• Current Photovoltaic Research
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• v.9 no.2
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• pp.59-73
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• 2021

The purpose of this study is to develop a business model that efficiently converts diesel power generation systems to renewable energy microgrids (MG) in large-scale islands. Most of the previous studies on the conversion of renewable energy MG in islands had limitations dealing with efficiency from the perspective of suppliers. However, the microgrid has the characteristic of getting benefits through the interaction between the consumer and the supplier. In addition, the efficient MG business model from the perspective of new institutional economics is a structure in which consumers and suppliers jointly participate. Therefore, this study assumed that the MG business model in which the supplier's MG and the consumer's community solar participated would benefit all participants, and verified the assumptions using domestic island data. In terms of supplier investment, the cost of power supply (LCOE) of assumed model was calculated to be 14.0% lower than that of the diesel model and 3.7% lower than that of the supplier-only MG model. From the perspective of consumer investment, electricity bills are expected to be reduced by more than 200,000 won per household per year through self-generation of solar power. Social benefits are expected to reduce external environmental costs. The CO₂ emissions of the assumed model were calculated to be 39.5% lower than the diesel model and 1.5% lower than the supplier-only MG model. Therefore, the MG business model with consumer participation proposed in this study is expected to be an efficient alternative to renewable energy MG conversion in domestic islands, and is meaningful as an energy plan that improves the benefits of local residents.

• International Area Studies Review
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• v.20 no.4
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• pp.37-56
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• 2016

The purpose of this research is to present the implication for Korean firms' entry into the power market in Myanmar. This study investigated the characteristics of the Myanmar power market and analyzed SWOT, focusing on energy policy, power supply and demand, energy relations with neighboring countries and climate change issue. Opportunity factors are changes in energy strategies, the launch of an energy integration organization, changes in the power energy portfolio, rapid economic and power demand growth, and a clean development mechanism. The threats are high nonfulfillment of a contract, high power loss rates and low electricity distribution rates, increased energy exports to neighboring countries, and vulnerability to climate change. We suggest the use of CHP (Combined Heat and Power), Clean Development Mechanism (CDM), and Multilateral Development Bank (MDB).

• Journal of the Korean Institute of Gas
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• v.25 no.6
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• pp.29-34
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• 2021

Flammable substances are often present in the raw materials of pharmaceutical products manufactured by pharmaceutical companies. In this case, an excessive amount of flammable substances is added to make an intermediate, and flammable substances that do not participate in the reaction are removed through filtration and drying steps. In addition, the flammable liquid separated in the filtration process is accumulated in the form of splash filling in the filtrate container. In this case, vapor and mist of flammable liquid are generated, which lowers the lower limit of explosion and minimum ignition energy, and increases the risk of fire and explosion due to complex charging. In this study, by analyzing fire accidents that occurred during the recent filtration process of pharmaceutical companies, it is proposed to prevent static electricity accumulation by measures of nitrogen supply facilities, capacity improvement, conductive filter fabric and so on.

• Journal of IKEEE
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• v.26 no.3
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• pp.355-363
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• 2022

Korea is pursuing a plan to switch and expand energy sources with a focus on renewable energy with the goal of becoming carbon neutral by 2050. As the instability of energy supply increases due to the intermittent nature of renewable energy, accurate prediction of the amount of renewable energy generation is becoming more important. Therefore, the government has opened a small-scale power brokerage market and is implementing a system that pays settlements according to the accuracy of renewable energy prediction. In this paper, a prediction model was implemented using a statistical model and an artificial intelligence model for the prediction of solar power generation. In addition, the results of prediction accuracy were compared and analyzed, and the revenue from the settlement amount of the renewable energy generation forecasting system was estimated.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.5
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• pp.376-383
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• 2022

The improved performance of computer parts, such as graphic card, CPU, and main board, has led to the need for power supplies with a high power output. The dynamic load profile rapidly changes the usage of power consumption depending on load operations, such as PC power and air conditioner. Under dynamic load profile conditions, power consumption can be classified into maximum, normal, and standby power. Several problems arise in the case of maximum power. Peak power is generated at the system power source in the maximum-power situation. Frequent generation of peak power can cause high-frequency problems and reduce the life of high-pressure parts (especially high-pressure capacitors). For example, when a plurality of PCs are used, system overload occurs due to peak power generation and causes problems, such as power failure and increase in electricity bills due to exceeded contract power. To solve this problem, a system peak power limit/compensation power circuit is proposed for a power supply under dynamic load profile conditions. The proposed circuit detects the system current to determine the power situation of the load. When the system current is higher than the set level, the circuit recognizes that the system current generates peak power and compensates for the load power through a converter using a super capacitor as the power source. Thus, the peak power of loads with a dynamic load profile is limited and compensated for, and problems, such as high-frequency issues, are solved. In addition, the life of high-pressure parts is increased.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.6
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• pp.251-258
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• 2023

It is necessary to predict peak load accurately in order to supply electric power and operate the power system stably. Especially, it is more important to predict peak load accurately in winter and summer because peak load is higher than other seasons. If peak load is predicted to be higher than actual peak load, the start-up costs of power plants would increase. It causes economic loss to the company. On the other hand, if the peak load is predicted to be lower than the actual peak load, blackout may occur due to a lack of power plants capable of generating electricity. Economic losses and blackouts can be prevented by minimizing the prediction error of the peak load. In this paper, the latest deep learning model such as TCN is used to minimize the prediction error of peak load. Even if the same deep learning model is used, there is a difference in performance depending on the hyper-parameters. So, I propose methods for optimizing hyper-parameters of TCN for predicting the peak load. Data from 2006 to 2021 were input into the model and trained, and prediction error was tested using data in 2022. It was confirmed that the performance of the deep learning model optimized by the methods proposed in this study is superior to other deep learning models.

• Journal of the Korean Institute of Gas
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• v.27 no.2
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• pp.49-56
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• 2023

As AI (Artificial Intelligence)-related technologies are highly developed due to the 4th industrial revolution, cases of applying AI in various fields are increasing. The main reason is that there are practical limits to direct processing and analysis of exponentially increasing data as information and communication technology develops, and the risk of human error can be reduced by applying new technologies. In this study, after collecting the data received from the 'remote potential measurement terminal (T/B, Test Box)' and the output of the 'remote rectifier' at that time, AI was trained. AI learning data was obtained through data augmentation through regression analysis of the initially collected data, and the learning model applied the value-based Q-Learning model among deep reinforcement learning (DRL) algorithms. did The AI that has completed data learning is put into the actual city gas supply area, and based on the received remote T/B data, it is verified that the AI responds appropriately, and through this, AI can be used as a suitable means for electricity management in the future. want to verify.

• Current Photovoltaic Research
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• v.11 no.4
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• pp.134-143
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• 2023

Efforts are being made to respond to global warming. Interest in and demand for the private sector-led RE100 campaign is also increasing. Self-built solar power generation, one of the implementation tools for RE100, is not expanding. However, it can be an economical means of implementation in the long run. In this study, we intend to analyze the impact on the optimal ratio of self-solar power generation using HOMER simulation. OPR defines the optimal solar power generation ratio and looks into what changes there are in the optimal solar power ratio when self-power consumption increases and external power purchase price changes. As a result, the optimal rate of self-solar power generation has a low impact even if self-power consumption increases. As the external power unit price increases, the optimal ratio increases, and at a power unit price of 100 KRW/kWh, OPR is 24%; at 200 KRW/kWh OPR is 31%; and at 300 KRW/kWh OPR is 34%. This shows that the electricity price replaced during the life cycle has a high impact on the economic feasibility of solar power generation. However, when the external power unit price reached a certain level, the increase in OPR decreased. This shows that it is difficult for domestic companies to achieve RE100 based on the economic feasibility of solar energy alone. Therefore, efforts are needed to supply renewable energy in the public sector.

• Nuclear Engineering and Technology
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• v.56 no.3
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• pp.993-1001
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• 2024

The TANDEM project is a European initiative funded under the EURATOM program. The project started on September 2022 and has a duration of 36 months. TANDEM stands for Small Modular ReacTor for a European sAfe aNd Decarbonized Energy Mix. Small Modular Reactors (SMRs) can be hybridized with other energy sources, storage systems and energy conversion applications to provide electricity, heat and hydrogen. Hybrid energy systems have the potential to strongly contribute to the energy decarbonization targeting carbon-neutrality in Europe by 2050. However, the integration of nuclear reactors, particularly SMRs, in hybrid energy systems, is a new R&D topic to be investigated. In this context, the TANDEM project aims to develop assessments and tools to facilitate the safe and efficient integration of SMRs into low-carbon hybrid energy systems. An open-source "TANDEM" model library of hybrid system components will be developed in Modelica language which, by coupling, will extend the capabilities of existing tools implemented in the project. The project proposes to specifically address the safety issues of SMRs related to their integration into hybrid energy systems, involving specific interactions between SMRs and the rest of the hybrid systems; new initiating events may have to be considered in the safety approach. TANDEM will study two hybrid systems covering the main trends of the European energy policy and market evolution at 2035's horizon: a district heating network and power supply in a large urban area, and an energy hub serving energy conversion systems, including hydrogen production; the energy hub is inspired from a harbor-like infrastructure. TANDEM will provide assessments on SMR safety, hybrid system operationality and techno-economics. Societal considerations will also be encased by analyzing European citizen engagement in SMR technology safety.

• Environmental and Resource Economics Review
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• v.24 no.3
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• pp.573-605
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• 2015

This study proposed scenarios of tax reform regarding taxation on bituminous coal for power generation since July 2015 and July 2014, estimated its impact on SMP, settlement price, tax revenue from year 2015 to year 2029. These scenarios are compared with those of the standard scenario. To estimate them, the power system simulation was performed based on the government plan, such as demand supply program and the customized model to fit Korea's power system and operation. Imposing a tax on bituminous coal for power generation while maintaining tax neutrality reducing tax rate on LNG, the short-term SMP is lowered than the one of the standard scenario. Because the cost of nuclear power generation is still smaller than costs of other power generation, and the nuclear power generation rarely determines SMPs, the taxation impact on SMP is almost nonexistent. Thus it is difficult to slow down the electrification of energy consumption due to taxation of power plant bituminous coal in the short term, if SMP and settlement price is closely related. However, in the mid or long term, if the capacity of coal power plant is to be big enough, the taxation of power plant bituminous coal will increase SMP. Therefore, if the tax reform is made to impose on power plant bituminous coal in the short term, and if the tax rate on LNG is to be revised after implementing big enough new power plants using bituminous coal, the energy demand would be reduced by increasing electric charges through energy tax reform. Both imposing a tax on power plant bituminous coal and reducing tax rate on LNG increase settlement price, higher than the one of the standard scenario. In the mid or long term, the utilization of LNG complex power plants would be lower due to an expansion of generating plants, and thus, the tax rate on LNG would not affect on settlement price. Unlike to the impact on SMP, the taxation on nuclear power plants has increased settlement price due to the impact of settlement adjustment factor. The net impact of energy taxation will depend upon the level of offset between settlement price decrease by the expansion of energy supply and settlement price increase by imposing a tax on energy. Among taxable items, the tax on nuclear power plants will increase the most of additional tax revenue. Considering tax revenues in accordance with energy tax scenarios, the higher the tax rate on bituminous coal and nuclear power, the bigger the tax revenues.