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53rd IEEE Annual Conference on Decision and Control (CDC)

作者： Fardad, Makan Diwadkar, Amit Vaidya, Umesh Syracuse Univ Dept Elect Engn & Comp Sci Syracuse NY 13244 USA Iowa State Univ Dept Elect & Comp Engn Ames IA 50011 USA

ISBN: (纸本)9781467360906

We consider the problem of controllability degradation in dynamical networks subjected to malicious attacks. Attacks on the networks are assumed to be in the form of the removal of interconnection links. We formulate an optimization problem that seeks sets of links whose removal causes maximal degradation in the rank of the controllability gramian. We apply the alternating direction method of multipliers and sequential convex programming to find local solutions to this combinatorial optimization problem. We provide illustrative examples to demonstrate the utility of our results.

关键词： Alternating direction method of multipliers (ADMM) cyber-physical systems link failure rank minimization sequential convex programming

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Power Flow Optimization for Smart Microgrids by SDP Relaxation on Linear Networks

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IEEE TRANSACTIONS ON SMART GRID 2013年第2期4卷 751-762页

作者： Erseghe, Tomaso Tomasin, Stefano Univ Padua Dipartimento Ingn Informaz I-35131 Padua Italy

In a smart microgrid currents injected by distributed energy resources (DERs) and by the point of common coupling can be adapted to minimize the energy cost. Design and quality constraints usually make the problem grow fast with the number of nodes in the network. In this paper we provide a solution to the optimization problem having a significantly reduced complexity with respect to existing techniques. The efficiency of the proposed solution stems by modeling the smart microgrid as a linear network where loads are approximated as impedances. This simplification allows avoiding explicit use of power flow equations, and having a number of equation proportional to the number of DERs rather than to the total number of nodes (loads and DERs). The optimal power flow problem is then solved by a semidefinite programming (SDP) relaxation, which provides the initial point for the search of a feasible solution by a sequential convex programming procedure based on a local linear approximation of non-convex constraints. Numerical results show the merits of the proposed approach for typical smart microgrid scenarios.

关键词： Energy efficiency optimal power flow semidefinite programming sequential convex programming smart microgrid

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Voltage/VAR Control in Distribution Networks via Reactive Power Injection Through Distributed Generators

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IEEE TRANSACTIONS ON SMART GRID 2012年第3期3卷 1226-1234页

作者： Deshmukh, Siddharth Natarajan, Balasubramaniam Pahwa, Anil Kansas State Univ Dept Elect & Comp Engn Kansas City KS 66506 USA

This paper demonstrates how reactive power injection from distributed generators can be used to mitigate the voltage/VAR control problem of a distribution network. Firstly, power flow equations are formulated with arbitrarily located distributed generators in the network. Since reactive power injection is limited by economic viability and power electronics interface, we formulate voltage/VAR control as a constrained optimization problem. The formulation aims to minimize the combined reactive power injection by distributed generators, with constraints on: 1) power flow equations;2) voltage regulation;3) phase imbalance correction;and 4) maximum and minimum reactive power injection. The formulation is a nonconvex problem thereby making the search for an optimal solution extremely complex. So, a suboptimal approach is proposed based on methods of sequential convex programming (SCP). Comparing our suboptimal approach with the optimal solution obtained from branch and bound method, we show the trade-off in quality of our solution with runtime. We also validate our approach on the IEEE 123 node test feeder and illustrate the efficacy of using distributed generators as distributed reactive power resource.

关键词： convex optimization distributed generation distribution network sequential convex programming voltage/VAR control

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TIME DIVISION MULTIPLE ACCESS METHODS IN BI-DIRECTIONAL COOPERATIVE RELAY NETWORKS

TIME DIVISION MULTIPLE ACCESS METHODS IN BI-DIRECTIONAL COOP...

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IEEE 7th Sensor Array and Multichannel Signal Processing Workshop (SAM)

作者： Schad, Adrian Pesavento, Marius Tech Univ Darmstadt Commun Syst Grp D-64283 Darmstadt Germany

ISBN: (纸本)9781467310710

In this paper, we develop a new class of time division multiple access schemes for bi-directional multiuser communications in cooperative amplify-and-forward relay networks. The proposed schemes enable a flexible trade-off between spectral efficiency and suppression of multiuser interference. The relay weights are chosen to maximize the minimum received quality-of-service of all the users under constraints on the individual and the total power at the relays. Simulation results demonstrate that the selection of the scheme has a considerable impact on the achieved throughput of the relay network.

关键词： Amplify-and-forward relaying bi-directional relaying distributed beamforming multiuser peer-to-peer relay networks sequential convex programming

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Optimization methods for advanced design of aircraft panels: a comparison

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OPTIMIZATION AND ENGINEERING 2010年第4期11卷 583-596页

作者： Colson, Benoit Bruyneel, Michael Grihon, Stephane Raick, Caroline Remouchamps, Alain SAMTECH Sa Liege Belgium AIRBUS France Toulouse France

Advanced nonlinear analyses developed for estimating structural responses for recent applications for the aerospace industry lead to expensive computational times. However optimization procedures are necessary to quickly provide optimal designs. Several possible optimization methods are available in the literature, based on either local or global approximations, which may or may not include sensitivities (gradient computations), and which may or may not be able to resort to parallelism facilities. In this paper sequential convex programming (SCP), Derivative Free Optimization techniques (DFO), Surrogate Based Optimization (SBO) and Genetic Algorithm (GA) approaches are compared in the design of stiffened aircraft panels with respect to local and global instabilities (buckling and collapse). The computations are carried out with software developed for the European aeronautical industry. The specificities of each optimization method, the results obtained, computational time considerations and their adequacy to the studied problems are discussed.

关键词： Structural optimization sequential convex programming Derivative-free optimization Surrogate-based optimization Aeronautical engineering

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Very large scale optimization by sequential convex programming

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OPTIMIZATION METHODS & SOFTWARE 2004年第1期19卷 103-120页

作者： Zillober, C Schittkowski, K Moritzen, K Univ Bayreuth Dept Math D-95440 Bayreuth Germany Univ Dortmund Inst Appl Math D-44221 Dortmund Germany

We introduce a method for constrained nonlinear programming that is widely used in mechanical engineering and that is known under the name SCP for sequential convex programming. The algorithm consists of solving a sequence of convex and separable subproblems, where an augmented Lagrangian merit function is used for guaranteeing convergence. Originally, SCP methods were developed in structural mechanical optimization, and are particularly applied to solve topology optimization problems. These problems are extremely large and possess dense Hessians of the objective function. The purpose of the article is to show that constrained dense nonlinear programs with 10 5 -10 6 variables can be solved successfully and that SCP methods can be applied also to optimal control problems based on semilinear elliptic partial differential equations after a full discretization.

关键词： large scale nonlinear programming sequential convex programming topology optimization optimal control of partial differential equations semilinear elliptic equations

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Reduction of vibration level in rotordynamics by design optimization

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STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION 2007年第2期34卷 139-149页

作者： Strauss, Frank Inagaki, Mizuho Starke, Jens Heidelberg Univ Inst Appl Math D-69120 Heidelberg Germany Toyota Cent Res & Dev Labs Inc Aichi 4801192 Japan

We focus on the reduction of the vibration level of rotors by optimizing the shape of the body. The target is to reduce rotor weight and rotor vibrations leading to higher efficiency and less noise. We consider a finite element discretization of the rotor using a Rayleigh beam model which includes rotary inertia and gyroscopic moments leading to nonself-adjoint systems. We present a general algebraic framework for this case. The mass function is the objective function of the optimization problem and constraints are set on the nonlinear and nonconvex functions of critical speed and unbalanced response. For the numerical solution, algorithms belonging to the class of sequential convex programming are applied for the example of a turbocharger. A remarkable reduction of mass of an initially given prototype could be achieved while significantly reducing the unbalanced response and raising the critical speeds.

关键词： rotating machinery gyroscopic systems vibration level shape optimization sequential convex programming

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Composite structures optimization using sequential convex programming

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ADVANCES IN ENGINEERING SOFTWARE 2002年第7-10期33卷 697-711页

作者： Bruyneel, M Fleury, C Univ Liege Mech Inst B52 LTAS B-4000 Liege Belgium

The design of composite structures is considered here. The approximation concepts approach is used to solve the optimization problem. The convex approximations of the MMA family are briefly described. Several modifications of these approximations are presented. They are now based on gradient information at two successive iterations, avoiding the use of the expensive second-order derivatives. A two-point fitting scheme is also described, where the function value at the preceding design point is used to improve the approximation. Numerical examples compare these new purely non-monotonous schemes to the existing ones for the selection of optimal fibers orientations in laminates. It is shown how these two-point based approximations are well adapted to the problem and can improve the optimization task, leading to reasonable computational efforts. A procedure is also derived for considering simultaneously monotonous and non-monotonous structural behaviors. The resulting generalized approximation scheme is well suited for the optimization of composite structures when both plies thickness and fibers orientations are considered as design variables. It is concluded that the newly developed approximation schemes of the MMA family are reliable for composite structures optimization. All the studied approximations are convex and separable: the optimization problem can then be solved using a dual approach. (C) 2002 Civil-Comp Ltd and Elsevier Science Ltd. All rights reserved.

关键词： structural optimization sequential convex programming dual method composite structures

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Composite structures optimization using sequential convex programming

Composite structures optimization using sequential convex pr...

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2nd International Conference on Engineering Computational Technology/5th International Conference on Computational Structures Technology

作者： Bruyneel, M Fleury, C Univ Liege Mech Inst B52 LTAS B-4000 Liege Belgium

ISBN: (纸本)0948749695

关键词： structural optimization sequential convex programming dual method composite structures

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Nonlinear programming: Algorithms, software, and applications - From small to very large scale optimization

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21st Conference on System Modeling and Optimization

作者： Schittkowski, K Zillober, C Univ Bayreuth Dept Comp Sci D-95440 Bayreuth Germany

ISBN: (纸本)1402077602

We introduce some methods for constrained nonlinear programming that are widely used in practice and that are known under the names SQP for sequential quadratic programming and SCP for sequential convex programming. In both cases, convex subproblems are formulated, in the first case a quadratic programming problem, in the second case a separable nonlinear program in inverse variables. The methods are outlined in a uniform way and the results of some comparative performance tests are listed. We especially show the suitability of sequential convex programming methods to solve some classes of very large scale nonlinear programs, where implicitly defined systems of equations seem to support the usage of inverse approximations. The areas of interest are structural mechanical optimization, i.e., topology optimization, and optimal control of partial differential equations after a full discretization. In addition, a few industrial applications and case studies are shown to illustrate practical situations under which the codes implemented by the authors are in use.

关键词： sequential quadratic programming SQP sequential convex programming SCP comparative tests industrial applications topology optimization optimal control of semilinear elliptic equations

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