the suggested model in the future and verified availability.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.1
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• pp.222-228
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• 2017

The aims of the demand response market are stabilization of the power supply and improving of the reliability of the power system. The various applications of the energy storage system (ESS) in the railway systems are studied and implemented to raise the energy efficiency. It is one of the most important how to determine the obligation reduction capacity (ORC) in participation to the demand response market because it has an influence on the profit extremely. In this paper, when participating to the demand response market with demands in the urban railway, we calculated the available ORC and economically evaluated ESS based on the real load data.

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.521-522
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• 2006

This paper calculates co-generation generating capacity for the electric supply and demand. CHP is applied to SCM(Screening Curve Method) to calculate CHP generating capacity On the other hand, small co-generation is applied to potential area conversing small co-generation generating capacity considering economic analysis and useful life. these methods executed project scheduled to construction plan. Accordingly, EES(Expected Energy Served), Fuel type consumption and CO2 effects is analyzed by Booth-Baleriaux and data

• Journal of IKEEE
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• v.23 no.1
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• pp.134-142
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• 2019

As the development of internet of energy (IoE) technologies and spread of various electronic devices have diversified patterns of energy consumption, the reliability of demand prediction has decreased, causing problems in optimization of power generation and stabilization of power supply. In this study, we propose a deep learning method, 1-Dimention-Convolution and Bidirectional Long Short-Term Memory (1D-ConvBLSTM), that combines a convolution neural network (CNN) and a Bidirectional Long Short-Term Memory(BLSTM) for highly reliable demand forecasting by effectively extracting the energy consumption pattern. In experimental results, the demand is predicted with the proposed deep learning method for various number of learning iterations and feature maps, and it is verified that the test data is predicted with a small number of iterations.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.736-738
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• 2005

For calculating optimal generation composition of The Basic Plan of Long Term Electricity Supply & Demand, the Screening Curve Method that using generation cost for planning is needed. This paper will induce optimal power system ratio included Combined Head and Power and suggest the method for optimal generation composition of The Basic Plan of Long Term Electricity Supply & Demand that considered policy side.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.740-742
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• 1999

The demand for the high quality of utility electrical power has been increasing rapidly in recent years because of today's electrical energy dependent industries and most people's everyday lives based on computer systems. However, electrical power supply conditions to meet this high quality demand becomes more difficult and more due to a large portion of nuclear power plants output in total electrical power supply which normally do not respond to frequency variations, and high peak of air conditioner demands during the summer season. So the rest of power plants should be operated to show the best governor regulation performance to maintain the electrical power frequency quality.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.106-111
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• 1992

In order to achieve stable and efficient use of energy at iron and steel works, a model for the prediction of supply and demand of electric power system is developed on the basis of the information on operation and particular patterns of electric power consumption. The optimal amount of electric power to be purchased and the optimal fuel allocation for the in-house electric power plants are also obtained by a mixed-integer linear programming(MILP) and a nonlinear programming (NLP) solutions, respectively. The validity and the effectiveness of the proposed model are investigated by several illustrative examples. The simulation results show the satisfactory energy saving by the optimal solution obtained through this research.