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Application of Benders Decomposition to Transmission Expansion Planning with N-1 Security Constraints

IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING 2011年第2期6卷 127-133页

作者： Asadamongkol, Somphop Eua-arporn, Bundhit Chulalongkorn Univ Fac Engn Dept Elect Engn Bangkok 10330 Thailand

This paper proposes a methodology for solving a transmission expansion planning problem with N - 1 security constraints consideration. The problem is formulated using a disjunctive model solved by Benders decomposition. A local search procedure is applied to solve the master problem, i.e. investment problem. With this developed methodology, the computational time can be considerably reduced, especially for large system problems, and the global optimality of Bender decomposition can be preserved by solving the master problem in a complete search space for specified iteration numbers. The proposed methodology has been tested with the IEEE 24-bus system and the southern Brazilian system with satisfactory results. (C) 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

关键词： Benders decomposition disjunctive model mixed-integer linear programming transmission expansion planning

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Interval Uncertainty-Based Robust Optimization for Convex and Non-Convex Quadratic Programs with Applications in Network Infrastructure Planning

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NETWORKS & SPATIAL ECONOMICS 2011年第1期11卷 159-191页

作者： Li, Mian Gabriel, Steven A. Shim, Yohan Azarm, Shapour Univ Maryland Appl Math & Stat & Sci Computat Program College Pk MD 20742 USA Shanghai Jiao Tong Univ Univ Michigan Joint Inst Shanghai 200240 Peoples R China Univ Maryland Dept Civil & Environm Engn College Pk MD 20742 USA Univ Maryland Dept Mech Engn College Pk MD 20742 USA

Planning infrastructure networks such as roads, pipelines, waterways, power lines and telecommunication systems, require estimations on the future demand as well as other uncertain factors such as operating costs, degradation rates, or the like. When trying to construct infrastructure that is either optimal from a social welfare or profit perspective (depending on a public or private sector focus), typically researchers treat the uncertainties in the problem by using robust optimization methods. The goal of robust optimization is to find optimal solutions that are relatively insensitive to uncertain factors. This paper presents an efficient and tractable approach for finding robust optimum solutions to linear and, more importantly, quadratic programming problems with interval uncertainty using a worst case analysis. For linear, mixed-integer linear, and mixed-integer problems with quadratic objective and constraint functions, our robust formulations have the same complexity and tractability as their deterministic counterparts. Numerous examples with differing difficulties and complexities, especially with selected ones on network planning/operations problems, have been tested to demonstrate the viability of the proposed approach. The results show that the computational effort of the proposed approach, in terms of the number of function calls, for the robust problems is comparable to or even better than that of deterministic problems in some cases.

关键词： Robust optimization Interval uncertainty linear programming Quadratic programming mixed-integer linear programming mixed-integer quadratic programming

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Lifetime Maximization in Wireless Sensor Networks Using a Mobile Sink with Nonzero Traveling Time

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COMPUTER JOURNAL 2011年第12期54卷 1987-1999页

作者： Keskin, M. Emre Altinel, I. Kuban Aras, Necati Ersoy, Cem Bogazici Univ Dept Comp Engn Istanbul Turkey Bogazici Univ Dept Ind Engn Istanbul Turkey

It is a known phenomenon that in a wireless sensor network, sensors communicating directly with a sink deplete their energy faster than the others. As a result, the so-called neighboring sensors can die, disconnecting some of the sinks from the rest of the network, even though most of the sensors are still fully functional. One possible remedy is to balance the relaying load of the sensors using mobile sinks and controlling their mobility, which has attracted the interest of researchers. In this work, we extend the relevant literature by introducing two new mathematical programming models. They intend to maximize the network lifetime through the controlled mobility of a sink with nonzero travel times with and without limiting the number of hops by which the data originating from the sensors reach the sink. Both models allow more than one tour of the sink during the network lifetime and determine the optimal sink route and sojourn times. Since the models are computationally difficult to solve, we propose efficient heuristics methods to compute near-optimal solutions. On the basis of the computational results performed on randomly generated problem instances, we can say that their performance is remarkable.

关键词： controlled mobility lifetime maximization mobile sink wireless sensor networks mixed-integer linear programming

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EXPLORING THE CONNECTIVITY STRUCTURE IN METABOLIC NETWORKS: GOING BEYOND GRAPHS VIA DISCRETE OPTIMIZATION

EXPLORING THE CONNECTIVITY STRUCTURE IN METABOLIC NETWORKS: ...

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IEEE Statistical Signal Processing Workshop (SSP)

作者： Pey, Jon Rubio, Angel Crespo, Pedro Planes, Francisco J. Beasley, John E. Univ Navarra CEIT & TECNUN Elect & Commun Manuel Lardizabal 15 San Sebastian 20018 Spain Brunel Univ Math Sci Uxbridge UB8 3PH Middx England

ISBN: (纸本)9781457705700

Complex biological networks are commonly represented as graphs, where nodes represent biological entities and edges interactions between such entities. An important topological property of such graphs is the connectivity between any pair of nodes, as well as, if connected, their underlying minimum distance, which overall restricts the global behavior of the system. Algorithms from graph theory are typically used to accomplish this connectivity analysis. In particular, connectivity analysis via graph theory has been extensively applied to metabolic networks. Metabolic networks involve the inter-conversions of low molecular weight compounds (metabolites), which are responsible for the generation of building blocks of complex macromolecules and cellular energy. In these networks, nodes usually represent metabolites and edges inter-conversions between metabolites, which are technically biochemical reactions. In this article we illustrate that graph theory is not an appropriate tool to fully capture the topological properties of metabolic networks. We present a novel methodology based on linear discrete optimization, which is applied to examine the connectivity of certain key metabolites in Escherichia Coli, a well-known bacteria in the biological world.

关键词： metabolic networks path finding methods stoichiometry mixed-integer linear programming

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Assessing Impact of Demand Response in Emission-Constrained Environments

Assessing Impact of Demand Response in Emission-Constrained ...

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General Meeting of the IEEE-Power-and-Energy-Society (PES)

作者： Parvania, Masood Fotuhi-Firuzabad, Mahmud Shahidehpour, Mohammad Sharif Univ Technol Ctr Excellence Power Syst Control & Management Dept Elect Engn Tehran Iran Illinois Inst Technol ECE Dept Chicago IL 94035 USA

ISBN: (纸本)9781457710018

Reducing the emissions produced by the electric power production may be one of the most challenging problems of the electricity sector in the coming future. As one of the potential solutions, demand response (DR) can play an important role to reduce emissions and costs associated with emission reduction activities. This paper aims to assess the short-term impacts of running a DR program on a power system constrained by emissions caps. The DR program is designed to procure operating reserve from demand-side participants. A day-ahead network-constrained market clearing model with emission cap constraints is used as the assessment tool, where the DR program participants along with generating units are considered as available resources to provide reserve for the system. A model is also presented for reserve provided by DRPs and its associated cost function. The proposed approach is applied to the IEEE-RTS to illustrate the impacts of the DR program.

关键词： demand response emission cap operating reserve market clearing mixed-integer linear programming

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Heuristic decomposition and LP-based scheduling in make-and-pack production

Heuristic decomposition and LP-based scheduling in make-and-...

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IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)

作者： Baumann, Philipp Trautmann, Norbert Univ Bern Dept Business Adm CH-3012 Bern Switzerland

ISBN: (纸本)9781457707391

In this paper, we are concerned about the short-term scheduling of industrial make-and-pack production processes. The planning problem consists in minimizing the production makespan while meeting given end-product demands. Sequence-dependent changeover times, multi-purpose storage units with finite capacities, quarantine times, batch splitting, partial equipment connectivity, material transfer times, and a large number of operations contribute to the complexity of the problem. Known MILP formulations cover all technological constraints of such production processes, but only small problem instances can be solved in reasonable CPU times. In this paper, we develop a heuristic in order to tackle large instances. Under this heuristic, groups of batches are scheduled iteratively using a novel MILP formulation;the assignment of the batches to the groups and the scheduling sequence of the groups are determined using a priority rule. We demonstrate the applicability by means of a real-world production process.

关键词： Heuristic make-and-pack production mixed-integer linear programming multipurpose storage units production planning and control

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Optimal Allocation of Capacitors in Radial Distribution Systems with Distributed Generation

Optimal Allocation of Capacitors in Radial Distribution Syst...

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IEEE-PES Conference on Innovative Smart Grid Technologies Latin America (ISGT LA)

作者： Franco, John F. Rider, Marcos J. Lavorato, Marina Romero, Ruben UNESP Univ Estadual Paulista Dept Engn Eletr Fac Engn Ilha Solteira Ilha Solteira SP Brazil

ISBN: (纸本)9781457718014

This paper presents a mixed-integer linear programming approach to solving the optimal fixed/switched capacitors allocation (OCA) problem in radial distribution systems with distributed generation. The use of a mixed-integer linear formulation guarantees convergence to optimality using existing optimization software. The results of one test system and one real distribution system are presented in order to show the accuracy as well as the efficiency of the proposed solution technique.

关键词： Distribution system optimization optimal allocation of capacitors mixed-integer linear programming CPLEX AMPL

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A Generation Expansion Planning Model of a Strategic Electricity Generating Firm

A Generation Expansion Planning Model of a Strategic Electri...

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General Meeting of the IEEE-Power-and-Energy-Society (PES)

作者： Hesamzadeh, M. R. Amelin, M. Royal Inst Technol Sch Elect Engn Elect Power Syst Lab S-10044 Stockholm Sweden

ISBN: (纸本)9781457710018

This paper derives a mathematical structure for investment decisions of a profit-maximising and strategic producer in liberalised electricity markets. The paper assumes a Cournot producer in an energy market with nodal pricing regime. The Cournot producer is assumed to have revenue from selling energy to the pool. The investment problem of the strategic producer is modelled through a leader-follower game in applied mathematics. The leader is the strategic producer seeking the optimal mix of its investment technologies and the follower is a stochastic estimator. The stochastic estimator forecasts the reactions of other producers in the market in response to the investment decisions of the producer in question. The stochastic estimator takes the investment decisions of the producer and it calculates the stochastic prices. The mathematical structure is a stochastic linear bilevel programming problem. This problem is reformulated as a stochastic MILP problem which can be solved using the commercially available software packages. Finally, the developed mathematical structure is applied to a six-node example system to highlight the strengths of the whole approach.

关键词： Generation expansion planning mixed-integer linear programming Uncertainty

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Hierarchical Control for Drift Correction in Transmission Electron Microscopes

Hierarchical Control for Drift Correction in Transmission El...

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IEEE International Conference on Control Applications (CCA)

作者： Tarau, Alina N. Nuij, Pieter Steinbuch, Maarten Eindhoven Univ Technol Fac Mech Engn Control Syst & Technol Dept NL-5600 MB Eindhoven Netherlands

ISBN: (纸本)9781457710636

Electron microscopes are important tools for material science research since they can reveal accurate images (down to the atomic level) for a wide range of specimens. Moreover, a sample can be visualized while thermal processes are induced to the specimen. Such processes involve the contraction or the expansion of the specimen holder, and hence image movement. In current practice one has to wait until the image stabilizes and then analyze the sample. In this paper we propose a hierarchical control framework where at the lower levels we use local and independent PID controllers for adjusting the stage and the beam deflectors. These controllers are then coordinated by a supervisory controller such that maximum performance is achieved. The coordinating controller will solve a nonlinear optimization problem for linear stage models in the model-based predictive control (MPC) setting. Typically, this problem is NP hard and therefore difficult to solve. In this paper we propose to further improve the performance of the system by recasting the optimization problem into a mixed-integer linear programming (MILP) one. The advantage is that for MILP optimization problems solvers are available which guarantee to find the global optimum. Then the MILP solution can be used as good initial point when solving optimization problems for nonlinear stage models.

关键词： Computational modeling DC motors NP hard Optimization PID controllers Predictive models Transmission electron microscopy beam deflector adjustment computational complexity drift correction electron probes hierarchical control framework image movement image processing image stabilization integer programming linear programming linear stage models material science research mixed-integer linear programming model-based predictive control nonlinear optimization problem nonlinear programming physical instrumentation control predictive control stage adjustment thermal processes three-term control transmission electron microscopes

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Formulations and heuristics for the k-piecewise affine model fitting problem

Formulations and heuristics for the k-piecewise affine model...

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10th Cologne-Twente Workshop on Graphs and Combinatorial Optimization, CTW 2011

作者： Amaldi, E. Coniglio, S. Taccari, L. Dipartimento di Elettronica E Informazione Politecnico di Milano Piazza L. da Vinci 32 22133 Milan Italy

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