• Journal of Electrical Engineering and Technology
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• v.5 no.1
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• pp.21-27
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• 2010

This paper examines the long-run social welfare maximization problems facing public utilities, which includes consideration of the cost of capital or other fixed costs of production, from which it derives optimal investment decisions in a reliability differentiated pricing based market. Reliability differentiated pricing policies lead to straightforward mathematical results on optimal investment decisions in generation and transmission expansion planning. This paper presents the mathematical conditions for optimal investment decisions.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.8
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• pp.585-592
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• 1989

This paper presents an efficient algorithm for the reactive planning of transmission network under normal operating conditions. The optimal operation of a power system is a prerequisite to obtain the optimal investment planning. The operation problem is decomposed into a P-optimization module and a Q-optimization module, but both modules use the same objective function of generation cost. In the investment problem, a new variable decomposition technique is adopted which can operate the operation and the investment variables. The optimization problem is solved by using the gradient projection method (GPM).

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.229-244
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• 2004

This study addresses the problem of flexible technology acquisition in multi-product market when demands are uncertain. We confine the concept of flexibility to the ability of manufacturing system to produce a number of different types of products, called product-mix flexibility type. And an analytical model in which economies of scope is incorporated explicitly as a feature of flexible technology is presented to find the optimal investment decision to acquire flexible technology and optimal production planning. The characteristics of optimal investment strategy related to capacity and production planning are discussed.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.2
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• pp.135-142
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• 2005

This study addresses the problem of flexible technology acquisition in a multi-product market when demands are uncertain. We confine the concept of flexibility to the ability of manufacturing system to produce a number of different types of products, called a product-mix flexibility type. And an analytical model in which the economies of scope are incorporated explicitly as a feature of flexible technology is presented to find the optimal investment decision to acquire flexible technology and optimal production planning. The characteristics of optimal investment strategy related to capacity and production planning are discussed.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.2
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• pp.77-90
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• 2009

Total profit level Increases if a company increase the cost for achieving R&D related goals of equipment productivity enhancement, production cost saving, or for achieving equipment scale target, sales volume goal. But how much money should be invested to achieve a certain level of profit? We formulated the model to set the optimal goal levels to minimize the investment cost under the constraint that certain level of total profit should be guaranteed. This model derived from a case of P steel company. We found that this should be considered in relation with the production sales planning (known as optimal product mix problem) to guarantee the profit. We suggested a nonlinear programming model, 3 valiant form of the p+roduct mix problem. We can find the optimal Investment level for the R&D related goals or sales volume goal, equipment scale target for the P steel company using the model.

• Journal of the Korean Regional Science Association
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• v.10 no.2
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• pp.45-51
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• 1994

The purpose of this paper is to present the optimal investment conditions of SOC facilities for maximizing regional social welfare in implementing the urban development project in the theoretical fashion. Particularily, SOC facilities are divided into both supply-side($P_s$) and demand-side SOC ($P_d$) in the paper. General equilibrium analysis from the intra-regional viewpoint by utilizing Pareto's Optimal Conditions and by revising Samuleson's Conditions for public goods($P_s$ and $P_d$) results in the optimum pattern of SOC investment. The following are important implications from the analysis. First, rather than the pursue social equity, SOC investment is to resolve the issue of efficiency to activate the regional economy. Second, the marginal rate of transformation (MRT) between $P_s$ and $P_d$ in the region is to play a significant role in structuring SOC investment plant of local government for social welfare maximization. Third, the optimal SOC investment policy based on this regional economy but also to generate the enhancement of soical amenities of the residents.

• Journal of Electrical Engineering and Technology
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• v.5 no.2
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• pp.239-245
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• 2010

Today, as power trades between generators and loads are liberalized, the uncertainty level of power systems is rapidly increasing. Therefore, transmission operators are required to incorporate these uncertainties when establishing an investment plan for effective operation of transmission facilities. This paper proposes the methodology for an optimal solution of transmission expansion plans for the long-term in a deregulated power system. The proposed model uses the probabilistic cost of transmission congestion for various scenarios and the annual increasing rates of loads. The locations and the installation times of expanded transmissions lines with minimum cost are acquired by the model. To minimize the investment risk, the Mean-Variance Markowitz portfolio theory is applied to the model. In a case study, the optimal solution of a transmission expansion plan is obtained considering the uncertain power market.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.4
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• pp.560-566
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• 2008

Today, as the power trades between generation companies and power customer are liberalized, the uncertainty level of operated power system is rapidly increased. Therefore, transmission operators as decision makers for transmission expansion are required to establish a deliberate investment plan for effective operations of transmission facilities considering forecasted conditions of power system. This paper proposes the methodology for the optimal solution of transmission expansion in deregulated power system. The paper obtains the expected value of transmission congestion cost for various scenarios by using occurrence probability. In addition, the paper assumes that increasing rates of loads are the probability distribution and indicates the location of expanded transmission line, the time for transmission expansion with the minimum cost for the future by performing the Montecarlo simulation. To minimize the investment risk as the variance of the congestion cost, Mean-Variance Markowitz portfolio theory is applied to the optimization model by the penalty factor of the variance. By the case study, the optimal solution for transmission expansion plan considering the feature of market participants is obtained.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.797-799
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• 1997

This paper presents an operation and planning model of integrated energy systems which consist of small scale cogeneration systems, thermal accumulator, ice storage and electrical energy storage systems. In the proposed planning model, an optimization of total cost which contains investment, operation, thermal shortage and salvage costs has carried out with the maximum principle based on the lifetime of each system component and unit price per capacity. From this model, optimal investment capacity per annum can be determined during the studied periods using the marginal costs according to the operation characteristics of each system component.

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.2
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• pp.39-60
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• 1995

In this paper, an integration of stochastic dynamic programming (SDP), integer goal programming (IGP) and analytic hierarchy process (AHP) is proposed to handle multiobjective-multicriteria sequential decision making problems under uncertainty inherent in R & D investment planning. SDP has its capability to handle problems which are sequential and stochastic. In the SDP model, the probabilities of the funding levels in any time period are generated using a subjective model which employs functional relationships among interrelated parameters, scenarios of future budget availability and subjective inputs elicited from a group of decision makers. The SDP model primarily yields an optimal investment planning policy considering the possibility that actual funding received may be less than anticipated one and thus the projects being selected under the anticipated budget would be interrupted. IGP is used to handle the multiobjective issues such as tradoff between economic benefit and technology accumulation level. Other managerial concerns related to the determination of the optimal project portifolio within each stage of the SDP model. including project selection, project scheduling and annual budget allocation are also determined by the IGP. AHP is proposed for generating scenario-based transformation probabilities under budgetary uncertainty and for quantifying the environmental risk to be considered.