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Probabilistic reactive power procurement in hybrid electricity markets with uncertain loads

ELECTRIC POWER SYSTEMS RESEARCH 2012年第1期82卷 68-80页

作者： Kargarian, Amin Raoofat, Mahdi Mohammadi, Mohammad Islamic Azad Univ Safashahr Branch Dept Elect & Comp Engn Safashahr Iran Shiraz Univ Sch Elect & Comp Engn Dept Power & Control Eng Shiraz Iran

This paper presents a novel probabilistic algorithm for optimal reactive power provision in hybrid electricity markets. The proposed algorithm is a six-stage multiobjective nonlinear constrained optimization problem which takes into account load forecasting inaccuracies. Considering a set of probable forecasted loads, a three-component expected total market payment function is suggested being minimized as cost function of the first stage. Besides economic issues, expected voltage security margin, deviation from multilateral and pool based energy transactions, deviation from spinning reserve contracts, having adequate local reactive power reserve in each voltage control area of the system and transmission congestion probability are well thought out in stages 2-5 as technical aspects of the market. Finally, in the last stage, using different weighting factors to compromise between all objects, a probabilistic multiobjective function is presented to find the best reactive power market schedule. The proposed algorithm is applied on IEEE 24-bus test system. As a benchmark, Monte Carlo Simulation method is utilized to simulate the market of given period of time to evaluate results of the proposed algorithm, and satisfactory results are achieved. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Hybrid electricity markets Local reactive power reserve Monte Carlo Simulation multiobjective programming Probabilistic reactive power market System security

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Pseudoinvexity, optimality conditions and efficiency in multiobjective problems;duality

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NONLINEAR ANALYSIS-THEORY METHODS & APPLICATIONS 2008年第1期68卷 24-34页

作者： Arana-Jimenez, A. Rufian-Lizana, A. Osuna-Gomez, R. Ruiz-Garzon, G. Univ Cadiz Fac Ciencias Dept Estadistica Invest Operativa E-11510 Puerto Real Spain IES San Jose Del Valle Cadiz 11580 Spain Univ Seville Fac Matemat Dept Estadistica Invest Operativa Seville Spain

In this paper, we establish characterizations for efficient solutions to multiobjective programming problems, which generalize the characterization of established results for optimal solutions to scalar programming problems. So, we prove that in order for Kuhn-Tucker points to be efficient solutions it is necessary and sufficient that the multiobjective problem functions belong to a new class of functions, which we introduce. Similarly, we obtain characterizations for efficient solutions by using Fritz-John optimality conditions. Some examples are proposed to illustrate these classes of functions and optimality results. We study the dual problem and establish weak, strong and converse duality results. (C) 2007 Published by Elsevier Ltd.

关键词： multiobjective programming invexity pseudoinvexity Kuhn-Tucker and Fritz-John optimality conditions efficient solutions

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Improving fleet utilization for carriers by interval scheduling

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2012年第1期218卷 261-269页

作者： Lee, Soonhui Turner, Jonathan Daskin, Mark S. Homem-de-Mello, Tito Smilowitz, Karen Northwestern Univ Dept Ind Engn & Management Sci Evanston IL 60208 USA Univ Michigan Dept Ind & Operat Engn Ann Arbor MI 48109 USA Univ Adolfo Ibanez Sch Business Santiago Chile

Carriers are under increasing pressure to offset rising fuel charges with cost cutting or revenue generating schemes. One opportunity for cost reduction lies in asset management. This paper presents resource allocation scheduling models that can be used to assign truck loads to delivery times and trucks when delivery times are flexible. The paper makes two main contributions. First, we formulate the problem as a multi-objective optimization model - minimizing the number of trucks needed as well as the costs associated with tardiness or earliness - and demonstrate how improvements in fleet usage translate into savings which carriers can use as incentives to promote flexible delivery times for customers. Second, we show that a two-phase model with a polynomial algorithm in the second phase is able to produce optimal schedules in a reasonable time. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Multi-machine scheduling Flexible delivery times Fleet size reduction Penalty costs multiobjective programming

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Inventory management under uncertainty: A military application

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COMPUTERS & INDUSTRIAL ENGINEERING 2016年 96卷 96-107页

作者： Bean, Wilna L. Joubert, Johan W. Luhandjula, M. K. Univ Pretoria Dept Ind & Syst Engn ZA-0002 Pretoria South Africa CSIR Built Environm Transport Syst & Operat POB 395 ZA-0001 Pretoria South Africa Univ S Africa Dept Decis Sci POB 392 ZA-0003 Pretoria South Africa

Inventory management under uncertainty is a widely investigated field and many different types of inventory models have been used to address inventory problems in practice. However, a look at the literature reveals that few papers are devoted to inventory planning and management in environments characterised by uncertainty resulting from extreme events. In this paper a fuzzy-stochastic multi objective modelling approach is used to address the problem of managing inventory in an environment characterised by uncertainty. The model is applied specifically to the military environment and determines the required stock level for a single item, based on three different scenarios. A numerical example is provided for the sake of illustration and the reliability of the model tested through simulation. The results are compared with those obtained from the well known (r, Q) and (s, S) inventory models in the literature. This comparison showed that the hybrid model presented in this paper is more reliable in extreme scenarios. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Inventory management Fuzzy-stochastic programming multiobjective programming Military stock Uncertainty

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Fast Model Predictive Control for Multilevel Cascaded H-Bridge STATCOM With Polynomial Computation Time

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2016年第8期63卷 5231-5243页

作者： Zhang, Yonglei Wu, Xiaojie Yuan, Xibo Wang, Yingjie Dai, Peng China Univ Min & Technol Sch Informat & Elect Engn Xuzhou 221116 Peoples R China Univ Bristol Dept Elect & Elect Engn Bristol BS8 1UB Avon England

To solve the issue of exponentially increasing computational burden of finite control set model predictive control (FCS-MPC) for multilevel converters, a fast MPC scheme for multilevel cascaded H-bridge STATCOM is presented. The proposed approach consists of three steps. First, with the partially stratified optimization approach, the multiobjective programming of MPC is divided into two suboptimization problems, i.e., current-control MPC and voltage-balancing MPC. Second, a dynamic programming algorithm is proposed for the optimization of current-control MPC. Third, a mixed algorithm, which combines dynamic programming and greedy algorithm (0-1 programing), is proposed to select the optimal switching combination from all the redundant switching combinations for the voltage balancing MPC achieving a global optimization. Through the analysis of the time complexity, with the proposed scheme, the total computation of FCS-MPC can be reduced to polynomial time from exponential time. The proposed approaches will not deteriorate the control performance. The control performance is validated by simulation results and the effectiveness is further demonstrated by implementing the algorithm on a low-cost DSP (TMS320F28335) in real time.

关键词： Cascaded H-bridge (CHB) static synchronous compensator (STATCOM) dynamic programming model predictive control (MPC) multiobjective programming partially stratified optimization

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ANALYSIS OF MULTICRITERIA DECISION AID IN EUROPE

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 1986年第2期25卷 160-168页

作者： VINCKE, P UNIV LIBRE BRUXELLES CP 210 BLVD TRIOMPHE B-1050 BRUSSELS BELGIUM

As asked by the editors of this special issue, the purpose of this paper is to analyze the existing literature on multicriteria decision-aid, to bring out the successes and the difficulties of this field and to propose some ways of research. Furthermore, as mentioned in the title, this analysis is essentially devoted to the research in Europe, even if some comments are concerned with the American literature. This paper is not a survey of all what has been done in multicriteria decision-aid, but we have tried to approach its main aspects. [ABSTRACT FROM AUTHOR]

关键词： multiattribute utility theory Multicriteria decision aid multiobjective programming outranking methods

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multiobjective transportation problem with interval cost, source and destination parameters

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 1999年第1期117卷 100-112页

作者： Das, SK Goswami, A Alam, SS Indian Inst Technol Dept Math Kharagpur 721302 W Bengal India

In this paper,. we focus on the solution procedure of the multiobjective transportation problem (MOTP) where the cost coefficients of the objective functions, and the source and destination parameters have been expressed as interval values by the decision maker. This problem has been transformed into a classical MOTP where to minimize the interval objective function, the order relations that represent the decision maker's preference between interval profits have been defined by the right limit, left limit, centre, and half-width of an interval. The constraints with interval source and destination parameters have been converted into deterministic ones. Finally, the equivalent transformed problem has been solved by fuzzy programming technique. Numerical examples have been provided to illustrate the solution procedure for three possible cases of the original problem. (C) 1999 Elsevier Science B.V. All rights reserved.

关键词： multiobjective programming transportation problem interval number fuzzy programming

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MATHEMATICAL programming PROBLEMS WITH SEVERAL FUZZY OBJECTIVE FUNCTIONS

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INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS 2013年第sup1期21卷 51-62页

作者： Kalonda, Luhandjula Monga Joseph, Rangoaga Moeti Univ S Africa Dept Decis Sci ZA-0003 Unisa South Africa

In this paper we propose an approach for multiobjective programming problems with fuzzy number coefficients. The main idea behind our approach is to approximate involved fuzzy numbers by their respective nearest interval approximation counterparts. An algorithm that returns a nearest interval approximation to a given fuzzy number, plays a pivotal role in the proposed method. Our approach contrasts markedly with those based on deffuzification operators which replace a fuzzy set by a single real number leading to a loss of many important information. A numerical example is also provided for the sake of illustration.

关键词： multiobjective programming fuzzy numbers nearest interval approximation

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Proper Efficiency and Tradeoffs in Multiple Criteria and Stochastic Optimization

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MATHEMATICS OF OPERATIONS RESEARCH 2017年第1期42卷 119-134页

作者： Engau, Alexander Univ Colorado Denver Math & Stat Sci Denver CO 80202 USA

The mathematical equivalence between linear scalarizations in multiobjective programming and expected- value functions in stochastic optimization suggests to investigate and establish further conceptual analogies between these two areas. In this paper, we focus on the notion of proper efficiency that allows us to provide a first comprehensive analysis of solution and scenario tradeoffs in stochastic optimization. In generalization of two standard characterizations of properly efficient solutions using weighted sums and augmented weighted Tchebycheff norms for finitely many criteria, we show that these results are generally false for infinitely many criteria. In particular, these observations motivate a slightly modified definition to prove that expected- value optimization over continuous random variables still yields bounded tradeoffs almost everywhere in general. Further consequences and practical implications of these results for decision-making under uncertainty and its related theory and methodology of multiple criteria, stochastic and robust optimization are discussed.

关键词： proper efficiency tradeoffs multicriteria optimization multiobjective programming stochastic optimization stochastic programming robust optimization linear scalarization weighted sum method augmented Tchebycheff norm expected value function decision making under uncertainty

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A NOTE ON FIRST-ORDER SUFFICIENT OPTIMALITY CONDITIONS FOR PARETO PROBLEMS

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NUMERICAL FUNCTIONAL ANALYSIS AND OPTIMIZATION 2008年第9-10期29卷 1108-1113页

作者： Giorgi, Giorgio Jimenez, Bienvenido Novo, Vicente Univ Nacl Educ Distancia ETSI Ind Dept Matemat Aplicada E-28040 Madrid Spain Univ Pavia Fac Econ Dipartimento Ric Aziendali I-27100 Pavia Italy

We take into consideration the first-order sufficient conditions, established by Jimenez and Novo (Numer. Funct. Anal. Optim. 2002;23: 303-322) for strict local Pareto minima. We give here a more operative condition f... 详细信息

关键词： First-order sufficient optimality conditions multiobjective programming Strict local Pareto minimum

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