• 전기학회논문지
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• 제65권6호
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• pp.969-978
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• 2016

Around the world are increasing the demand for ESS. Currently, the domestic is expected to benefit by operating ESS. In the domestic, it is expected to benefit from operations of the installed ESS because of the introduction of ESS less capacity. However ESS capacity to the maximum profit occurs is unknown. ESS is different from the charge-discharge characteristics and the reserve to replace, depending on the application. Therefore, it should be established in accordance with the ESS optimal capacity according to the purpose used because it can maximize the quality and efficiency of the electric energy. To the ESS optimal capacity estimation by the purpose used, It should compare the investment cost caused by ESS facility installation and operation cost caused by operating ESS. In this paper, the operation mathematical model for estimating marginal operation costs established. In operation mathematical model, operating cost is considered fuel cost and no-load cost start-up cost. Because no-load cost and start-up cost are not related to cost and power plant output, there are expressed an integer variable costs as a step function.

• 한국인터넷방송통신학회논문지
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• 제16권2호
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• pp.181-188
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• 2016

본 논문은 경제급전 최적화 문제에 개별 발전회사별로 독립적으로 경제급전을 수행하는 방법에 비해 중앙에서 통합하여 경제급전 최적화를 수행하는 경우가 보다 경제적임을 보였다. 이 경우에 적용된 알고리즘으로 밸브지점으로 발전량을 조절하는 균형방법을 수행한 후 발전량을 감소시킬 때의 비용 감소분과 증가시킬 때의 비용 증가분 차이로 발전량을 상호 교환하는 방법으로 최적화를 수행하였다. 10대, 13대과 40대-발전기를 독립적으로 운영하는 경우와 통합된 63대-발전기를 경제급전하는 경우를 비교한 결과 통합운영 방법이 독립적 경제급전에 비해 발전비용을 획기적으로 감소시켜 경제적인 이익을 극대화 시킬 수 있음을 보였다.

• 한국병원경영학회지
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• 제22권3호
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• pp.46-60
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• 2017

The purpose of this study is to analyze the difference of productivity according to environmental factors among 25 Regional base public hospitals. Also this study is to propose a method to improve the productivity of Regional base public hospitals in the future by improving the public performance and stable management performance by studying the productivity variables affecting profitability. The survey period was based on the last three years, and 25 Regional base public hospitals were selected for the survey. The dependent variable is the total capital medical marginal profitability and the medical profit marginal profitability which are the indicators of profitability. The independent variable, productivity, is classified into three indicators: capital productivity, labor productivity, and value added productivity. The ANOVA analysis method was used to analyze the productivity difference according to the frequency factor and the environmental factors of the Regional base public hospitals. Finally, we conducted a hierarchical regression analysis to examine the productivity variables affecting profitability. The results of this study showed that there were differences in productivity due to environmental factors such as hospital size, competition in the local medical market, and differences in management performance. The difference in productivity and profitability depending on the environmental factors suggests that it is difficult for Regional base public hospitals in each regional base to perform a balanced public service. In order to overcome this, it is necessary to provide balanced medical services such as government financial support expansion, regional medical demand forecasting and facility infrastructure construction.

• Journal of Electrical Engineering and Technology
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• 제13권6호
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• pp.2227-2235
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• 2018

Under the current policies and compensation rules in South Korea, Photovoltaic (PV) generation supplier can maximize the profit by combining PV generation with Energy Storage System (ESS). However, the existing operational strategy of ESS is not able to maximize the profit due to the limitation of ESS capacity. In this paper, new ESS scheduling algorithm is introduced by utilizing the System Marginal Price (SMP) and PV generation forecasting to maximize the profits of PV generation supplier. The proposed algorithm determines the charging time of ESS by ranking the charging schedule from low to high SMP when PV generation is more than enough to charge ESS. The discharging time of ESS is determined by ranking the discharging schedule from high to low SMP when ESS energy is not enough to maintain the discharging. To compensate forecasting error, the algorithm is updated every hour to apply the up-to-date information. The simulation is performed to verify the effectiveness of the proposed algorithm by using actual PV generation and ESS information.

• Journal of Electrical Engineering and Technology
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• 제5권4호
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• pp.530-537
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• 2010

By development of renewable energy and more efficient facilities in an increasingly deregulated electricity market, the operation cost of distributed generation (DG) is becoming more competitive. International environmental regulations of the leaking carbon become effective to reinforce global efforts for a low-carbon paradigm. Through increased DG, operators of DG are able to supply electric power to customers who are connected directly to DG as well as loads that are connected to entire network. In this situation, a community energy system (CES) with DGs is a new participant in the energy market. DG's purchase price from the market is different from the DG's sales price to the market due to transmission service charges and other costs. Therefore, CES who owns DGs has to control the produced electric power per hourly period in order to maximize profit. Considering the international environment regulations, CE will be an important element to decide the marginal cost of generators as well as the classified fuel unit cost and unit's efficiency. This paper introduces the optimal operation of CES's DG connected to the distribution network considering CE. The purpose of optimization is to maximize the profit of CES. A Particle Swarm Optimization (PSO) will be used to solve this complicated problem. The optimal operation of DG represented in this paper would guide CES and system operators in determining the decision making criteria.

• 경영과학
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• 제28권3호
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• pp.15-29
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• 2011

In this paper, we consider a system working at both primary service and secondary service. A server can switch between the primary service and the secondary service or it can be assigned to secondary service as a dedicated server. A service policy is characterized by the number of servers dedicated to the secondary service and a rule for switching the remaining servers between two services. The primary service system is modelled as a Markovian queueing system and the throughput is a function of the number of servers, buffer capacity, and service policy. And the secondary service system has a service level requirement strategically determined to perform the service assigned. There is a revenue obtained from throughput and costs due to servers and buffers. We study the problem of simultaneously determining the optimal total number of servers, buffers, and service policy to maximize profit of the system subject to both an expected customer waiting time constraint of the primary service and a service level constraint of the secondary service and develop an algorithm which can be successfully applied with the small number of computations.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 A
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• pp.374-375
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• 2006

전력시장이 경쟁체제로 바뀜에 따라 전력거래소는 적정예비력을 에너지 시장과 분리된 예비력 시장을 통해 확보해야 한다. 발전사업자는 두 시장에서 이득을 얻을 수 있으므로 이득을 고려하여 전략적인 입찰함수를 결정한다. 본 연구에서는 에너지 시장과 예비력 시장을 모형화하고 lemke 알고리즘을 사용하여 경쟁으로 나타나는 균형점을 해석한다. 또한 균형상태의 시장실적을 분석하여 발전사업자의 전략적인 행태를 분석한다. 마지막으로 예비력 시장과 에너지 시장의 참여유인을 한계이득과 관련지어 분석한다.

• 한국경영과학회지
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• 제32권3호
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• pp.17-31
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• 2007

In this paper, we consider a service system with bi-functional servers, which can switch between the primary service room and the secondary room. A service policy is characterized by the switching paints which depend on the queue length in the primary service room and the service level requirement constraint of the secondary room. The primary service room is modeled as a Markovian queueing system and the throughput of the primary service room is function of the total number of bi-functional servers. the buffer capacity of the primary service room, and the service policy. There is a revenue obtained from throughput and costs due to servers and buffers. We study the problem of simuitaneously determining the optimal number of servers, buffer capacity, and service policy to maximize profit of the service system, and develop an algorithm which can be successfully applied with the small number of computations.

• 전기학회논문지
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• 제58권8호
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• pp.1504-1511
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• 2009

By development of renewable energies and high-efficient facilities and deregulated electricity market, the operation cost of distributed generation(DG) becomes more competitive. The amount of distributed resource is considerably increasing in the distribution network consequently. Also, international environmental regulations of the leaking carbon become effective to keep pace with the global efforts for low-carbon paradigm. It contributes to spread out the business of DG. Therefore, the operator of DG is able to supply electric power to customers who are connected directly to DG as well as loads that are connected to entire network. In this situation, community energy system(CES) having DGs is recently a new participant in the energy market. DG's purchase price from the market is different from the DG's sales price to the market due to the transmission service charges and etc. Therefore, CES who owns DGs has to control the produced electric power per hourly period in order to maximize the profit. If there is no regulation for carbon emission(CE), the generators which get higher production than generation cost will hold a prominent position in a competitive price. However, considering the international environment regulation, CE newly will be an important element to decide the marginal cost of generators as well as the classified fuel unit cost and unit's efficiency. This paper will introduce the optimal operation of CES's DG connected to the distribution network considering CE. The purpose of optimization is to maximize the profit of CES and Particle Swarm Optimization (PSO) will be used to solve this problem. The optimal operation of DG represented in this paper is to be resource to CES and system operator for determining the decision making criteria.

• 한국항해학회지
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• 제7권1호
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• pp.1-32
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• 1983

The delay due to congestion has recently attracted widespread attention with the analysis of over-all operation at the port. But, the complexity of the situation is evident in view of the large number of factors which impinge on the considerable end. Queueing theory is applicable to a large scale transportation system which is associated with arrivals of vessels in a large port. The attempt of this paper is to make an extensive analysis of the port transport system and its economic implications from the viewpoint that port is one of the physical distribution facilities and a kind of queueing system which includes ships and cargoes as port customer. By analyzing the real data on the Port of Pusan, it is known that this port can be represented as a set of multi-channel with identical setof Poisson arrival and Erlang service time, and also it is confirmed that the following formula is suitable to calculate the mean delay in this port, namely, $W_4={\frac{\rho}{\lambda(1-\rho)} {\frac{e_N(\rho{\cdot}N)}{D_{N-1}(\rho{\cdot}N)}$ where, ${\lambda}$: mean arrival rate $\mu$: mean servicing rate; N: number of servicing channel; ${\rho}$: utillization rate (${\lambda}/N{\mu}$) $e_N$: the Poisson function Coming to grips with the essentials of the cost of delay due to congestion, a simple ship journey cost model is adopted and the operating profit sensitivity to variation in port time is examined, and for purpose of a future development for port princing service the marginal cost is approximately calculated on the basis of queueing theory.