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Process Optimization for Industrial Load Management

INTERNATIONAL ENERGY JOURNAL 2008年第3期9卷 215-220页

作者： Babu, C. A. Ashok, S. Natl Inst Technol Dept Elect Engn Calicut 673601 Kerala India

Continuous process industries engaged in large scale manufacturing of chemicals and fertilizers are highly energy intensive and contribute significantly to system peak demand. Consequent to the introduction of TOU tariff rates by the utilities, industrial load management programs aimed at economic reduction of electric energy demand of the industries during utility's peak generation period, gained importance. This paper presents an optimization model and formulation for peak demand and electricity cost reduction in continuous process industries. The formulation utilizes non - linear programming technique for minimizing the electricity cost by rescheduling the loads satisfying the process, production, and maximum demand constraints. The proposed optimal schedules when applied to a typical chemical plant resulted in significant reduction in peak demand (about 16.8%) and electricity cost (about 4.6%) under the TOU tariff.

关键词： Load scheduling non linear programming peak demand TOU tariff

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Issues in the implementation of the DSD algorithm for the traffic assignment problem

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2006年第3期175卷 1577-1587页

作者： Lotito, Pablo A. Inst Natl Rech Informat & Automat METALAU Project F-78153 Le Chesnay France INRETS Arcueil France

In this paper we consider the practical implementation of the disaggregated simplicial decomposition (DSD) algorithm for the traffic assignment problem. It is a column generation method that at each step has to solve a huge number of quadratic knapsack problems (QKP). We propose a Newton-like method to solve the QKP when the quadratic functional is convex but not necessarily strictly. Our O(n) algorithm does not improve the complexity of the current methods but extends them to a more general case and is better suited for reoptimization and so a good option for the DSD algorithm. It also allows the solution of many QKP's simultaneously in a vectorial or parallel way. (c) 2005 Elsevier B.V. All rights reserved.

关键词： large scale optimization non linear programming quadratic programming traffic network flows

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Economic evaluation of two public policies to control water pollution.

INGENIERIA HIDRAULICA EN MEXICO

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INGENIERIA HIDRAULICA EN MEXICO 2006年第1期21卷 85-94页

作者： Gutíerrez-Andrade, MA Bravo-Pérez, HM Univ Autonoma Metropolitana Iztapalapa Iztapalapa Mexico Ctr Invest & Docencia Econ Div Adm Publ Mexico City DF Mexico

Since Pigou proposed that the internalization of the negative externalities could be done calculating a tax in order to correct the difference between private costs and social costs;this will recover the conditions of economic efficiency in all the hydraulic legislations of the world, however this advice has been applied in conditions of great shortage;it could be thought that to burden the consumptive use could be more suitable than to burden the production of residual water reaching this way not only the recovering of social efficiency but also a double dividend. to stimulate the water recycling. This work evaluates the effect of the tax charging to the consumptive use will have over a fake economy The achieved results of a residual water production tax. The contrast is done using a model of computable general equilibrium with the Arrow-Debreu assumptions relaxed with the introduction of a government that collect the proposed taxes in a previously distorted economy. The collection distributes through a direct transference to the revenue of the consumers, the model calibrates and resolves following the methodology proposed by Shoven & Whalley (1984).

关键词： public policies applied general equilibrium public economy water pollution water economy fiscal incidence non linear programming optimization

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IDENTIFICATION OF POWER AMPLIFIER USING MIMO TIME-DOMAIN REPRESENTATION

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IFAC Proceedings Volumes 2006年第1期39卷 541-546页

作者： Smail Bachir Mourad Djamai Claude Duvanaud Régis Ouvrard Laboratoire d'Automatique et d'Informatique Industrielle 4 avenue de Varsovie 16021 Angoulěme cedex

In this paper, we present a new technique for modeling and characterization of Power Amplifier (PA) by parameter estimation using continuous-time representation. Firstly, we study a continuous model which takes into account nonlinearities and PA filtering. The filter structure includes a non linear polynomial representing amplitude and phase conversion in addition to a MIMO Laplace plant. Then, we propose a new approach for PA model characterization based on parameter estimation with several excitations. Using time-domain measurements, this method deduces recursively an optimal estimation with non linear programming technique. The experimental results show good agreement and demonstrate the possibility of this technique to explain power amplifier dynamics.

关键词： Parameter estimation non linear programming initialization problem PA modeling continuous filter time-domain envelope

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PREDICTIVE CONTROL OF ASYMMETRICAL PROCESSES

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IFAC Proceedings Volumes 2006年第2期39卷 359-364页

作者： César de Prada Smaranda Cristea Department of Systems Engineering and Automatic Control University of Valladolid Spain

This paper deals with the control of processes that present different dynamic responses for equal increments and decrements of its manipulate variable, showing a non symmetric response. Being non-linear systems, instead of using non linear general methods directly, the paper explores two alternative formulations based on an MPC approach that take advantage of its structure. An application example is provided showing the behaviour of the proposed methods.

关键词： asymmetrical processes predictive control non linear programming MIQP problem

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Multiple data sets for model updating in real-time operations optimization

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COMPUTERS & CHEMICAL ENGINEERING 2002年第10期26卷 1345-1362页

作者： Yip, WS Marlin, TE McMaster Univ Dept Chem Engn Hamilton ON L8S 4L7 Canada

This paper presents a method for improving model-updating methods used for the real-time optimization (RTO) of plant operations. Previous work on updating and results analysis and diagnosis is extended to the use of multiple data sets for updating the steady-state plant model and to use prior knowledge to categorize the parameters as fast or slow changing. A key challenge in real-time estimation is identifying the maximum number of parameters that can be estimated reliably using the current data;this number changes due to differences in variability in operating condition and sensor availability. Since reliable parameter estimation yields a parameter covariance matrix with a small condition number and determinant, the number is based on a real-time diagnostic that is based on the covariance matrix. Case studies demonstrate the importance of a real-time updating diagnostic and indicate that when plant variation exists in multiple data sets, increased profit can be obtained by updating the additional parameters to reduce the plant/model mismatch. (C) 2002 Elsevier Science Ltd. All rights reserved.

关键词： real-time optimization parameter estimation non linear programming

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Computational experience with a safeguarded barrier algorithm for sparse nonlinear programming

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COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 2001年第1期19卷 107-120页

作者： Gajulapalli, RS Lasdon, LS Univ Texas Coll Business Adm MSIS Dept Austin TX 78712 USA

We describe an enhanced version of the primal-dual interior point algorithm in Lasdon, Plummer, and Yu (ORSA Journal on Computing, vol. 7, no. 3, pp. 321-332, 1995), designed to improve convergence with minimal loss of efficiency, and designed to solve large sparse nonlinear problems which may not be convex. New features include (a) a backtracking linesearch using an L1 exact penalty function, (b) ensuring that search directions are downhill for this function by increasing Lagrangian Hessian diagonal elements when necessary, (c) a quasi-Newton option, where the Lagrangian Hessian is replaced by a positive definite approximation (d) inexact solution of each barrier subproblem, in order to approach the central trajectory as the barrier parameter approaches zero, and (e) solution of the symmetric indefinite linear Newton equations using a multifrontal sparse Gaussian elimination procedure, as implemented in the MA47 subroutine from the Harwell Library (Rutherford Appleton Laboratory Report RAL-95-001, Oxfordshire, UK, Jan. 1995). Second derivatives of all problem functions are required when the true Hessian option is used. A Fortran implementation is briefly described. Computational results are presented for 34 smaller models coded in Fortran, where first and second derivatives are approximated by differencing, and for 89 larger GAMS models, where analytic first derivatives are available and finite differencing is used for second partials. The GAMS results are, to our knowledge, the first to show the performance of this promising class of algorithms on large sparse NLP's. For both small and large problems, both true Hessian and quasi- Newton options are quite reliable and converge rapidly. Using the true Hessian, INTOPT is as reliable as MINOS on the GAMS models, although not as reliable as CONOPT. Computation times are considerably longer than for the other 2 solvers. However, interior point methods should be considerably faster than they are here when analytic second

关键词： non linear programming barrier algorithm SQP algorithm large sparse problems

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New strategies for flexibility analysis and design under uncertainty

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COMPUTERS & CHEMICAL ENGINEERING 2000年第9-10期24卷 2193-2209页

作者： Raspanti, CG Bandoni, JA Biegler, LT Univ Nacl Sur Planta Piloto Ingn Quim CONICET RA-8000 Bahia Blanca Buenos Aires Argentina Carnegie Mellon Univ Dept Chem Engn Pittsburgh PA 15213 USA

Process flexibility and design under uncertainty have been researched extensively in the literature. Problem formulations for flexibility include nested optimization problems and these can often be refined by substituting the optimality conditions for these nested problems. However, these reformulations are highly constrained and can be expensive to solve. In this paper we extend algorithms to solve these reformulated NLP problem under uncertainty by introducing two contributions to this approach. These are the use of a Constraint Aggregation function (KS function) and Smoothing Functions. We begin with basic properties of KS function. Next, we review a class of parametric smooth functions, used to replace the complementarity conditions of the KKT conditions with a well-behaved, smoothed nonlinear equality constraint. In this paper we apply the previous strategies to two specific problems: i) the 'worst case algorithm', that assesses design under uncertainty and, ii) the flexibility index and feasibility test formulations. In the first case, two new algorithms are derived, one of them being single level optimization problem. Next using similar ideas, both flexibility index and feasibility test are reformulated leading to a single non linear programming problem instead of a mixed integer non linear programming one. The new formulations are demonstrated on five different example problems where a CPU time reduction of more than 70 and 80% is demonstrated. (C) 2000 Elsevier Science Ireland Ltd. All rights reserved.

关键词： design uncertainty flexibility non linear programming algorithms

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Optimization of plate fin heat exchangers - A continuous formulation

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CHEMICAL ENGINEERING RESEARCH & DESIGN 2000年第A6期78卷 849-859页

作者： Reneaume, JM Pingaud, H Niclout, N Ecole Natl Super Chim Genie Technol Ind Lab Genie Procedes Pau F-64000 Pau France Ecole Natl Super Ingenieurs Genie Chim Toulouse Lab Genie Chim Toulouse France Nordon Cryogenie Sas Golbey France

An industrial application of mathematical programming is presented. The objective is to propose a tool for computer aided design of compact plate fin heat exchangers. A proprietary sizing procedure, COLETH, is used to initialize the optimization problem and to evaluate the objective function and the constraints during the optimization problem resolution. The main features of COLETH are presented. The partial infeasible path strategy is discussed: at each optimization step, duty requirements are satisfied, but pressure drop constraints are not. Intermediate information can be used and the cpu time is quite low. A non linear programming optimization problem is formulated. Then the problem is solved using a reduced Hessien Successive Quadratic programming algorithm, which can take advantage of the system sparcity. Other features of this algorithm are discussed. Three test problems are presented and the program abilities are illustrated.

关键词： plate fin heat exchanger non linear programming optimization

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An infeasible point method for minimizing the Lennard-Jones potential

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COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 1997年第3期8卷 273-286页

作者： Gockenbach, MS Kearsley, AJ Symes, WW NIST APPL & COMPUTAT MATH DIVGAITHERSBURGMD 20899 RICE UNIV DEPT COMPUTAT & APPL MATHHOUSTONTX 77251

Minimizing the Lennard-Jones potential, the most-studied model problem for molecular conformation, is an unconstrained global optimization problem with a large number of local minima. In this paper, the problem is reformulated as an equality constrained nonlinear programming problem with only linear constraints. This formulation allows the solution to approached through infeasible configurations, increasing the basin of attraction of the global solution. In this way the likelihood of finding a global minimizer is increased. An algorithm for solving this nonlinear program is discussed, and results of numerical tests are presented.

关键词： global optimization penalty methods non linear programming

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