• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.793-796
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• 1996

This study proposes a new algorithm which performs a production simulation under various constraints and maintains computational efficiency. In order to consider the environmental and operational constraints, the proposed algorithm is based on optimization techniques formulated in LP form In the algorithm, "system characteristic constraints" reflect the system characteristics such as LDC shape, unit loading order and forced outage rate. By using the concept of Energy Invariance Property and two operational rules i.e. Compliance Rule for Emission Constraint, Compliance Rule for Limited Energy of Individual Unit, the number of system characteristic constraints is appreciably reduced. As a solution method of the optimization problem, the author uses Karmarkar's method which performs effectively in solving large scale LP problem. The efficiency of production simulation is meaningful when it is effectively used in power system planning. With the proposed production simulation algorithm, an optimal expansion planning model which can cope with operational constraints, environmental restriction, and various uncertainties is developed. This expansion planning model is applied to the long range planning schemes by WASP, and determines an optimal expansion scheme which considers the effect of supply interruption, load forecasting errors, multistates of unit operation, plural limited energy plants etc.

• 한국환경복원기술학회지
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• 제23권6호
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• pp.125-135
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• 2020

The uncontrolled urban expansion causes various social, economic problems and natural/environmental problems. Therefore, it is necessary to forecast urban expansion by identifying various factors related to urban expansion. This study aims to forecast it using a decision tree that is widely used in various areas. The study used geographic data such as the area of use, geographical data like elevation and slope, the environmental conservation value assessment map, and population density data for 2006 and 2018. It extracted the new urban expansion areas by comparing the residential, industrial, and commercial zones of the zoning in 2006 and 2018 and derived a decision tree using the 2006 data as independent variables. It is intended to forecast urban expansion in 2030 by applying the data for 2018 to the derived decision tree. The analysis result confirmed that the distance from the green area, the elevation, the grade of the environmental conservation value assessment map, and the distance from the industrial area were important factors in forecasting the urban area expansion. The AUC of 0.95051 showed excellent explanatory power in the ROC analysis performed to verify the accuracy. However, the forecast of the urban area expansion for 2018 using the decision tree was 15,459.98㎢, which was significantly different from the actual urban area of 4,144.93㎢ for 2018. Since many regions use decision tree to forecast urban expansion, they can be useful for identifying which factors affect urban expansion, although they are not suitable for forecasting the expansion of urban region in detail. Identifying such important factors for urban expansion is expected to provide information that can be used in future land, urban, and environmental planning.

• Journal of Electrical Engineering and Technology
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• 제10권3호
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• pp.895-904
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• 2015

This paper presents a probabilistic approach of reliability evaluation and economic assessment for solving transmission network expansion planning problems. Three methods are proposed for TNEP, which are reorganizing the existing power system focused on the buses of interest, selecting candidates using modified system operating state method with healthy, marginal and at-risk states, and finally choosing the optimal alternative using cost-optimization method. TNEP candidates can be selected based on the state reliability such as sufficient and insufficient indices, as proposed in this paper. The process of economic assessment involves the costs of construction, maintenance and operation, congestion, and outage. The case studies are carried out with modified IEEE-24 bus system and Jeju island power system expansion plan in Korea, to verify the proposed methodology.

• KIEE International Transactions on Power Engineering
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• 제5A권1호
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• pp.46-55
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• 2005

This paper proposes a new method for choice of the best transmission system expansion plan on the side of highest satisfaction level of decision maker using fuzzy integer programming. The proposed method considers the permissibility and ambiguity of the investment budget (economics) for constructing the new transmission lines and the delivery marginal rate (reliability criteria) of the system by modeling the transmission expansion problem as a fuzzy integer programming one. It solves the optimal strategy (reasonable as well as flexible) using a fuzzy set theory-based on branch and bound method that utilizes a network flow approach and the maximum flow-minimum cut set theorem. Under no or only a very small database for the evaluation of reliability indices, the proposed technique provides the decision maker with a valuable and practical tool to solve the transmission expansion problem considering problem uncertainties. Test results on the 63-bus test system show that the proposed method is practical and efficiently applicable to transmission expansion planning.

• 대한전기학회논문지
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• 제34권8호
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• pp.308-316
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• 1985

This paper proposes an analytic tool for long-term generation expansion planning based on the maximum principle. Many research works have been performed in the field of generation expansion planning. But few works can be found with the maxinmum principle. A recently published one worked by professor Young Moon Park et al. shows remarkable improvements in modeling and computation. But this modeling allows only thermal units. This paper has extended Professor Park's model so that the optimal pumped-storage operation is taken into account. So the ability for practical application is enhanced. In addition, the analytic supply-shortage cost function is included. The maximum principle is solved by gradient search due to its simplicity. Every iteration is treated as if mathematical programming such that all controls from the initial to the terminal time are manipulated within the same plane. Proposed methodology is tested in a real scale power system and the simulation results are compared with other available package. Capability of proposed method is fully demonstrated. It is expected that the proposed method can be served as a powerful analytic tool for long-term generation expansion planning.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 제39회 하계학술대회
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• pp.564-565
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• 2008

All over the world, energy environment dramatically changes because of highly oil price, global warming and reduction of greenhouse gas. The power sector is effected directly indirectly by these factors. Especially, the power expansion planning of power sector should adapt itself to new surroundings. This paper presents the new system of the power expansion planning that reflects Genco's needs, power market and variable conditions. This presented system would provide regulator and Gencos with useful information about a power planning.

• 대한전기학회논문지:전력기술부문A
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• 제50권4호
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• pp.180-187
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• 2001

This paper proposes an efficient evolutionary programming algorithm for solving a generation expansion planning(GEP) problem known as a highly-nonlinear dynamic problem. Evolutionary programming(EP) is an optimization algorithm based on the simulated evolution (mutation, competition and selection). In this paper, new algorithm is presented to enhance the efficiency of the EP algorithm for solving the GEP problem. By a domain mapping procedure, yearly cumulative capacity vectors are transformed into one dummy vector, whose change can yield a kind of trend in the cost value. To validate the proposed approach, this algorithm is tested on two cases of expansion planning problems. Simulation results show that the proposed algorithm can provide successful results within a resonable computational time compared with conventional EP and dynamic programming.

• 대한산업공학회지
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• 제16권1호
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• pp.51-58
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• 1990

A deterministic capacity expansion planning model for a two-capacity type facility is analyzed to determine the sizes to be expanded in each period so as to supply the known demands for two distinct capacity type(product) on time and to minimize the total cost incurred over a finite planning horizon of T periods. The model assumes that capacity unit of the facility simultaneously serves a prespecified number of demand units of each capacity type, that capacity type 1 can be used to supply demands for capacity type 2, but that capacity type 2 can't be used to supply demands for capacity type 1. Capacity expansion and excess capacity holding cost functions considered are nondecreasing and concave. The structure of an optimal solution is characterized and then used in developing an efficient dynamic programming algorithm that finds optimal capacity planning policy.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1983년도 하계학술회의강연.논문초록집
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• pp.156-158
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• 1983

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 춘계학술대회 논문집 전력기술부문
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• pp.77-83
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• 2001