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Thermoeconomic Optimization of a 450 MW Natural Gas Burning Steam Power Plant

ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2016年第11期41卷 4643-4659页

作者： Anetor, Lucky Osakue, Edward E. Odetunde, Christopher Nigerian Def Acad Dept Mech Engn Kaduna Nigeria Texas Southern Univ Dept Ind Technol Houston TX USA Kwara State Univ Dept Aeronaut & Astronaut Engn Malete Nigeria

The theory of thermoeconomics and local optimization were used to investigate how the cost of the resources consumed by a 450 MW power plant varies with the unit cost of the resources consumed, the technical production coefficients of the productive structure and/or the external demand for the products. In order to accomplish this, the costs of exergy of the productive structure were analyzed under three different conditions by using the relevant characteristic equations. In general, it was found that the thermoeconomic cost of a flow consists of two parts, namely the monetary cost of the fuel exergy (natural gas in the present study) needed to produce the flow, that is, its thermoeconomic cost and the costs due to the productive process (cost of capital equipment, maintenance, etc.). The results show that the steam leaving the boiler has the lowest exergy cost, while the condenser has the highest. The sequential quadratic programming (SQP) algorithm was used to obtain the optimized solutions of each major component of the plant. It was found that substantial operational and capital cost benefits were realized by optimizing most of the major plant equipment (boiler, turbines, feedwater heaters and the pumps). However, optimization of the condenser did not yield any cost benefit in capital equipment cost, but did produce some savings in operational cost.

关键词： Thermoeconomic Local optimization Exergy sequential quadratic programming

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Numerical method for the time optimal control problem governed by the Benjamin-Bona-Mahony equation

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INTERNATIONAL JOURNAL OF COMPUTATIONAL SCIENCE AND ENGINEERING 2016年第3期13卷 296-302页

作者： Yu, Xin Zhang, Qian Zhang, Haolan Xu, Chao Zhejiang Univ Ningbo Inst Technol Ningbo 315100 Zhejiang Peoples R China Zhejiang Univ State Key Lab Ind Control Technol Hangzhou 310027 Zhejiang Peoples R China Zhejiang Univ Inst Cyber Syst & Control Hangzhou 310027 Zhejiang Peoples R China

This paper deals with the numerical approximation for the time optimal control problem governed by the Benjamin-Bona-Mahony (BBM) equation, which is an unspecified terminal time problem. Firstly, by projecting the original problem with the finite element method (FEM), another approximate problem governed by a system of ordinary differential equations will be obtained. Then, the parameterisation method for the optimal time and the control function will be carried out and the unspecified terminal time problem can be reduced to an optimal parameter selection problem with a fixed time horizon [0, 1]. This optimal parameter selection problem is a standard nonlinear mathematical programming problem and can be solved by sequential quadratic programming (SQP) algorithm. Finally, some numerical simulation studies will be given to illustrate the effectiveness of our numerical approximation method for the time optimal control problem governed by the BBM equation.

关键词： finite element method FEM sequential quadratic programming SQP time optimal control Benjamin-Bona-Mahony equation parameterisation method

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Gradient-based solution for hybrid precoding in MIMO systems

Gradient-based solution for hybrid precoding in MIMO systems

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Negin Bakhshi Zanjani Seyran Khademi Geert Leus Faculty of Electrical Engineering Mathematics and Computer Science TU Delft The Netherlands

ISBN: (纸本)9781509041183

The combination of baseband and analog precoding for multiple-input multiple-output (MIMO) systems is considered in this paper which is referred to as hybrid precoding. The system capacity, as a design criterion, is maximized subject to unit modulus constraints on the elements of the analog precoder (phase shifters), and a total power constraint. This is a non-convex problem due to the product of the analog and baseband precoder variables. The proposed technique suggests computing non-trivial complex derivatives of the objective and constraints, analytically, in order to develop an iterative gradient-based sequential optimization algorithm to solve the non-convex problem. Promising simulation results show that the solution of the proposed algorithm is sufficiently close to the optimal (full-baseband) precoder solution, regardless of the channel characteristics.

关键词： multiple-input multiple-output (MIMO) hybrid precoding nonlinear optimization sequential quadratic programming sequential quadratic programming multiple input multiple output systems prediction coding system capacity Baseband Non-Convex DESIGN CRITERIA Analog HYBRID aggregate capacity Solutions

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An SR1/BFGS SQP algorithm for nonconvex nonlinear programs with block-diagonal Hessian matrix

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MATHEMATICAL programming COMPUTATION 2016年第4期8卷 435-459页

作者： Janka, Dennis Kirches, Christian Sager, Sebastian Wachter, Andreas Heidelberg Univ Interdisciplinary Ctr Sci Comp IWR Neuenheimer Feld 368 D-69120 Heidelberg Germany Otto von Guericke Univ Inst Math Optimizat D-39106 Magdeburg Germany Northwestern Univ Dept Ind Engn & Management Sci Evanston IL 60208 USA

We present a quasi-Newton sequential quadratic programming (SQP) algorithm for nonlinear programs in which the Hessian of the Lagrangian function is block-diagonal. Problems with this characteristic frequently arise in the context of optimal control;for example, when a direct multiple shooting parametrization is used. In this article, we describe an implementation of a filter line-search SQP method that computes search directions using an active-set quadratic programming (QP) solver. To take advantage of the block-diagonal structure of the Hessian matrix, each block is approximated separately by quasi-Newton updates. For nonconvex instances, that arise, for example, in optimum experimental design control problems, these blocks are often found to be indefinite. In that case, the block-BFGS quasi-Newton update can lead to poor convergence. The novel aspect in this work is the use of SR1 updates in place of BFGS approximations whenever possible. The resulting indefinite QPs necessitate an inertia control mechanism within the sparse Schur-complement factorization that is carried out by the active-set QP solver. This permits an adaptive selection of the Hessian approximation that guarantees sufficient progress towards a stationary point of the problem. Numerical results demonstrate that the proposed approach reduces the number of SQP iterations and CPU time required for the solution of a set of optimal control problems.

关键词： Quasi-Newton sequential quadratic programming Direct methods for optimal control Optimum experimental design

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Energy-efficient design for non-regenerative MIMO relay networks

Energy-efficient design for non-regenerative MIMO relay netw...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Cong Sun Alessio Zappone Eduard A. Jorswieck School of Science Beijing University of Posts and Telecommunications China University of Casino and Southern Lazio Italy Communications Theory Communications Laboratory TU Dresden Germany

ISBN: (纸本)9781509041183

We consider the global energy efficiency (GEE) maximization problem for the general non-regenerative MIMO relay network, under the maximum power constraints for each user and each relay. The problem is reformulated through the fractional optimization technique, and the mean square error receiver filter is considered. By applying the alternating minimization method, we simplify the problem into several convex quadratic constrained quadratic programming subproblems, and solve the subproblems by the feasible shrinkage method combined with the sequential quadratic programming method. Because the result highly depends on the initialization, we design a deterministic initialization by introducing an auxiliary power minimization problem. Simulation results show that our proposed algorithm can achieve more than 10 times higher GEE than the previous works which are not tailored for GEE maximization.

关键词： MIMO relay energy efficiency deterministic initialization sequential quadratic programming sequential quadratic programming Relay networks Energy efficiency shrinkage mining initialization energy-efficient design Minimization methods multiple input multiple output systems

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Bio-inspired computational heuristics to study Lane-Emden systems arising in astrophysics model

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SPRINGERPLUS 2016年第1期5卷 1页

作者： Ahmad, Iftikhar Raja, Muhammad Asif Zahoor Bilal, Muhammad Ashraf, Farooq Univ Gujrat Dept Math Gujrat 50700 Pakistan COMSATS Inst Informat Technol Dept Elect Engn Attock 43600 Pakistan Univ Malaysia Pahang Fac Sci & Technol Pekan Pahang Malaysia

This study reports novel hybrid computational methods for the solutions of nonlinear singular Lane-Emden type differential equation arising in astrophysics models by exploiting the strength of unsupervised neural network models and stochastic optimization techniques. In the scheme the neural network, sub-part of large field called soft computing, is exploited for modelling of the equation in an unsupervised manner. The proposed approximated solutions of higher order ordinary differential equation are calculated with the weights of neural networks trained with genetic algorithm, and pattern search hybrid with sequential quadratic programming for rapid local convergence. The results of proposed solvers for solving the nonlinear singular systems are in good agreements with the standard solutions. Accuracy and convergence the design schemes are demonstrated by the results of statistical performance measures based on the sufficient large number of independent runs.

关键词： Singular systems Computational intelligence Genetic algorithm Artificial neural networks Pattern search methods sequential quadratic programming

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Design Optimization of an Interior Permanent Magnet Synchronous Machine (IPMSM) for Electric Vehicle Application 5

Design Optimization of an Interior Permanent Magnet Synchron...

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5th IEEE International Conference on Renewable Energy Research and Applications (ICRERA)

作者： Turker, Harun TH Smart Grid Expertise & Consulting 2 Rue Pasteur F-38600 Fontaine France

ISBN: (纸本)9781509033881

The aim of this paper is to optimize the performances of an Interior Permanent Magnet Synchronous Machine (IPMSM) for an Electric Vehicle application. The originality of this work concerns the use of a Reluctance Network (RN) method which furnishes the harmonics of output parameters (i.e. torque and back-emf) and automatically generates the derivative of the model. Then, precise and very fast optimizations are performed own to gradient method as sequential quadratic programming (SQP). Results arc also compared to Finite Element Analysis (FEA) and several optimizations are presented. Finally, the proposed method helps engineers to have a better sense of machines behavior and to quickly optimize the geometry of their machines during preliminary Design Process.

关键词： Permanent Synchronous Machine Electric Vehicle Reluctance Network sequential quadratic programming Finite Element Analysis Design Process

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Optimal Overcurrent Relay Coordination in Distribution System using Nonlinear programming Method 2

Optimal Overcurrent Relay Coordination in Distribution Syste...

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IEEE International Conference on Electrical Power and Energy Systems (ICEPES)

作者： Korde, Pragati N. Bedekar, Prashant P. GH Raisoni Inst Engn & Technol Elect Engn Dept Pune Maharashtra India Govt Coll Engn Elect Engn Dept Amravati India

ISBN: (纸本)9781509024766

A simple but powerful optimization method for coordination of over current (OC) relays is presented in this paper. For distribution system protection as well as backup protection in transmission system, overcurrent relay is most widely used. Maloperation of relays may occur if primary and backup relays are not properly coordinated. And therefore relay coordination become important part of power system protection. The main contribution of this paper is application of sequential quadratic programming (SQP) method for calculating optimum values of time multiplier setting (TMS) and plug setting (PS) of OCRs. The proposed algorithm was successfully tested on different systems. Comparison of results with genetic algorithm is also presented in this paper. From results it is found that SQP method is superior as compared to GA technique.

关键词： Overcurrent relay coordination backup protection nonlinear constrained optimization sequential quadratic programming genetic algorithm

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Improving the Accuracy of Time Series Prediction Pethod Based on Support Vector Machine 19

Improving the Accuracy of Time Series Prediction Pethod Base...

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19th IEEE International Conference on Soft Computing and Measurements (SCM)

作者： Polyakhov, Nikolay D. Prihodko, Irina A. Van, Efen St Petersburg Electrotech Univ LETI Dept Automat Control Syst St Petersburg Russia

ISBN: (纸本)9781467389198

Changing the electrical load is a non-stationary random process. It is proposed to process the observation data using principal component analysis. To predict the power consumption the method of support vector machine was selected in which the parameters of the regression model are determined on the basis of the solution of a sequential quadratic programming problem. Optimization of parameters of nuclear function is executed on the basis of particle swarm. The simulation results confirm the effectiveness of the proposed approach.

关键词： principal component analysis support vector machine sequential quadratic programming

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Aerodynamic Shape Optimization for Natural Laminar Flow Using a Discrete-Adjoint Approach 22

Aerodynamic Shape Optimization for Natural Laminar Flow Usin...

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22nd AIAA Computational Fluid Dynamics Conference

作者： Rashad, Ramy Zingg, David W. Univ Toronto Toronto ON M3H 5T6 Canada

ISBN: (数字)9781624103667

ISBN: (纸本)9781624103667

A framework for the design of natural-laminar-flow airfoils is developed based on multipoint aerodynamic shape optimization capable of efficiently incorporating and exploiting laminar-turbulent transition. A two-dimensional Reynolds-averaged Navier-Stokes flow solver making use of the Spalart-Allmaras turbulence model is extended to incorporate an iterative laminar-turbulent transition prediction methodology. The natural transition locations due to Tollmien-Schlichting instabilities are predicted using a simplified e(N) method or the compressible form of the Arnal-Habiballah-Delcourt criterion. The Reynolds-averaged Navier-Stokes solver is subsequently used in a gradient-based sequential quadratic programming shape optimization framework. The transition criteria are tightly coupled into the objective and gradient evaluations. The gradients are obtained using an augmented discrete-adjoint formulation for nonlocal transition criteria. Robust design over a range of cruise flight conditions is demonstrated through multipoint optimization. Finally, a technique is proposed and demonstrated to enable the design of natural-laminar-flow airfoils with robust performance over a range of critical N factors: the optimizer is seen to produce transition ramps similar to those used by experienced designers.

关键词： Natural Laminar Flow Aerodynamic Shape Optimization Reynolds Averaged Navier Stokes Laminar Turbulent Transition sequential quadratic programming Spalart Allmaras Turbulence Model Shape Optimization Aerodynamic Performance Commercial Aircraft Lift to Drag Ratio

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