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IEEE EUROCON

作者： Perica Ilak Slavko Krajcar Ivan Rajsl Marko Delimar Department of Energy and Power Systems University of Zagreb Faculty of Electrical Engineering and Computing

ISBN: (纸本)9781467322331

Water is scarce resource with uncertain availability. Hence finding an optimal production schedule for hydro producer is usually a complex task and it is necessary to carefully balance the timing of water use. This paper addresses the self-scheduling problem for a price-taker hydro producer. The goal is maximizing the profit of a hydro producer through participating in the day-ahead energy and ancillary service markets. The spinning reserve and regulation market are considered as ancillary service markets. The self-scheduling problem of hydro producer is formulated and solved as a mixed integer linear programming problem. Model is deterministic and three-dimensional relationship between the power produced, the water discharged, and the head of associated reservoir is accounted. Real hydropower system Vinodol is considered.

关键词： Hydroelectric producer Short-term planning Day-ahead auction market Ancillary services Head dependent power output mixed integer linear programming

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linearization method for the nonlinear factors of cascaded hydropower system

Linearization method for the nonlinear factors of cascaded h...

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Chinese Control Conference (CCC)

作者： Jiangtao Jia Zhi Feng The Electronic and Information Engineering College Xi'an Polytechnic University 710048 China

With the developments in linear programming code, a mixed integer linear programming (MILP)-based approaches have started to attract more attention in the word, some new linearization methods have been proposed. In this paper, MILP formulation of short-term scheduling for cascaded plants with pumped-storage units is established, for the nonlinear factors such as nonlinear hydroelectric production function, the characteristics of pumped-storage units, minimum/maximum down/up time of hydro units, etc. A new practical and systematic linearization approach is proposed. Some integer variables are introduced such that the problem is formulated as MILP. Numerical testing results show that the MILP formulation given in this paper is efficient and effective.

关键词： Power systems Electronic mail Educational institutions mixed integer linear programming Production Hydroelectric power generation Abstracts

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A Modeling Framework for Model Predictive Scheduling Using Switching Max-Plus linear Models

A Modeling Framework for Model Predictive Scheduling Using S...

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IEEE Annual Conference on Decision and Control

作者： Ton J.J. van den Boom Gabriel Delgado Lopes Bart De Schutter Delft University of Technology Delft Center for Systems and Control Delft The Netherlands

ISBN: (纸本)9781467357159

In this paper we discuss a modeling framework for model predictive scheduling of a class of semi-cyclic discrete event systems that can be described by switching max-plus linear models. We study the structure of the system matrices and derive how routing, ordering, and synchronization can be manipulated by a set of control variables. In addition, we show that this leads to a system matrix that is linear in the control variables. We define the model predictive scheduling design problem to optimize the schedule, and we show that the problem can be recast as a mixed integer linear programming (MILP) problem.

关键词： linear models control variable Predictive mixed integer linear programming switching Frameworks Modeling

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Tight and compact MILP formulation of start-up and shut-down ramping in unit commitment

Tight and compact MILP formulation of start-up and shut-down...

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IEEE General Meeting Power& Energy Society

作者： Germán Morales-España Jesus M. Latorre Andres Ramos Electric Power Systems KTH Royal Institute of Technology Institute for Research in Technology (IIT) Universidad Pontificia Comillas

Summary form only given. This paper presents a mixed-integer linear programming (MILP) formulation of start-up (SU) and shut-down (SD) power trajectories of thermal units. Multiple SU power-trajectories and costs are modeled according to how long the unit has been offline. The proposed formulation significantly reduces the computational burden in comparison with others commonly found in the literature. This is because the formulation is 1) tighter, i.e., the relaxed solution is nearer to the optimal integer solution; and 2) more compact, i.e., it needs fewer constraints, variables and nonzero elements in the constraint matrix. For illustration, the self-unit commitment problem faced by a thermal unit is employed. We provide computational results comparing the proposed formulation with others found in the literature.

关键词： Decision support systems Power systems mixed integer linear programming Trajectory Computational modeling

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Specialized Genetic Algorithm to Solve the Electrical Distribution System Expansion Planning

Specialized Genetic Algorithm to Solve the Electrical Distri...

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IEEE Power and Energy Society General Meeting

作者： Vera Camargo Marina Lavorato Rubén Romero Department of Mathematics of Sinop Mato Grosso State University Sinop – MT Brazil Faculty of Engineering of Ilha Solteira Paulista State University Ilha Solteira - SP Brazil

ISBN: (纸本)9781479913022

A specialized genetic algorithm with a adaptation of Chu-Beasley algorithm is presented in this paper to solve the electrical distribution distribution system expansion planning (DSP) problem modeled by a mixed integer nonlinear programming problem. The specialized genetic algorithm proposed in this paper starting from a initial population where all elements have a radial topology found using a heuristic algorithm and after the selection and mutation operations must also go through a local improvement in order to make the proposed solution in a feasible solution, if necessary, with respect to operational constraints. The DSP problem presented in this paper consider the circuit construction/recondutoring for different types of conductors and the substation construct/reinforcement. To evaluate the quality of the proposed methodology were used three different test systems found in the literature, 23, 54 and 136 buses systems.

关键词： Distribution network planning genetic algorithm mixed integer nonlinear programming power systems optimization. power distribution planning Genetic Algorithm (GA) Electricity Distribution Systems system optimization expansion plan mixed integer linear programming power system expansion planning Feasible Solution

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Optimal Branch Exchange for Feeder Reconfiguration in Distribution Networks

Optimal Branch Exchange for Feeder Reconfiguration in Distri...

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IEEE Annual Conference on Decision and Control

作者： Qiuyu Peng Steven H. Low Electrical Engineering Department California Institute of Technology Pasadena CA 91125 USA Computing and Mathematical Sciences and the Electrical Engineering Departments California Institute of Technology Pasadena CA 91125 USA

ISBN: (纸本)9781467357159

The feeder reconfiguration problem chooses the on/off status of the switches in a distribution network in order to minimize a certain cost such as power loss. It is a mixed integer nonlinear program and hence hard to solve. A popular heuristic search consists of repeated application of branch exchange, where some loads are transferred from one feeder to another feeder while maintaining the radial structure of the network, until no load transfer can further reduce the cost. Optimizing each branch exchange step is itself a mixed integer nonlinear program. In this paper we propose an efficient algorithm for optimizing a branch exchange step. It uses an AC power flow model and is based on the recently developed convex relaxation of optimal power flow. We provide a bound on the gap between the optimal cost and that of our solution. We prove that our algorithm is optimal when the voltage magnitudes are the same at all buses. We illustrate the effectiveness of our algorithm through the simulation of real-world distribution feeders.

关键词： branch exchange Power grids voltage magnitude Reconfiguration mixed integer linear programming Nonlinear programming optimal load flow Load transfer power loss efficient algorithm

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A linear reformulation of Boolean optimization problems and structure identification of gene regulation networks

A linear reformulation of Boolean optimization problems and ...

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IEEE Annual Conference on Decision and Control

作者： Christian Breindl Madalena Chaves Frank Allgower Institute for Systems Theory and Automatic Control University of Stuttgart Pfaffenwaldring 9 70550 Stuttgart Germany BIOCORE INRIA 2004 Route des Lucioles BP 93 06902 Sophia Antipolis France

ISBN: (纸本)9781467357159

We consider the problem of estimating Boolean models of gene regulation networks from few and noisy measurements. To this end, we use a representation of Boolean functions as multi-affine polynomials, leading to a reformulation of the estimation problem as mixed integer linear program. We then show that the integer constraints can be omitted which improves existing results and reduces the required computing time drastically. Also certain properties of Boolean functions such as unateness or the canalizing property can be included in the linear formulation. The benefits of this reformulation are demonstrated with the help of a large Boolean model of the network of the segment polarity genes in Drosophila melanogaster.

关键词： Boolean functions Gene regulation mixed integer linear programming Drosophila melanogaster Network

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Batch versus cyclic scheduling of flexible flow shops by mixed-integer programming

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2012年第18期50卷 5017-5034页

作者： Sawik, Tadeusz AGH Univ Sci & Technol Dept Operat Res & Informat Technol PL-30059 Krakow Poland

New mixed-integer programming models are proposed for deterministic batch or cyclic scheduling in flow shops with parallel machines and finite in-process buffers. Models for scheduling with all machines continuously available for processing throughout the entire scheduling horizon as well as for scheduling with an arbitrary pattern of machine availability due to pre-scheduled downtime events are provided. Numerical examples modelled after real-world flexible flow shop scheduling in electronics manufacturing are presented, and to compare the batch and cyclic schedules with continuous or with limited machine availability, results of computational experiments are reported.

关键词： flow shop scheduling mixed integer linear programming batch scheduling cyclic scheduling

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Simultaneous design and scheduling of a semicontinuous/batch plant for ethanol and derivatives production

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COMPUTERS & CHEMICAL ENGINEERING 2012年第1期36卷 342-357页

作者： Fumero, Yanina Montagna, Jorge M. Corsano, Gabriela INGAR Inst Desarrollo & Diseno CONICET UTN Santa Fe Argentina Univ Tecnol Nacl Fac Reg Santa Fe CIDISI Santa Fe Argentina

The interest on renewable fuels has greatly increased in the last years. Particularly, ethanol production arises as a good solution to many current economic-environmental problems. Yeast production from the ethanol residuals constitutes a sustainable alternative. Usually, this kind of plants is designed using single product campaigns. However, since yeast degradation is fast and a continuous supply must be assured, the mixed product campaign policy is the most appropriate. Besides, a stable context can be assumed to justify this approach that takes advantage of the special structure of the plant. Therefore, in this paper, a mixed integer linear programming model is formulated for simultaneous design and scheduling of a semicontinuous/batch plant for ethanol and derivatives production. The optimal plant configuration, unit sizes, number of batches of each product in the campaign and its sequencing is obtained in order to fulfill the ethanol and yeast demands minimizing the investment cost. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Batch/semicontinuous plant design Scheduling Ethanol and yeast productions mixed integer linear programming

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Path Planning for UAVs Under Communication Constraints Using SPLAT! and MILP

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JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS 2012年第1-4期65卷 265-282页

作者： Grotli, Esten Ingar Johansen, Tor Arne Dept Engn Cybernet N-7491 Trondheim Norway

We will in this paper address the problem of offline path planning for Unmanned Aerial Vehicles (UAVs). Our goal is to find paths that meet mission objectives, are safe with respect to collision and grounding, fuel efficient and satisfy criteria for communication. Due to the many nonconvex constraints of the problem, mixed integer linear programming (MILP) will be used in finding the path. Approximate communication constraints and terrain avoidance constraints are used in the MILP formulation. To achieve more accurate prediction of the ability to communicate, the path is then analyzed in the radio propagation toolbox SPLAT!, and if the UAVs are not able to communicate according to design criteria for bandwidth, constraints are modified in the optimization problem in an iterative manner. The approach is exemplified with the following setup: The path of two UAVs are planned so they can serve as relay nodes between a target without line of sight to the base station.

关键词： Path planning mixed integer linear programming Communication constraints Unmanned aerial vehicles

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