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Decomposition based stochastic programming approach for polygeneration energy systems design under uncertainty / Pei Liu in Industrial & engineering chemistry research, Vol. 49 N° 7 (Avril 2010) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 49 N° 7 (Avril 2010) . - pp. 3295–3305 Titre : Decomposition based stochastic programming approach for polygeneration energy systems design under uncertainty Type de document : texte imprimé Auteurs : Pei Liu, Auteur ; Efstratios N. Pistikopoulos, Auteur ; Li, Zheng, Auteur Année de publication : 2010 Article en page(s) : pp. 3295–3305 Note générale : Industrial Chemistry Langues : Anglais (eng) Mots-clés : Stochastic  Programming  Polygeneration  Energy  Systems  under  Uncertainty Résumé : Polygeneration, a multi-input multioutput energy conversion process which typically involves the coproduction of electricity and liquid synthetic fuels, is a promising technology which offers real potential toward the reduction of excessive energy consumption and consequent greenhouse gas emissions. The optimal design of such a complex and nonlinear process system under inevitable and unpredictable future uncertainty poses great challenges in terms of both modeling and corresponding solution strategies. In this paper, we propose a stochastic programming framework for the optimal design under uncertainty of polygeneration energy systems. On the basis of a detailed mixed-integer nonlinear programming (MINLP) model, proposed in our previous work, a two-stage stochastic programming problem is formulated, which is then converted into a large-scale multiperiod MINLP problem by employing cubature based integration and sampling techniques. A decomposition algorithm is utilized for the efficient solution of the multiperiod problem, which involves iterations between a set of nonlinear subproblems of much smaller size and a master mixed-integer linear programming problem. A case study is then presented, where detailed computational results and comparisons between optimal designs obtained for both the stochastic and deterministic cases are shown. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie901490g [article] Decomposition based stochastic programming approach for polygeneration energy systems design under uncertainty [texte imprimé] / Pei Liu, Auteur ; Efstratios N. Pistikopoulos, Auteur ; Li, Zheng, Auteur . - 2010 . - pp. 3295–3305. Industrial Chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 49 N° 7 (Avril 2010) . - pp. 3295–3305 Mots-clés : Stochastic  Programming  Polygeneration  Energy  Systems  under  Uncertainty Résumé : Polygeneration, a multi-input multioutput energy conversion process which typically involves the coproduction of electricity and liquid synthetic fuels, is a promising technology which offers real potential toward the reduction of excessive energy consumption and consequent greenhouse gas emissions. The optimal design of such a complex and nonlinear process system under inevitable and unpredictable future uncertainty poses great challenges in terms of both modeling and corresponding solution strategies. In this paper, we propose a stochastic programming framework for the optimal design under uncertainty of polygeneration energy systems. On the basis of a detailed mixed-integer nonlinear programming (MINLP) model, proposed in our previous work, a two-stage stochastic programming problem is formulated, which is then converted into a large-scale multiperiod MINLP problem by employing cubature based integration and sampling techniques. A decomposition algorithm is utilized for the efficient solution of the multiperiod problem, which involves iterations between a set of nonlinear subproblems of much smaller size and a master mixed-integer linear programming problem. A case study is then presented, where detailed computational results and comparisons between optimal designs obtained for both the stochastic and deterministic cases are shown. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie901490g

Robust control of PM spherical stepper motor based on neural networks / Li, Zheng in IEEE transactions on industrial electronics, Vol. 56 N° 8 (Août 2009) 

Public ISBD [article]  in IEEE transactions on industrial electronics > Vol. 56 N° 8 (Août 2009) . - pp. 2945 - 2954 Titre : Robust control of PM spherical stepper motor based on neural networks Type de document : texte imprimé Auteurs : Li, Zheng, Auteur Article en page(s) : pp. 2945 - 2954 Note générale : Génie électrique Langues : Anglais (eng) Mots-clés : Dynamic  model  Permanent  magnet  (PM)  Robust  neural  network  (RNN)  control  Spherical  stepper  motor  Tracking Index. décimale : 621.38 Dispositifs électroniques. Tubes à électrons. Photocellules. Accélérateurs de particules. Tubes à rayons X Résumé : There are many uncertainties and disturbances in the real dynamic system of a spherical stepper motor that make traditional control methods with lower precision, such as uncertain changes of magnetic field, load, and friction that generate speed ripple and deteriorate the 3-D tracking performance of the spherical motor system. In this paper, an available method is proposed to solve them by using neural networks (NNs) and a robust control scheme for improving the performance. First, a simplified torque calculation model based on finite-element method results can guarantee quick prediction of electromagnetic torque with lower error. Thus, the system model considering the friction, load, and disturbances is developed. Second, a robust NN (RNN) control scheme is presented to eliminate uncertainties to improve the tracking robust stability and overcome the undesired influence of uncertainties based on the nonlinear system dynamic model under continuous-trajectory tracking mode. Finally, as an example, the step-response and continuous-tracking processes of the motor using an RNN controller are simulated, and experiments, including the tracking using RNN proportional-differential control, are carried out to confirm the usefulness of the proposed control scheme. The simulation and experimental results of the proposed control scheme on the spherical stepper motor system demonstrate the effectiveness on satisfactory tracking performance. DEWEY : 621.38 ISSN : 0278-0046 En ligne : http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5061562 [article] Robust control of PM spherical stepper motor based on neural networks [texte imprimé] / Li, Zheng, Auteur . - pp. 2945 - 2954. Génie électrique Langues : Anglais (eng) in IEEE transactions on industrial electronics > Vol. 56 N° 8 (Août 2009) . - pp. 2945 - 2954 Mots-clés : Dynamic  model  Permanent  magnet  (PM)  Robust  neural  network  (RNN)  control  Spherical  stepper  motor  Tracking Index. décimale : 621.38 Dispositifs électroniques. Tubes à électrons. Photocellules. Accélérateurs de particules. Tubes à rayons X Résumé : There are many uncertainties and disturbances in the real dynamic system of a spherical stepper motor that make traditional control methods with lower precision, such as uncertain changes of magnetic field, load, and friction that generate speed ripple and deteriorate the 3-D tracking performance of the spherical motor system. In this paper, an available method is proposed to solve them by using neural networks (NNs) and a robust control scheme for improving the performance. First, a simplified torque calculation model based on finite-element method results can guarantee quick prediction of electromagnetic torque with lower error. Thus, the system model considering the friction, load, and disturbances is developed. Second, a robust NN (RNN) control scheme is presented to eliminate uncertainties to improve the tracking robust stability and overcome the undesired influence of uncertainties based on the nonlinear system dynamic model under continuous-trajectory tracking mode. Finally, as an example, the step-response and continuous-tracking processes of the motor using an RNN controller are simulated, and experiments, including the tracking using RNN proportional-differential control, are carried out to confirm the usefulness of the proposed control scheme. The simulation and experimental results of the proposed control scheme on the spherical stepper motor system demonstrate the effectiveness on satisfactory tracking performance. DEWEY : 621.38 ISSN : 0278-0046 En ligne : http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5061562