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Jiao Y.,Zhejiang University | Su H.,Zhejiang University | Hou W.,Zhejiang Supcon Software Co. | Liao Z.,Zhejiang University
Chemical Engineering Research and Design | Year: 2012

Deterministic optimization approaches have been developed and used in the optimization of hydrogen network in refinery. However, uncertainties may have a large impact on the optimization of hydrogen network. Thus the consideration of uncertainties in optimization approaches is necessary for the optimization of hydrogen network. A novel chance constrained programming (CCP) approach for the optimization of hydrogen network in refinery under uncertainties is proposed. The stochastic properties of the uncertainties are explicitly considered in the problem formulation in which some input and state constraints are to be complied with predefined probability levels. The problem is then transformed to an equivalent deterministic mixed-integer nonlinear programming (MINLP) problem so that it can be solved by a MINLP solver. The solution of the optimization problem provides comprehensive information on the economic benefit under different confidence levels by satisfying process constraints. Based on this approach, an optimal and reliable decision can be made, and a suitable compensation between the profit and the probability of constraints violation can be achieved. The approach proposed in this paper makes better use of resources and can provide significant environmental and economic benefits. Finally, a case study from a refinery in China is presented to illustrate the applicability and efficiency of the developed approach. © 2012 The Institution of Chemical Engineers. Source


Jiao Y.,Zhejiang University | Su H.,Zhejiang University | Hou W.,Zhejiang Supcon Software Co.
2011 International Symposium on Advanced Control of Industrial Processes, ADCONIP 2011 | Year: 2011

The requirement of hydrogen in oil refineries is increasing as market forces and environmental legislation, so the management and optimization of hydrogen system in refineries is becoming increasingly more important. In this paper, an improved approach for the optimization of hydrogen network is proposed. The method decomposes the optimization problem into two sub-problems, the optimization of feed routes of purification system and hydrogen network. By establishing a superstructure model, all possible placements of existing compressors and purifiers are incorporated in the proposed NLP model. The approach in this paper makes best use of resources and can provide significant environmental and economic benefits. A real case study is introduced to illustrate the applicability of the presented approach. © 2011 Zhejiang University. Source


Shen Y.,Zhejiang University | Chen X.,Zhejiang University | Xie L.,Zhejiang University | Li X.,Zhejiang University | And 2 more authors.
Huagong Xuebao/CIESC Journal | Year: 2013

Proton exchange membrane(PEM) fuel cells are electrochemical devices that covert the chemical energy to electricity directly. This study was concentrated on the air supply system. This paper presented an improved four order fuel cell air supply system model, analyzing its constraints. And the linear parameter varying(LPV) model was proposed to deal with the non-linear characteristics of the dynamic model. To cope with the problem of immeasurable states, the Kalman filter was used to estimate the states and the output variables which should be measured were selected. Additionally, the state space model predictive control algorithm satisfying the constraints is designed based on LPV model to control the compressor voltage to ensure an adequate response to hydrogen fuel. Simulation results showed that model predictive controller based on LPV model is able to effectively control the fuel cell air system, and to meet the compressor surge and blocking boundary conditions and other constraints, Comparing with single model predictive control, better control performance was obtained with the proposed LPV-MPC. © All Rights Reserved. Source


Jiao Y.,Zhejiang University | Su H.,Zhejiang University | Hou W.,Zhejiang Supcon Software Co. | Liao Z.,Zhejiang University
Industrial and Engineering Chemistry Research | Year: 2012

In a refinery, hydrogen, as a valuable resource, is also a byproduct and a significant raw material source of the petroleum refining and petrochemical hydrogenation process. To reduce costs and save energy for the petrochemical industry, the hydrogen system in a refinery should be operated under the optimal scheme to meet the varying hydrogen demands of hydrogen consumers. Optimal scheduling of the hydrogen system can help a refinery to achieve cost reduction and cleaner production. In this paper, a discrete-time mixed-integer nonlinear programming (MINLP) model that considers the penalties for abnormal situations in the hydrogen pipe network (HPN), compressors start-stop, and changes in hydrogen sources for hydrogen consumers is proposed for the optimal scheduling of the hydrogen system under multiperiod operation. The solution of the scheduling problem is obtained based on an iterative method between that of a mixed-integer linear programming (MILP) problem and that of a nonlinear programming (NLP) problem, avoiding the solution of the MINLP problem directly and the occurrence of composition discrepancy. A case study based on the data from a real refinery is presented to illustrate the effectiveness and feasibility of the proposed methodology. © 2012 American Chemical Society. Source


Jiao Y.,Zhejiang University | Su H.,Zhejiang University | Liao Z.,Zhejiang University | Hou W.,Zhejiang Supcon Software Co.
Chinese Journal of Chemical Engineering | Year: 2011

The demand of hydrogen in oil refinery is increasing as market forces and environmental legislation, so hydrogen network management is becoming increasingly important in refineries. Most studies focused on single- objective optimization problem for the hydrogen network, but few account for the multi-objective optimization problem. This paper presents a novel approach for modeling and multi-objective optimization for hydrogen network in refineries. An improved multi-objective optimization model is proposed based on the concept of superstructure. The optimization includes minimization of operating cost and minimization of investment cost of equipment. The proposed methodology for the multi-objective optimization of hydrogen network takes into account flow rate constraints, pressure constraints, purity constraints, impurity constraints, payback period, etc. The method considers all the feasible connections and subjects this to mixed-integer nonlinear programming (MINLP). A deterministic optimization method is applied to solve this multi-objective optimization problem. Finally, a real case study is introduced to illustrate the applicability of the approach. © 2011 Chemical Industry and Engineering Society of China (CIESC) and Chemical Industry Press (CIP). Source

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