• 한국시스템다이내믹스연구
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• 제2권2호
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• pp.25-40
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• 2001

This paper describes the forecast of power plant construction in a competitive korean electricity market. In Korea, KEPCO (Korea Electric Power Corporation, fully controlled by government) was responsible for from the production of the electricity to the sale of electricity to customer. However, the generation part is separated from KEPCO and six generation companies were established for whole sale competition from April 1st, 2001. The generation companies consist of five fossil power companies and one nuclear power company in Korea at present time. Fossil power companies are scheduled to be sold to private companies including foreign investors. Nuclear power company is owned and controlled by government. The competition in generation market will start from 2003. ISO (Independence System Operator will purchase the electricity from the power exchange market. The market price is determined by the SMP(System Marginal Price) which is decided by the balance between demand and supply of electricity in power exchange market. Under this uncertain circumstance, the energy policy planners such as government are interested to the construction of the power plant in the future. These interests are accelerated due to the recent shortage of electricity supply in California. In the competitive market, investors are no longer interested in the investment for the capital intensive, long lead time generating technologies such as nuclear and coal plants. Large unclear and coal plants were no longer the top choices. Instead, investors in the competitive market are interested in smaller, more efficient, cheaper, cleaner technologies such as CCGT(Combined Cycle Gas Turbine). Electricity is treated as commodity in the competitive market. The investors behavior in the commodity market shows that the new investment decision is made when the market price exceeds the sum of capital cost and variable cost of the new facility and the existing facility utilization depends on the marginal cost of the facility. This investors behavior can be applied to the new investments for the power plant. Under these postulations, there is the potential for power plant construction to appear in waves causing alternating periods of over and under supply of electricity like commodity production or real estate production. A computer model was developed to sturdy the possibility that construction will appear in waves of boom and bust in Korean electricity market. This model was constructed using System Dynamics method pioneered by Forrester(MIT, 1961) and explained in recent text by Sternman (Business Dynamics, MIT, 2000) and the recent work by Andrew Ford(Energy Policy, 1999). This model was designed based on the Energy Policy results(Ford, 1999) with parameters for loads and resources in Korea. This Korea Market Model was developed and tested in a small scale project to demonstrate the usefulness of the System Dynamics approach. Korea electricity market is isolated and not allowed to import electricity from outsides. In this model, the base load such as unclear and large coal power plant are assumed to be user specified investment and only CCGT is selected for new investment by investors in the market. This model may be used to learn if government investment in new unclear plants could compensate for the unstable actions of private developers. This model can be used to test the policy focused on the role of unclear investments over time. This model also can be used to test whether the future power plant construction can meet the government targets for the mix of generating resources and to test whether to maintain stable price in the spot market.

• 전기학회논문지
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• 제60권4호
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• pp.726-732
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• 2011

To establish the transmission system expansion plan based on reliability, valuation of outage cost become more important. In previous studies about outage cost estimation, macroscopic, microscopic and analytic methods are proposed but they have some limit. For instance, microscopic method involves a complex field survey process and macroscopic method can not estimate regional outage cost. So in this paper, a new method to estimate regional macroscopic outage cost using the reduction of value added due to power outages is proposed. This method uses regional add value according to production activities called Gross Regional Domestic Product(GRDP) and regional electricity sales.

• Journal of Electrical Engineering and Technology
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• 제2권2호
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• pp.201-207
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• 2007

As the power industry moves towards open competition, there has been a need for methodology to evaluate distribution power system reliability by using customer interruption costs, particularly in power supply zones under the competitive electricity market. This paper presents an algorithm to evaluate system average interruption duration index, expected energy not supplied, and system outage cost taking into consideration failure rate of the distribution facility and industrial customer interruption cost. Also, to apply this algorithm to evaluate system outage cost presented in this paper, the distribution arrangement of a dual supply system consisting of mostly high voltage customers in an industrial complex in Korea is used as a sample case study. Finally, evaluation results of system interruption cost, system average interruption duration index, and expected energy not supplied in the sample industrial complex area are shown in detail.

• 설비공학논문집
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• 제16권7호
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• pp.673-682
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• 2004

The cost accounting of products on energy system is important for evaluating the economical efficiency and deciding the reasonable sale price. In the present, the suggested OECOPC method was applied to a combined cycle cogeneration, and each unit cost of electricity and heat products was calculated. In addition, the previous thermoeconomic methods were applied and calculated to equal system. As a result of comparing various methods, the unit costs by OECOPC method were calculated in the middle value of those. This result tells that OECOPC methods are most moderate. The suggested OECOPC method can apply any energy system. Hence this method is expected to make contribution to cost accounting on energy System.

• Journal of Construction Engineering and Project Management
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• 제3권3호
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• pp.23-34
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• 2013

As climate change and environmental pollution become one of the biggest global issues today, new renewable energy, especially solar photovoltaic (PV) system, is getting great attention as a sustainable energy source. However, initial investment cost of PV system is considerable, and thus, it is crucial to predict electricity generation accurately before installation of the system. This study analyzes the loss ratio of solar photovoltaic electricity generation from the actual PV system monitoring data to predict electricity generation more accurately in advance. This study is carried out with the following five steps: (i) Data collection of actual electricity generation from PV system and the related information; (ii) Calculation of simulation-based electricity generation; (iii) Comparative analysis between actual electricity generation and simulation-based electricity generation based on the seasonality; (iv) Stochastic approach by defining probability distribution of loss ratio between actual electricity generation and simulation-based electricity generation ; and (v) Case study by conducting Monte-Carlo Simulation (MCS) based on the probability distribution function of loss ratio. The results of this study could be used (i) to estimate electricity generation from PV system more accurately before installation of the system, (ii) to establish the optimal maintenance strategy for the different application fields and the different season, and (iii) to conduct feasibility study on investment at the level of life cycle.

• 국제학술발표논문집
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• The 5th International Conference on Construction Engineering and Project Management
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• pp.375-385
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• 2013

As climate change and environmental pollution become one of the biggest global issues today, new renewable energy, especially solar photovoltaic (PV) system, is getting great attention as a sustainable energy source. However, initial investment cost of PV system is considerable, and thus, it is crucial to predict electricity generation accurately before installation of the system. This study analyzes the loss ratio of solar photovoltaic electricity generation from the actual PV system monitoring data to predict electricity generation more accurately in advance. This study is carried out with the following five steps: (i) Data collection of actual electricity generation from PV system and the related information; (ii) Calculation of simulation-based electricity generation; (iii) Comparative analysis between actual electricity generation and simulation-based electricity generation based on the seasonality; (iv) Stochastic approach by defining probability distribution of loss ratio between actual electricity generation and simulation-based electricity generation ; and (v) Case study by conducting Monte-Carlo Simulation (MCS) based on the probability distribution function of loss ratio. The results of this study could be used (i) to estimate electricity generation from PV system more accurately before installation of the system, (ii) to establish the optimal maintenance strategy for the different application fields and the different season, and (iii) to conduct feasibility study on investment at the level of life cycle.

• 상하수도학회지
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• 제31권6호
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• pp.529-537
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• 2017

Membrane filtration process is an advanced water treatment technology that has excellently removes turbidity and microorganisms. However, it is known that it has problems such as low economic efficiency and the operating stability. Therefore, this study was to evaluate on the economical feasibility and operational stability comparison of membrane and sand filtration process in Im-sil drinking water treatment plant. For the economic analysis of each process, the electricity cost and chemical consumption were compared. In the case of electric power consumption, electricity cost is $68.67KRW/m^3$ for sand filtration and $79.98KRW/m^3$ for membrane filtration, respectively. Therefore, membrane filtration process was about 16% higher than sand filtration process of electricity cost. While, the coagulant usage in the membrane filtration process was 43% lower than the sand filtration process. Thus, comparing the operation costs of the two processes, there is no significant difference in the operating cost of the membrane filtration process and the sand filtration process as $85.94KRW/m^3$ and $79.71KRW/m^3$ respectively (the sum of electricity and chemical cost). As a result of operating the membrane filtration process for 3 years including the winter season and the high turbidity period, the filtrated water turbidity was stable to less than 0.025 NTU irrespective of changes in the turbidity of raw water. And the CIP(Clean In Place) cycle turned out to be more than 1 year. Based on the results of this study, the membrane filtration process showed high performance of water quality, and it was also determined to have the economics and operation stability.

• 플랜트 저널
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• 제12권4호
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• pp.32-36
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• 2016

본 연구에서는 CGAM 인수성능에 대한 페널티 비용 책정 방법론이 제안되어 있다. CGAM 성능시험결과 전기생산량에서 0.33% 감소, 전기생산효율에서 0.37% 감소, 열생산량에서 0.35% 증가, 열생산효율에서 0.31% 증가하였다. 페널티비용 책정 결과 전기생산량에서 -$22,138, 전기생산효율에서 -$24,348, 열생산량에서 +$11,661, 열생산효율에서 +$10,451로 산정되었다. 위 4 종류의 페널티 산정 계산은 명확하나, 총 페널티 비용은 위 4 종류를 어떻게 조합하는 가에 따라 달라진다. 계산결과 최대 -$46,486부터 -$13,898 범위였다. 따라서 총 페널티 정의에 대한 발주처와 건설사의 협의는 매우 중요하다는 것을 알 수 있다.

• KIEAE Journal
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• 제15권6호
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• pp.5-10
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• 2015

Purpose: To evaluate the economic performance of grid-connected photovoltaic system in residential house, household electricity bill policy of Korea Electric Power Corporation (KEPCO) must be applied precisely, and market tendency and uncertainty of system also need to be considered. In this study, to evaluate the economic feasibility of PV system, we measured PV power generation and electricity consumption of six of Green home in Daejeon through web based remote monitoring system. Method: We applied Monte-Carlo simulation based on life cycle cost analysis, to reflect an uncertainty of main factor in economic feasibility evaluation of photovoltaic system. Result: First, with deterministic analysis, the difference of NPV of cumulative financial savings among households varied from -3,310 ~ 24,170 thousand won, portraying notably big range. Also the possibility of getting the same result was 50% when applying uncertainty. Second, the higher electricity consumption is, the more economic feasibility of photovoltaic system increases because KEPCO uses progressive taxation in household electricity bill policy. Third, The contribution to variance of electricity price increases in NPV varied from 98.5% to 99.9%. While the inflation rate and annual degradation contributed very little to none.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권1호
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• pp.97-115
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• 2022

Smart power grid is a user friendly system that transforms the traditional electric grid to the one that operates in a co-operative and reliable manner. Demand Response (DR) is one of the important components of the smart grid. The DR programs enable the end user participation by which they can communicate with the electricity service provider and shape their daily energy consumption patterns and reduce their consumption costs. The increasing demands of electricity owing to growing population stresses the need for optimal usage of electricity and also to look out alternative and cheap renewable sources of electricity. The solar and wind energy are the promising sources of alternative energy at present because of renewable nature and low cost implementation. The proposed work models a smart home with renewable energy units. The random nature of the renewable sources like wind and solar energy brings an uncertainty to the model developed. A stochastic dual descent optimization method is used to bring optimality to the developed model. The proposed work is validated using the simulation results. From the results it is concluded that proposed work brings a balanced usage of the grid power and the renewable energy units. The work also optimizes the daily consumption pattern thereby reducing the consumption cost for the end users of electricity.