• International Journal of Fuzzy Logic and Intelligent Systems
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• 제13권3호
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• pp.171-177
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• 2013

This paper presents a fuzzy set method to enforce complementarity constraints (CCs) in a nonlinear interior point method (NIPM)-based optimization. NIPM is a Newton-type approach to nonlinear programming problems, but it adopts log-barrier functions to deal with the obstacle of managing inequality constraints. The fuzzy-enforcement method has been implemented for CCs, which can be incorporated in optimization problems for real-world applications. In this paper, numerical simulations that apply this method to power system optimal power flow problems are included.

• 한국국방경영분석학회지
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• 제25권2호
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• pp.97-105
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• 1999

When infeasible interior-point methods are applied to large-scale linear programming problems, they become unstable and cannot solve the problems if convergence rates of primal feasibility, dual feasibility and duality gap are not well-balanced. We can balance convergence rates of primal feasibility, dual feasibility and duality gap by introducing control parameters. As a result, the stability and the efficiency of infeasible interior-point methods can be improved.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 A
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• pp.122-124
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• 2001

This Paper presents an application technique for solving the Security Constrained Economic Dispatch(SCED) problem using the Interior Point Method. The optimal power flow solution is obtained by optimizing the given generation cost objectives function subject to the system security constraints. The proposed technique is applied to a prototype 6-bus system for evaluation and test.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제9권3호
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• pp.238-243
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• 2009

This paper present same thodology for the classification of power system voltage stability, the trajectory of which to instability is monotonic, using an interior point method based support vector machine(IPMSVM). The SVM based voltage stability classifier canp rovide real-time stability identification only using the local measurement data, without the topological information conventionally used.

• 한국화재소방학회:학술대회논문집
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• 한국화재소방학회 1996년도 학술발표회
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• pp.43-48
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• 1996

It is considered that automobile inner space is dangerous due to its combustion characteristics. (Automobile interior is largely made by plastic materials.) At last it is necessary to study on combustion characteristics of automobile interior. we could obtain its rapid combustion velocity and high smoke density by using ASTM D 2863 apparatus, DSC (Differential Scanning Calorimetry), Smoke density apparatus and so on. The study is summerized by following conditions and results. 1. Sample size was 150mm(length)$\times$60mmwidth). 2. Combustion velocity appeared peak point in the 2cm point. 3. PVC and foam layers are important factors in the face of smoke density. 4. Using DSC, we obtained the point that automobile interior was melted. 5. Automobile interior should be improved because of its low L.O.I value and rapid flame propagation velocity.

• 대한산업공학회지
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• 제27권3호
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• pp.274-280
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• 2001

In this research, we develop a specialized primal-dual interior point solver for the multicommodity flow problems (MCFP). The Castro's approach that exploits the problem structure is investigated and several aspects that must be considered in the implementation are addressed. First, we show how preprocessing techniques for linear programming(LP) are adjusted for MCFP. Secondly, we develop a procedure that extracts a network structure from the general LP formulated MCFP. Finally, we consider how the special structure of the mutual capacity constraints is exploited. Results of comupational comparison between our solver and a general interior point solver are also included.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 제36회 하계학술대회 논문집 A
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• pp.858-860
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• 2005

This paper presents an Optimal Power Flow (OPF) algorithm using Interior Point Method (IPM) to swiftly and precisely perform the five minute dispatch. This newly suggested methodology is based on Affine Scailing Interior Point Method (AS IPM), which is favorable for large-scale problems involving many constraints. It is also eligible for OPF problems in order to improve the calculation speed and the preciseness of its resultant solutions. Lastly, this paper provides a relevant case study to confirm the efficiency of the proposed methodology.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 추계학술대회 논문집 전력기술부문
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• pp.156-158
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• 2005

This paper presents an Optimal Power Flow (OPF) algorithm using Interior Point Method (IPM) to swiftly and precisely perform the five minute dispatch. This newly suggested methodology is based on Affine Sealing Interior Point Method (AS IPM), which is favorable for large-scale problems involving many constraints. It is also eligible for OPF problems in order to improve the calculation speed and the preciseness of its resultant solutions. Big-M Method is also used to improve the solution stability. Finally, this paper provides a relevant case study to confirm the efficiency of the proposed methodology.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 A
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• pp.366-368
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• 2002

This paper presents a technique that can obtain an optimal solution for the Security-Constrained Economic Dispatch (SCED) problems using the Interior Point Method (IPM) while taking into account of the power flow constraints. The SCED equations are formulated by using only the real power flow equations from the optimal power flow. Then an algorithm is presented that can linearize the SCED equations based on the relationships among generation real power outputs, loads, and transmission losses to obtain the optimal solutions by applying the linear programming (LP) technique. Finally, the application of the Primal Interior Point Method (PIPM) for solving the optimization problem based on the proposed linearized objective function is presented. The results are compared with the Simplex Method and the Promising results ard obtained.

• East Asian mathematical journal
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• 제29권3호
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• pp.279-292
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• 2013

It is well known that each kernel function defines a primal-dual interior-point method(IPM). Most of polynomial-time interior-point algorithms for linear optimization(LO) are based on the logarithmic kernel function([2, 11]). In this paper we define a new eligible kernel function and propose a new search direction and proximity function based on this function for LO problems. We show that the new algorithm has ${\mathcal{O}}((log\;p){\sqrt{n}}\;log\;n\;log\;{\frac{n}{\epsilon}})$ and ${\mathcal{O}}((q\;log\;p)^{\frac{3}{2}}{\sqrt{n}}\;log\;{\frac{n}{\epsilon}})$ iteration bound for large- and small-update methods, respectively. These are currently the best known complexity results.