• 제목/요약/키워드: SQP(Sequential Quadratic Programming)

검색결과 110건 처리시간 0.037초

윈도우환경을 기반으로 한 최적전력조류 프로그램 팩키지 개발 (Windows Based Programming for Optimal Power Flow Analysis)

  • 김규호;이상봉;이재규;유석구
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2001년도 추계학술대회 논문집 전력기술부문
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    • pp.239-242
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    • 2001
  • This paper presents a windows program package for solving security constrained OPF in interconnected power systems, which is based on the combined application of evolutionary programming(EP) and sequential quadratic programming(SQP). The objective functions are the minimization of generation fuel costs and system power losses. The control variables are the active power of the generating units, the voltage magnitude of the generator, transformer tap settings and SVC setting. The state variables are the bus voltage magnitude, the reactive power of the generating unit, line flows and the tie line flow. In OPF considering security, the outages are selected by contingency ranking method. The resulting optimal operating point has to be feasible after outages such as any single line outage(respect of voltage magnitude, reactive power generation and power flow limits). The OPF package proposed is applied to 10 machines 39 buses model system.

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병렬유전알고리즘을 응용한 대규모 전력계통의 최적 부하배분 (Optimal Economic Load Dispatch using Parallel Genetic Algorithms in Large Scale Power Systems)

  • 김태균;김규호;유석구
    • 대한전기학회논문지:전력기술부문A
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    • 제48권4호
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    • pp.388-394
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    • 1999
  • This paper is concerned with an application of Parallel Genetic Algorithms(PGA) to optimal econmic load dispatch(ELD) in power systems. The ELD problem is to minimize the total generation fuel cost of power outputs for all generating units while satisfying load balancing constraints. Genetic Algorithms(GA) is a good candidate for effective parallelization because of their inherent principle of evolving in parallel a population of individuals. Each individual of a population evaluates the fitness function without data exchanges between individuals. In application of the parallel processing to GA, it is possible to use Single Instruction stream, Multiple Data stream(SIMD), a kind of parallel system. The architecture of SIMD system need not data communications between processors assigned. The proposed ELD problem with C code is implemented by SIMSCRIPT language for parallel processing which is a powerfrul, free-from and versatile computer simulation programming language. The proposed algorithms has been tested for 38 units system and has been compared with Sequential Quadratic programming(SQP).

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비선형 최적화 기법에 의한 최소 조파저항 선형 생성 (Hull Form Generation of Minimum Wave Resistance by a Nonlinear Optimization Method)

  • 김희정;전호환
    • 대한조선학회논문집
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    • 제37권4호
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    • pp.11-18
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    • 2000
  • 본 논문은 조파저항 성능 평가법을 비선형 계획법에 적용해서 선수 형상의 최적화에 응용한 연구결과이다. 조파저항은 비점성 포텐셜 유동의 가정으로 랜킨 소오스법(Rankine source method)을 이용하여 계산하였고 최적화 기법으로는 SQP(Sequential Quadratic Programming)법을 이용하였다. 선수형상의 표현과 변경은 스플라인(spline)함수를 이용하였으며 본 방법에 의하여 조파저항이 최소가 되는 선수형상의 결정이 가능하였다. 또한 마찰저항공식과 경험식으로 주어지는 형상영향계수(from factor)를 고려한 점성저항을 첨가하여 총 저항이 최소가 되는 선수 형상도 도출하여 서로 비교하였다.

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SQP법을 사용한 복합재 조류력 발전용 블레이드의 스파 캡에 대한 두께 최적화 (Thickness Optimization for Spar Cap of Composite Tidal Current Turbine Blade using SQP Method)

  • 차명찬;김상우;정민수;이인;유승재;박천진
    • Composites Research
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    • 제26권4호
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    • pp.207-212
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    • 2013
  • 본 연구에서는 유리강화섬유폴리머(GFRP)와 탄소강화섬유폴리머(CFRP)로 적층된 조류력 블레이드의 스파 캡(Spar cap)을 대상으로 끝단 처짐의 제한에 따른 단방향(UD) GFRP의 적층 두께를 최적화 하였다. 또한 도출된 적층 두께에 따른 블레이드 내부의 응력의 변화와 블레이드의 재료비용을 확인하였다. 비선형 최적화에 뛰어난 순차 이차방정식 프로그래밍(SQP) 알고리즘을 사용하였고, 목적함수를 계산하기 위하여 상용 유한요소해석 프로그램인 Abaqus/Standard와 연계하였다. UD CFRP의 적층 두께가 9 mm로 제한된 경우, 끝단 처짐이 감소함에 따라 UD GFRP의 적층 두께가 증가하였다. 즉, 최적화된 스파 캡의 무게는 최대 96.2% 증가였으며 최대 인장응력은 최대 24.6% 감소하였다. 끝단 처짐이 126.83 mm로 제한된 경우, UD CFRP의 적층 두께가 줄어듦에 따라 UD GFRP의 적층 두께가 증가하였다. 이로 인하여 무게는 최대 40.1% 증가하였지만 재료비용은 최대 16.97% 감소하였다. 본 연구에서 제시한 블레이드 스파 캡의 최적화된 두께를 바탕으로 조류력 블레이드의 무게, 내부의 최대 응력과 재료비용의 상관관계를 제시하였다.

A Globally Stabilizing Model Predictive Controller for Neutrally Stable Linear Systems with Input Constraints

  • Yoon, Tae-Woong;Kim, Jung-Su;Jadbabaie, Ali;Persis, Claudio De
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.1901-1904
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    • 2003
  • MPC or model predictive control is representative of control methods which are able to handle physical constraints. Closed-loop stability can therefore be ensured only locally in the presence of constraints of this type. However, if the system is neutrally stable, and if the constraints are imposed only on the input, global aymptotic stability can be obtained; until recently, use of infinite horizons was thought to be inevitable in this case. A globally stabilizing finite-horizon MPC has lately been suggested for neutrally stable continuous-time systems using a non-quadratic terminal cost which consists of cubic as well as quadratic functions of the state. The idea originates from the so-called small gain control, where the global stability is proven using a non-quadratic Lyapunov function. The newly developed finite-horizon MPC employs the same form of Lyapunov function as the terminal cost, thereby leading to global asymptotic stability. A discrete-time version of this finite-horizon MPC is presented here. The proposed MPC algorithm is also coded using an SQP (Sequential Quadratic Programming) algorithm, and simulation results are given to show the effectiveness of the method.

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크리깅 메타모델에 의한 철도차량 현수장치 최적설계 (Optimization of a Train Suspension using Kriging Meta-model)

  • 이광기;이태희;박찬경
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2001년도 춘계학술대회논문집C
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    • pp.339-344
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    • 2001
  • In recent engineering, the designer has become more and more dependent on the computer simulations such as FEM (Finite Element Method) and BEM (Boundary Element Method). In order to optimize such implicit models more efficiently and reliably, the meta-modeling technique has been developed for solving such a complex problems combined with the DACE (Design and Analysis of Computer Experiments). It is widely used for exploring the engineer's design space and for building meta-models in order to facilitate an effective solution of multi-objective and multi-disciplinary optimization problems. Optimization of a train suspension is performed according to the minimization of forty-six responses that represent ten ride comforts, twelve derailment quotients, twelve unloading ratios, and twelve stabilities by using the Kriging meta-model of a train suspension. After each Kriging meta-model is constructed, multi-objective optimal solutions are achieved by using a nonlinear programming method called SQP (Sequential Quadratic Programming).

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연계계통에서 안전도제약을 고려한 최적전력조류 (Optimal Power Flow considering Security in Interconnected Power Systems)

  • 김규호;이재규;이상봉;유석구
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2001년도 하계학술대회 논문집 A
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    • pp.194-196
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    • 2001
  • This paper presents a hybrid algorithm for solving security constrained OPF in interconnected power systems, which is based on the combined application of evolutionary programming (EP) and sequential quadratic programming (SQP). The objective functions are the minimization of generation fuel costs and system power losses. In OPF considering security, the outages are selected by contingency ranking method. The control variables are the active power of the generating units, the voltage magnitude of the generator, transformer tap settings and SVC setting. The state variables are the bus voltage magnitude, the reactive power of the generating unit, line flows and the tie line flow. The method proposed is applied to the modified IEEE 14buses model system.

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진화연산을 이용한 대규모 전력계통의 최적화 방안 (An Optimization Method using Evolutionary Computation in Large Scale Power Systems)

  • 유석구;박창주;김규호;이재규
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1996년도 하계학술대회 논문집 B
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    • pp.714-716
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    • 1996
  • This paper presents an optimization method for optimal reactive power dispatch which minimizes real power loss and improves voltage profile of power systems using evolutionary computation such as genetic algorithms(GAs), evolutionary programming(EP). and evolution strategy(ES). Many conventional methods to this problem have been proposed in the past, but most these approaches have the common defect of being caught to a local minimum solution. Recently, global search methods such as GAs, EP, and ES are introduced. The proposed methods were applied to the IEEE 30-bus system. Each simulation result, compared with that obtained by using a conventional gradient-based optimization method, Sequential Quadratic Programming (SQP), shows the possibility of applications of evolutionary computation to large scale power systems.

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인증규정을 고려한 KLA-100항공기 고양력장치 최적화 설계 (Flap Design Optimization for KLA-100 Aircraft in compliance with Airworthiness Certification)

  • 박진환;;;김상호;이재우
    • 한국항공우주학회지
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    • 제41권8호
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    • pp.649-656
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    • 2013
  • 고양력장치는 항공기의 이착륙 및 실속성능에 큰 영향을 미친다. 그러므로, 이 논문에서는 주어진 2차원 플랩 형상에 대하여 가장 최적화된 플랩 위치와 변위각을 얻는 슬롯티드 플랩 설계 최적화 프로세스을 제안하였다. 플랩 변위각 및 Gap, Overlap을 양력을 증가시키는 주요 변수로 생각하였고, 정확한 해석결과를 위해 공력해석 소프트웨어로 ANSYS Fluent 13.0.0$^{(R)}$을 사용하였다. 최적화된 형상은 SQP(Sequential Quadratic Programming) 알고리즘을 통해 도출됐으며, 최적화된 플랩과 함께 ADSP(Aircraft Design Synthesis Program) in-house 성능해석 코드를 사용하여 항공기의 성능을 시험하였고, 이착륙 거리, 실속속도 등의 성능변수들이 KAS-VLA 인증규정을 만족하는 결과를 얻었다.

Optimal Particle Swarm Based Placement and Sizing of Static Synchronous Series Compensator to Maximize Social Welfare

  • Hajforoosh, Somayeh;Nabavi, Seyed M.H.;Masoum, Mohammad A.S.
    • Journal of Electrical Engineering and Technology
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    • 제7권4호
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    • pp.501-512
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    • 2012
  • Social welfare maximization in a double-sided auction market is performed by implementing an aggregation-based particle swarm optimization (CAPSO) algorithm for optimal placement and sizing of one Static Synchronous Series Compensator (SSSC) device. Dallied simulation results (without/with line flow constraints and without/with SSSC) are generated to demonstrate the impact of SSSC on the congestion levels of the modified IEEE 14-bus test system. The proposed CAPSO algorithm employs conventional quadratic smooth and augmented quadratic nonsmooth generator cost curves with sine components to improve the accurate of the model by incorporating the valve loading effects. CAPSO also employs quadratic smooth consumer benefit functions. The proposed approach relies on particle swarm optimization to capture the near-optimal GenCos and DisCos, as well as the location and rating of SSSC while the Newton based load flow solution minimizes the mismatch equations. Simulation results of the proposed CAPSO algorithm are compared to solutions obtained by sequential quadratic programming (SQP) and a recently implemented Fuzzy based genetic algorithm (Fuzzy-GA). The main contributions are inclusion of customer benefit in the congestion management objective function, consideration of nonsmooth generator characteristics and the utilization of a coordinated aggregation-based PSO for locating/sizing of SSSC.