• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.65 no.6
• /
• pp.969-978
• /
• 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.

• IE interfaces
• /
• v.17 no.2
• /
• pp.142-148
• /
• 2004

The objective of bridge construction cost allocation is to distribute in a fair and rational manner the bridge construction costs among those vehicles using the bridge. In most bridge construction cost allocation studies, bridge construction costs are mainly distributed according to traffic load(gross vehicle weight), without any consideration of bridge capacity requirements(the number of lanes). In this paper, a bridge cost allocation method for considering both traffic capacity and traffic loads is developed. The proposed method is based on cooperative game theory, particularly two concepts known as the Aumann-Shapley (A-S) value and Shapley value. This method can help to analyze the impact of traffic capacity costs. By applying the proposed method to an example, traffic capacity cost is found to be high so that traffic capacity should be considered to allocate the bridge construction costs to vehicle classes in a more equitable manner.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.35 no.4
• /
• pp.110-117
• /
• 2012

The demand for facility used in producing multi-products is changed dynamically for discrete and finite time periods. The excess or the shortage for facility is occurred according to difference of the facility capacity size and demand for facility through given time periods. The shortage facility is met through the outsourcing production. The excess facility cost is considered for the periods that the facility capacity is greater than the demand for the facility, and the outsourcing production cost is considered for the periods that the demand for facility is greater than the facility capacity. This paper addresses to determine the facility capacity size, outsourcing production products and amount that minimizes the sum of the facility capacity cost, the excess facility cost and the outsourcing production cost. The characteristics of the optimal solution are analyzed, and an algorithm applying them is developed. A numerical example is shown to explain the problem.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.64 no.4
• /
• pp.273-276
• /
• 2015

In this paper, ESS capacity installed in industrial customer is calculated using economic analysis. To do this, electric charge for industrial customer is analyzed and power management system(PMS) of ESS is selected. Reduction of kW cost and kWh cost are set to 'benefit' according to operation of ESS. Also, installation cost and maintenance cost of ESS are set to 'cost'. Proper ESS capacity is determined as a result of benefit-to-cost(B/C) analysis according to the variation of ESS installation cost. In case study, B/C is analyzed for the specific industrial customer and minimum capacity of ESS to make a profit are proposed for the customer.

• Industrial Engineering and Management Systems
• /
• v.9 no.2
• /
• pp.107-120
• /
• 2010

In today's uncertain economic environment, the evaluation of safety for investment alternatives is of practical importance in manufacturing companies. This paper examines a method of quantitatively evaluating profitability and risk for multiple alternatives using the total-cost unit-cost domain. The paper assumes such factors as unit sales price, sales and production volume, unit variable cost, fixed cost, and yield for each alternative. The paper incorporates the relationship between production capacity and demand, distinguishing between cases of production capacity surplus and shortage for each year over the entire planning horizon. The paper investigates the case in which the values of each factor independently move in the direction of decreasing profit each year, and clarifies the procedure of comparing safety among multiple investment alternatives on a single consolidated total-cost unit-cost domain. The difficulty of the problem lies in the method of consolidating multiple total-cost unit-cost domains into a single domain since the combination of years of capacity surplus and shortage depends upon the change values in each factor under consideration. A systematic method of evaluating profitability as well as risk is presented, and the validity of the proposed method is verified using a numerical example.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.20 no.5
• /
• pp.321-326
• /
• 2008

This paper presents and analyzes the effects of on-grid electricity cost, fuel price and initial capital cost of a CHP system, on the optimum DG and AC capacity and NPV, by using the ORNL CHP Capacity Optimizer, which was applied to a library in a university. By considering the current domestic energy cost and initial capital cost, it is shown that the installation and operation of the CHP system is not economical. However, with the current domestic CHP installation cost and fuel price, the NPV achieved by the installation of CHP system is greater when the on-grid electricity price is a factor of ${\times}1.5$ the present value. Regarding the initial capital cost of the CHP system, the reduction of the DG cost is much more economical than that of the AC cost, with respect to NPV. Electricity cost and fuel price have opposite effects on NPV, and NPV is more sensitive to an increase of the electricity cost than an increase of the fuel price.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.53 no.9
• /
• pp.481-486
• /
• 2004

In operation of distribution system, $DG_s$ Distributed Generations) are installed as an alternative of extension and establishment of substations and transmission and distribution lines according to increasing power demand. In operation planning of $DG_s$, determining optimal capacity and allocation gets economical pro(it and improves power reliability. This paper proposes determining a optimal number, size and allocation of $DG_s$ needed to minimize operation cost of distribution system. Capacity of $DG_s$ (or economical operation of distribution system estimated by the load growth and line capacity during operation planning duration, DG allocations are determined to minimize total cost with power buying cost. operation cost of DG, loss cost and outage cost using GA(Genetic Algorithm).

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.56 no.7
• /
• pp.1199-1204
• /
• 2007

In a cost based pool market, the generation capacity can be used as strategic bids by generation companies (Gencos) with the cost functions open to the market. Competition using strategic capacities is modeled by Cournot and Perfect Competiton (PC) model, and transformed into two by two payoff matrix game with Gencos' decision variables of Cournot and PC model. The payoff matrices vary when capacity payments are given to Gencos in accordance with their capacity bids. Nash Equilibrium (NE) in the matrices also moves with capacity price changes. In order to maximize social welfare of the market, NE should locate in a certain position of the payoff matrices, which corresponds to a PC NE. A concept of a critical capacity price is proposed and calculated in this paper that is defined as a minimum capacity price leading to PC NE. The critical capacity price is verified to work as a tool for suppressing a strategic capacity withholding in simulations of a test system.

• Nuclear Engineering and Technology
• /
• v.56 no.2
• /
• pp.644-654
• /
• 2024

After the Tohoku earthquake and tsunami (Japan, 2011), regulatory efforts to mitigate external hazards have increased both the safety requirements and the total capital cost of nuclear power plants (NPPs). In these circumstances, identifying not only disaster robustness but also cost-effective capacity setting of NPPs has become one of the most important tasks for the nuclear power industry. A few studies have been performed to relocate the seismic capacity of NPPs, yet the effects of multiple hazards have not been accounted for in NPP capacity optimization. The major challenges in extending this problem to the multihazard dimension are (1) the high computational costs for both multihazard risk quantification and system-level optimization and (2) the lack of capital cost databases of NPPs. To resolve these issues, this paper proposes an effective method that identifies the optimal multihazard capacity of NPPs using a multi-objective genetic algorithm and the two-stage direct quantification of fault trees using Monte Carlo simulation method, called the two-stage DQFM. Also, a capacity-based indirect capital cost measure is proposed. Such a proposed method enables NPP to achieve safety and cost-effectiveness against multi-hazard simultaneously within the computationally efficient platform. The proposed multihazard capacity optimization framework is demonstrated and tested with an earthquake-tsunami example.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.33 no.1
• /
• pp.71-79
• /
• 2010

This paper addresses capacity expansion planning model of distribution center under usability of public distribution center. For discrete and finite time periods, demands for distribution center increase dynamically. The capacity expansion planning is to determine the capacity expansion size of private distribution center and usage size of public distribution center for each period through the time periods. The capacity expansion of private distribution center or lease usage of public distribution center must be done to satisfy demand increase for distribution center. The costs are capacity expansion cost and excess capacity holding cost of private distribution center, lease usage cost of public distribution center. Capacity expansion planning of minimizing the total costs is mathematically modelled. The properties of optimal solution are characterized and a dynamic programming algorithm is developed. A numerical example is shown to explain the problem.