• 제목, 요약, 키워드: Chance constrained programming

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Dynamic Economic Dispatch for Microgrid Based on the Chance-Constrained Programming

  • Huang, Daizheng;Xie, Lingling;Wu, Zhihui
    • Journal of Electrical Engineering and Technology
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    • v.12 no.3
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    • pp.1064-1072
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    • 2017
  • The power of controlled generators in microgrids randomly fluctuate because of the stochastic volatility of the outputs of photovoltaic systems and wind turbines as well as the load demands. To address and dispatch these stochastic factors for daily operations, a dynamic economic dispatch model with the goal of minimizing the generation cost is established via chance-constrained programming. A Monte Carlo simulation combined with particle swarm optimization algorithm is employed to optimize the model. The simulation results show that both the objective function and constraint condition have been tightened and that the operation costs have increased. A higher stability of the system corresponds to the higher operation costs of controlled generators. These operation costs also increase along with the confidence levels for the objective function and constraints.

DUALITY FOR LINEAR CHANCE-CONSTRAINED OPTIMIZATION PROBLEMS

  • Bot, Radu Ioan;Lorenz, Nicole;Wanka, Gert
    • 대한수학회지
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    • v.47 no.1
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    • pp.17-28
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    • 2010
  • In this paper we deal with linear chance-constrained optimization problems, a class of problems which naturally arise in practical applications in finance, engineering, transportation and scheduling, where decisions are made in presence of uncertainty. After giving the deterministic equivalent formulation of a linear chance-constrained optimization problem we construct a conjugate dual problem to it. Then we provide for this primal-dual pair weak sufficient conditions which ensure strong duality. In this way we generalize some results recently given in the literature. We also apply the general duality scheme to a portfolio optimization problem, a fact that allows us to derive necessary and sufficient optimality conditions for it.

0 - 1 목표계획모형의 재구조화에 관한 연구-기회제약계획법(CCP)과 계층화 분석과정(AHP)의 결합 가능성을 중심으로- (A Study of the Reformulation of 0-1 Goal Programming)

  • 이영찬;민재형
    • 한국경영과학회:학술대회논문집
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    • pp.525-529
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    • 1996
  • Decision environments involve a high degree of uncertainty as well as multiple, conflicting goals. Although traditional goal programming offers a means of considering multiple, conflicting goals and arrives at a satisficing solution in a deterministic manner, its major drawback is that decision makers often specify aspiration level of each goal as a single number. To overcome the problem of setting aspiration levels, chance constrained programming can be incorporated into goal programming formulation so that sampling information can be utilized to describe uncertainty distribution. Another drawback of goal programming is that it does not provide a systematic approach to set priorities and trade-offs among conflicting goals. To overcome this weekness, the analytic hierarchy process(AHP) is used in the model. Also, most goal programming models in the literature are of a linear form, although some nonlinear models have been presented. Consideration of risk in technological coefficients and right hand sides, however, leads to nonlinear goal programming models, which require a linear approximation to be solved. In this paper, chance constrained reformulation with linear approximation is presented for a 0-1 goal programming problem whose technological coefficients and right hand sides are stochastic. The model is presented with a numerical example for the purpose of demonstration.

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확률제약조건계획법(確率制約條件計劃法)을 이용(利用)한 자본예산모형(資本豫算模型) (A New Chance-Constrained Programming Approach to Capital Budgeting)

  • 이주호
    • 대한산업공학회지
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    • v.6 no.2
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    • pp.21-29
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    • 1980
  • 본(本) 연구(硏究)는 투자안(投資案)들간의 상호관계(相互關係) 및 위험(危險)을 고려한 자본예산문제(資本豫算問題)를 다루고 있다. 기존(旣存)의 개발(開發)된 모형(模型)은 확률제약조건계획모형(確率制約條件計劃模型) 및 기대효용극대화모형(期待效用極大化模型)의 두 범주(範疇)로 구분(區分)될 수 있다. 전자의 경우 목적함수(目的凾數)가 다소 제약적(制約的)이며 위험(危險)을 직접적인 형태로 고려하지 않고 있는 반면에 후자는 기대효용(期待效用)에 대한 근사치(近似値)를 사용하기 때문에 투자결정(投資決定)이 최적화(最摘化)되지 못할 가능성이 있다. 본(本) 연구(硏究)는 목적함수(目的凾數)를 보다 일반적(一般的)인 형태로 수정(修正) 보완(補完)함으로써 현실적용성(現實適用性)을 높이고자 하였다. 해법절차(解法節次)로는, 자본예산문제(資本豫算問題)를 우선 비선형(非線型) 0-1 정수계획(整數計劃) 문제로 정식화(定式化)하고, 이를 선형(線型) 0-1 정수계획(整數計劃)문제로 변형(變形)하여 원문제(原問題)의 하한(下限)을 찾은 후 B&B 연산법(演算法)으로 원문제(原問題)의 최적해(最適解)를 구하고 있다.

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Support Vector Machine Based on Type-2 Fuzzy Training Samples

  • Ha, Ming-Hu;Huang, Jia-Ying;Yang, Yang;Wang, Chao
    • Industrial Engineering and Management Systems
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    • v.11 no.1
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    • pp.26-29
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    • 2012
  • In order to deal with the classification problems of type-2 fuzzy training samples on generalized credibility space. Firstly the type-2 fuzzy training samples are reduced to ordinary fuzzy samples by the mean reduction method. Secondly the definition of strong fuzzy linear separable data for type-2 fuzzy samples on generalized credibility space is introduced. Further, by utilizing fuzzy chance-constrained programming and classic support vector machine, a support vector machine based on type-2 fuzzy training samples and established on generalized credibility space is given. An example shows the efficiency of the support vector machine.

A New Solution for Stochastic Optimal Power Flow: Combining Limit Relaxation with Iterative Learning Control

  • Gong, Jinxia;Xie, Da;Jiang, Chuanwen;Zhang, Yanchi
    • Journal of Electrical Engineering and Technology
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    • v.9 no.1
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    • pp.80-89
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    • 2014
  • A stochastic optimal power flow (S-OPF) model considering uncertainties of load and wind power is developed based on chance constrained programming (CCP). The difficulties in solving the model are the nonlinearity and probabilistic constraints. In this paper, a limit relaxation approach and an iterative learning control (ILC) method are implemented to solve the S-OPF model indirectly. The limit relaxation approach narrows the solution space by introducing regulatory factors, according to the relationship between the constraint equations and the optimization variables. The regulatory factors are designed by ILC method to ensure the optimality of final solution under a predefined confidence level. The optimization algorithm for S-OPF is completed based on the combination of limit relaxation and ILC and tested on the IEEE 14-bus system.

확률제약 계획모형법을 이용한 농업용수의 경제적 가치 평가 (Valuation of Irrigation Water: A Chance-Constrained Programming Approach)

  • 권오상;이태호;허정회
    • 한국수자원학회논문집
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    • v.42 no.4
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    • pp.281-295
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    • 2009
  • 본고는 경제적 최적화모형인 확률제약 계획모형법을 이용하여, 농업용수 부존량 감소에 따른 농업이윤의 감소분을 계측하고 이를 통해 농업용수의 경제적 가치를 분석하고자 한다. 이를 위해 국가 전체 농업자원배분을 최적화 모형으로 구축하고, 농업용수를 포함하는 자원부존제약조건과, 각 상품의 가격이 형성되는 시장조건, 국제무역 및 관련정책변수의 영향들을 반영하고, 용수의 경우 그 이용량이 연도별로 불안정할 수 있다는 것까지 반영한다. 농업용수감소량이 농업부문 이윤에 미치는 영향을 시나리오를 주어 분석하면, 농업용수의 톤당 경제적 가치는 $303{\sim}1,093$원/$m^3$의 분포를 가지는 것으로 나타난다. 동일한 양의 용수량이 줄어들더라도 용수의 공급이 불안정할수록 경제적 가치 손실이 크며, 아울러 많은 양의 용수손실이 발생할수록 경제적 손실이 커 용수감소의 한계피해는 용수감소량의 증가 함수인 것으로 파악된다.

기존 농업용 저수지에서의 유효저수량의 평가 (Evaluation of the Effective Storage of Existing Agricultural Reservoir)

  • 안태진;조동호;이상호;최계윤;윤용남
    • 한국수자원학회논문집
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    • v.37 no.5
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    • pp.353-361
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    • 2004
  • 농업용 저수지의 유효저수량은 물수지 분석을 근거고 한 저수지 모의 운영을 통하여 결정하고 있다. 유역은 유출량에 관하여 고유한 특성을 갖고 있으므로 저수지에서 유효저수량의 결정은 유역으로부터의 유출량을 근거로 하는 것이 타당하다. 본 연구에서는 유역의 유출량을 근거로 한 추계학적 선형계획모형을 정립하고 저수지의 유효저수량을 분석하였다. 선형계획모형을 이용한 저수지 분석에 있어서 선형결정법칙은 Chance-constrained model과 함께 된 석년수와 관계없이 제약조건식을 줄이는데 기여한다. 경기도 안성시에 소재하고 있는 금광저수지를 대상저수지고 선정하여 유효저수량을 분석한 결과, 추계학적 선형계획모형에 의한 유효저수량은 물수지 분석에 의한 것 보다 크게 분석되었다. 본 연구에서 제시된 선형계획모형에 의하여 적정한 유효저수량을 결정하고, 저수지 모의운영을 통하여 결정된 유효저수량의 성능을 평가하는 것이 타당한 것으로 판단된다.

확률선형 계획법에 의한 최적 Var 배분 계뵉에 관한 연구(II) (Optimal Var allocation in System planning by Stochastic Linear Programming(II))

  • 송길영;이희영
    • 대한전기학회:학술대회논문집
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    • pp.191-193
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    • 1989
  • This paper presents a optimal Var allocation algorithm for minimizing power loss and improving voltage profile in a given system. In this paper, nodal input data is considered as Gaussian distribution with their mean value and their variance. A stochastic Linear Programming technique based on chance constrained method is applied to solve the probabilistic constraint. The test result in IEEE-14 Bus model system showes that the voltage distribution of load buses is improved and the power loss is more reduced than before Var allocation.

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확률 선형 계획법에 의한 최적 Var 배분 계획에 관한 연구 (Optimal Var Allocation in system planning by stochastic Linear Programming)

  • 송길영;이희영
    • 대한전기학회:학술대회논문집
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    • pp.863-865
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    • 1988
  • This paper presents a optimal Var allocation algorithm for minimizing transmission line losses and improving voltage profile in a given system. In this paper, nodal input data is considered as Gaussian distribution with their mean value and their variance. A Stocastic Linear programming technique based on chance constrained method is applied, to solve the var allocation problem with probabilistic constraint. The test result in 6-Bus Model system showes that the voltage distribution of load buses is improved and the power loss is more reduced than before var allocation.

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