Zhejiang Supcon Software Co.

Hangzhou, China

Zhejiang Supcon Software Co.

Hangzhou, China
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Jiao Y.,Zhejiang University | Su H.,Zhejiang University | Hou W.,Zhejiang Supcon Software Co. | Li P.,TU Ilmenau
Industrial and Engineering Chemistry Research | Year: 2013

With the increasing demand for hydrogen resulting from fierce market competition and stringent environmental legislation, the hydrogen system has become an important component of a refinery. It is vital for the hydrogen system to be operated economically and safely under varying operating conditions. This calls for a systematic approach to the design and optimization of flexible hydrogen systems, which is the aim of this article. The hydrogen distribution network is designed at the minimum total annual cost subject to constraints on the flow rates and pressures of both existing and new equipment during the payback period. Varying hydrogen demands, different pipeline levels, and the possibility of hydrogen units being shut down are considered as operating conditions in the design optimization task, leading to the formulation and solution of a mixed-integer nonlinear programming (MINLP) problem. Using a linearization method, the MINLP formulation is approximated by a mixed-integer linear programming (MILP) problem, resulting in an acceptable quality and high efficiency. An industrial hydrogen system is taken as a case study. As shown in the case study, the proposed approach can handle high-dimensional and complex hydrogen system problems and gain significant economic improvements in comparison to an existing design. © 2013 American Chemical Society.


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.


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.


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.


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.


Zhang J.,Zhejiang University | Rong G.,Zhejiang University | Hou W.,Zhejiang Supcon Software Co. | Huang C.,Zhejiang Supcon Software Co.
Chemical Engineering Research and Design | Year: 2010

In refineries, fuel gas, which is continuously produced during the production process, is one of the most important energy sources. In this paper, a brief introduction of fuel gas system is given. The main problems concerned by the fuel gas system scheduler, such as the compressor operation strategy and the fuel assignment decision, are presented. A logical modeling method, which is called generalized disjunctive programming (GDP), is introduced to model the operation of compressors and the flow of branching structure pipeline network in the fuel gas system. The main purpose of this method is to make the modeling process more easily and systematically. In order to effectively deal with the flow rate proportion of loop structure pipeline network in the fuel gas system, an iterative procedure based on pipeline network simulation is proposed. Thus, the solution of a complex MINLP formulation is replaced by the sequential MILP problem. The efficiency of this method, which requires very low computational requirements, is illustrated with a case study. © 2009 The Institution of Chemical Engineers.


Jiao Y.,Zhejiang University | Su H.,Zhejiang University | Hou W.,Zhejiang Supcon Software Co.
Control Engineering Practice | Year: 2012

Heavier market competition and tighter environmental legislation lead to the increasing demand for hydrogen in refinery. Hence it is necessary for refinery to seek effective hydrogen management strategies to satisfy the increasing hydrogen requirements. In this paper, two improved systematic mathematical methods are developed based on two-step approach and simultaneous optimization approach respectively to retrofit the hydrogen network in refinery. To make the proposed approaches more suitable for real systems, the flowrate and purity at the reactor inlet of hydrogen consumers and the hydrogen recovery of purification units are considered as variables, and the minimum pure hydrogen of hydrogen consumers must be satisfied. Then the corresponding optimization problem is mathematically transformed to a mixed-integer nonlinear programming (MINLP) problem. However, solving a MINLP model directly will result in inconsistency in solution quality and time. In this paper, the solving of the complex MINLP formulation is avoided by using a mixed-integer linear programming (MILP) linearization technique, resulting in better quality, stability, and efficiency than solving the MINLP model directly. The proposed approaches in this paper could make the best use of resources and consequently provide significant environmental and economic benefits for refinery. A real case study is presented to illustrate the applicability of the proposed approaches. © 2012 Elsevier Ltd.


Ye B.-L.,Zhejiang University | Wu W.,Zhejiang University | Zhou X.,Zhejiang University | Mao W.,Zhejiang University | Li J.,Zhejiang SUPCON Software Co.
IEEE International Conference on Automation Science and Engineering | Year: 2013

It is generally recognized that Model Predictive Control (MPC) has many advantages in signal control of urban traffic networks. However, the computational complexity grows exponentially with the increase in network scale and predictive time horizon. In order to overcome this drawback, a signal split optimization approach is proposed in this paper, in which a large-scale traffic network was decomposed into a set of subnetworks. Based on the store-and-forward modeling paradigm, the optimization framework of each subnetwork is developed firstly. Then, Lagrange multipliers are employed to deal with interconnecting constraints among subnetworks, and the dual optimization problem corresponding to the whole network is constructed. Moreover, the dual optimization problem is optimized under a two-level optimization structure by interaction prediction approach. In the end, simulation experiments are given to illustrate the effectiveness of the proposed approach. © 2013 IEEE.


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).


Jiao Y.,Zhejiang University | Su H.,Zhejiang University | Hou W.,Zhejiang Supcon Software Co.
Huagong Xuebao/CIESC Journal | Year: 2011

In refinery, hydrogen, which is a precious and clean energy resource, is also the by-product and significant material source of petroleum refining and petrochemical hydrogenation process. To reduce cost and save energy for petrochemical industry, the hydrogen system should be operated under the optimal scheme to meet the varying demand from process. In this paper, the impact factors of hydrogen system operational scheduling are elaborated. A mixed integer nonlinear programming (MINLP) model that involves all the impact factors is established to optimize the multi-period scheduling of hydrogen system and solved with Lingo software. A case study based on the data from certain refinery factory is showed to demonstrate the effectiveness and feasibility of the scheduling methodology, as well as this method proposed plays an important role in guiding the scheduling of hydrogen system in refinery. © All Rights Reserved.

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