• Transactions of the Korean hydrogen and new energy society
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• v.34 no.2
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• pp.91-99
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• 2023

Participation in power trading using surplus power is considered a business model active in the domestic energy trade market, but it is limited only if the legal requirements according to the type, capacity, and use of the facilities to be applied for are satisfied. The hydrogen residential demonstration model presented in this paper includes solar power, energy storage system (ESS), fuel cell, and water electrolysis facilities in electrical facilities for private use with low-voltage power receiving system. The concept of operations strategy for this model focuses on securing the energy self-sufficiency ratio of the entire system, securing economic feasibility through the optimal operation module installed in the energy management system (EMS), and securing the stability of the internal power balancing issue during the stand-alone mode. An electric facility configuration method of a hydrogen residential complex demonstrated to achieve this operational goal has a structure in which individual energy sources are electrically connected to the main bus, and ESS is also directly connected to the main bus instead of a renewable connection type to perform charging/discharging operation for energy balancing management in the complex. If surplus power exists after scheduling, participation in power trading through reverse transmission parallel operation can be considered to solve the energy balancing problem and ensure profitability. Consequentially, this paper reviews the legal regulations on participation in electric power trading using surplus power from hydrogen residential models that can produce and consume power, gas, and thermal energy including hybrid distributed power sources, and suggests action plans.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.4
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• pp.735-742
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• 2021

Recently, renewable energy-related power generation facilities have been surging due to the government's "Renewable Energy 3020", "Green New Deal", "2050 Carbon Neutrality" and "K-RE100" policies. Most renewable energy facilities are small and distributed, making it difficult to manage efficiently, and small distributed resources less than 1MW are having a hard time with participating in the market due to the limited sales and avoidance of trading. In particular, the intermittency of renewable energy has a significant impact on the stability of the power grid. The government is seeking to address volatility and intermittency issues through 'small distributed resource brokerage trading, and to expand the systematic resourceization and acceptability of heterogeneous large and small distributed resources. In this work, we intend to apply an AI-based power generation prediction model to a distributed resource brokerage trading system so that it can be utilized as a foundation platform for pioneering new energy business markets.

• Environmental and Resource Economics Review
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• v.32 no.3
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• pp.149-166
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• 2023

The emissions trading system, introduced to reduce greenhouse gas emissions, experienced a sharp increase in emission allowance prices during the second plan period (2018-2020), which led to an increase in the demand for smooth supply and demand of emission allowances, while suppliers anticipating a shortage of emission allowances in the future did not participate in trading. Therefore, the authority temporarily revised the guidelines to ensure that the amount of allowances carried forward is proportional to the trading volume as a market stabilization measure. Through an optimization process using a dynamic nonlinear mathematical model, this paper analyzes the impact of the government's intervention on the carryover policy on GHG emission reductions and emission allowance market prices. According to the simulation analysis results, banking regulations could cause a decline in prices during the regulation period, even though the initial policy was predicted to be adopted.

• The Journal of Society for e-Business Studies
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• v.5 no.2
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• pp.81-99
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• 2000

Nowadays, many commercial ERP products, such as Oracle, SAP, and Baan, etc, are designed based on large-scaled companies. It is difficult for small and medium-size companies with weakness in budgets and resources(e.g., human, organization, technique, and so on) to use them as it was. So, new ERP system need to be provided for small and medium-size companies. In this paper, we model and provide a conceptual ERP model for small and medium-size companies by using "4＋1 View" architecture model of Unified Modeling Language(UML). The conceptual ERP model consists of five subsystems： Manufacturing, Sales, HumanResource and Payroll, Accounting, and Trading. Especially, we describe the conceptual ERP model focusing on "Manufacturing" subsystem by using several diagrams of UML. By using the conceptual ERP model, the ERP system′s developers of small and medium-size companies can obtain many benefits： improving the efficiency of software developing process and helping user requirements gathering and description of ERP system′s nonfunctional aspect as well as functional aspect.

• Environmental and Resource Economics Review
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• v.15 no.4
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• pp.591-642
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• 2006

This paper intends to analyze economic impacts of commitment period and initial allocation in emissions trading using computable general equilibrium (CGE) modeling. The fully dynamic CGE model with perfect foresight assumption is employed to illustrate (i) how a model displays economic impact of $CO_2$ regulation upon different commitment periods: one-year budget clearing vs. 5-year commitment period, (ii) how major 8 energy-intensive industries respond to different ways to allocate initial allowances. According to the results of the analysis, it IS found that market players are motivated to bank the permits and tend to sell permits in earlier stage and to buy permits in later stage of commitment period. This implies that banking allows permit trading within a commitment period, which supports the conclusions of Kling and Rubin (1997). Other findings are related to efficiency. That is, emissions trading surpasses command and control, in terms of economic efficiency and longer terms of commitment period converge on lower permit price, In long term, initial allocation based on value-added performs the lowest GDP loss among different initial allocations.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.6
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• pp.163-171
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• 2021

In this paper, the energy transaction system was optimized by applying a resource allocation algorithm and deep reinforcement learning in the distributed power system. The power demand and supply environment were predicted by deep reinforcement learning. We propose a system that pursues common interests in power trading and increases the efficiency of long-term power transactions in the paradigm shift from conventional centralized to distributed power systems in the power trading system. For a realistic energy simulation model and environment, we construct the energy market by learning weather and monthly patterns adding Gaussian noise. In simulation results, we confirm that the proposed power trading systems are cooperative with each other, seek common interests, and increase profits in the prolonged energy transaction.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.153-153
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• 2018

Water-Energy-Food (WEF) nexus is a new holistic resources management concept that considers the interconnections among resources for sustainable resources planning and management. The current challenge is to fulfill the required demand in the lack of available resources. A traditional way to provide more available resource is by increase in production, but it caused increment of indirect demand of other interlinked resources. Importing resources from other area (where local supply is redundant) is another option to secure local resources with additional economic expenditure. The WEF nexus-trading model adapts the previously developed nationwide nexus simulation model with additional input parameters and functions to simulate trading scenarios. In general, the analysis starts with the quantification of local resources deficit (potential importing amount) and redundancy (potential exporting amount) of each area. Then, a trade module is initiated by determining possible donor area and importation amount. Finally, the nexus simulation for all area is re-run to determine final resources supply-demand results including the trading amount. The trade option provides an opportunity to meet local demands without draining local resources. However, the production capability of donor area may limit the importation amount. The newly developed trade option allows more alternatives for stakeholders to determine resources management plans.

• Journal of the Korea Society for Simulation
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• v.23 no.1
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• pp.1-10
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• 2014

A cloud computing is one of a parallel and distributed computing. The cloud computing provides some service for user with virtual resources. However, a user's service request does not show a time pattern. As a result, each resource also shows a different availability at the same time. This difference affects a quality of service (QoS) and a resource selection for users. Therefore, we propose the resource availability-based multi auction model for cloud service reservation and resource brokering system. The proposed system is to select the proper resource provider based on the users' request. The proposal adopts the multi phase of the auction to transact resources. The system evaluates the available factor of each resource on the auction phase, and finally reserves the service on the adaptive queue. The proposed model shows the better performance than other existing method.

• Environmental and Resource Economics Review
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• v.18 no.4
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• pp.587-635
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• 2009

The purpose of this study is to develop the Global Dynamic Computable General Equilibrium Model (Global CGE Model) in order to produce an economic impact analysis, including prospective obligations for the Post-2012 regime. This model explores the impact of an international emissions trading market and macroeconomic variables such as GNP, consumption, investment, imports and exports, in accordance with potential increased obligations on the Republic of Korea. Distinguishing it from existing studies, this Global CGE Model divides the global community into major economic groups, and in the capacity of the analyzed global model, reflecting the principle nations' macroeconomic indicators through the theoretical approach of endogenous growth theory. Policies such as an emissions trading scheme and carbon tax are reflected in the model. Also, in particular, the model reflects exogenous technological advances. According to this analysis, the stronger the greenhouse gas reductions, the greater the adverse effects on the economy; among macroeconomic indicators that appear, a significant decline is realized in the balance of trade, along with a significant decrease in investment and consumption. Energy dependence, in particular, plays a large role-varying in degree by industry type-, as greenhouse gas reductions would have a greater impact on energy-intensive industries. Furthermore, if Korea, currently recognized as a developing country, is given the obligation to reduce greenhouse gas emissions, competing countries such as China and other developing countries will be given an advantage.

• Journal of the Korean Solar Energy Society
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• v.39 no.6
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• pp.113-125
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• 2019

With the opening of the small power brokerage business market in December 2018, the small power trading market has started in Korea. Operators must submit the day-ahead estimates of power output and receive incentives based on its accuracy. Therefore, the accuracy of power generation forecasts is directly affects profits of the operators. The forecasting process for power generation can be divided into two procedure. The first is to forecast solar irradiation and the second is to transform forecasted solar irradiation into power generation. There are two methods for transformation. One is to simulate with physical model, and another is to use regression model. In this study, we found the best-fit regression model by analyzing hourly data of PV output and solar irradiation data during three years for 242 PV plants in Korea. The best model was not a linear model, but a sigmoidal model and specifically a Gompertz model. The combined linear regression and Gompertz curve was proposed because a the curve has non-zero y-intercept. As the result, R² and RMSE between observed data and the curve was significantly reduced.