变负荷工况下NOx排放量预测控制

NO_x是火电厂排放的主要污染物之一,降低NO_x的排放是火电厂面临的主要问题。针对火电厂变负荷工况下的NO_x排放量最小化问题,本文提出了一种基于最小二乘支持向量机（LSSVM）的非线性模型预测控制算法。根据电站锅炉实际历史数据建立锅炉负荷预测模型和NO_x排放预测模型,并以交叉验证的方法优化模型参数,从而获得高精度模型。在此基础上以NO_x的排放量最小为优化目标,考虑锅炉负荷约束,构建锅炉燃烧优化模型。采用差分进化算法求解优化模型得到控制参数的最优设定值。为了验证本文提出算法的有效性,采用实际生产数据进行实验。实验结果表明本方法能够在变负荷工况下有效降低NO_x排放量,在不增加电厂改造成本上,为电厂提供了有效的控制手段,具有一定应用前景。     

空分短期停车时间阈值对氧气生产调度的影响

针对钢铁企业高炉休风场景下的氧气生产调度问题,提出以空分短期计划性停车为主要手段的调度策略,并基于MILP方法建立了氧气系统的优化调度模型。调度模型的优化目标为整个规划周期内氧气高压管网的综合压力最小化。模型包含了空分和部分氧气压缩机短期停车再启动操作的约束条件,并结合实际情况考虑了前述设备的停车时间阈值和运行时间阈值。以国内某大型钢铁企业为实际案例,验证了调度模型的合理性与可行性,然后基于模型计算分析了空分停车时间阈值对调度目标的影响规律。分析结果表明,减小空分停车时间阈值有利于获得更优的调度目标,但空分停车时间阈值对优化目标的影响规律具有阶跃特性,而非简单的比例关系。     

Modeling,simulation, and optimization of multiproduct cryogenic air separation unit startup

The startup of multiproduct cryogenic air separation plants takes several hours, during which time limited revenue is generated with high costs incurred due to the highly energy-intensive nature of these operations. This motivates the development of high-fidelity dynamic models to capture the complexity of the startup process to aid decision-making. This article focuses on the development of a startup model for a multiproduct air separation unit (ASU), and its use in dynamic simulation and optimization. To accomplish this, a first-principles based dynamic ASU model is extended by including various discontinuities using smooth approximations, adding dynamics to the primary heat exchanger, and extending the handling phase change within process streams. Dynamic simulations demonstrate plant response behavior during startup, including a failed startup resulting from an injudicious choice of input trajectory. In addition, improvement of startup operation is demonstrated through the incorporation of the model within a dynamic optimization framework.     

Effect of air separation unit integration on integrated gasification combined cycle performance and NO<Subscript>x</Subscript> emission characteristics

Thermodynamic simulation method is developed and applied to analyze the performance and the NO_x emission characteristics of the IGCC (Integrated Gasification Combined Cycle) power plants coupled with ASU (Air Separation Unit). Simulations on IGCC power plants are made through combining the chemical process models for coal gasification and gas clean-up and the thermodynamic combined cycle model with NO_x prediction capability. With coal as feedstock of IGCC, the present study investigates and compares the power output, the overall efficiency and the NO_x emission characteristics of various IGCC plants at different ASU integration conditions in order to give the design criteria for efficient and environmental friendly IGCC configuration.     

Maintenance scheduling and process optimization under uncertainty

In this paper, we describe an optimization framework for (i) deriving optimal maintenance policies in continuous process operations in the presence of parametric uncertainty and (ii) analyzing and quantifying the impact of uncertainty on optimal maintenance schedules. A systems effectiveness measure is introduced which depends on expected process profitability and process and reliability/maintenance characteristics. A mixed integer nonlinear optimization model is proposed which aims at identifying the number of maintenance (preventive or corrective) actions required over a given time horizon of interest, the time instants and sequence of these maintenance actions on the various components of the process system, so that the system effectiveness is maximized. By introducing the concept of availability threshold values, it is shown that an efficient solution strategy can be established which requires the solution of much smaller nonlinear optimization problems. The application of the proposed framework to an example problem highlights the important interactions between process operation and maintenance scheduling in the presence of uncertainty.     

A systematic strategy for multi-period heat exchanger network retrofit under multiple practical restrictions

A systematic strategy for retrofit of the multi-period heat exchanger network (HEN) on the basis of the multi-objective optimization is developed. In this three-stage procedure, a simplified multi-objective optimization model of the multi-period HEN is first established and then solved to target the retrofit, aiming to minimizing the total annual cost and total annual CO2 emissions. The obtained Pareto front represents series of retrofit targets under different emission limitations, from which the most desirable one can be selected. The matching of the existing and the required heat exchangers is further implemented to finalize the retrofit, which wil meet the practical retrofit requirements and matching restrictions. The application of the proposed procedure is il ustrated through a case study of a HEN in a vacuum gas oil hydro-treating unit.     

IGCC系统中燃机岛优化研究

为提高IGCC系统的功率和效率,需要对系统进行优化。采用Thermoflex软件从系统的角度出发对燃机岛进行了优化研究。研究表明：等燃气轮机排气温度（死）调节为燃气轮机的最佳调节方式。合理搭配压气机抽气比例和N2回注量可提高IGCC的系统效率,最佳匹配为整体空分系数0．2和N2回注系数0．6。采用燃气湿饱和法为主,N2稀释为辅的NOx排放控制方案有利于提高系统效率,最佳控制方案为燃料湿饱和法＋N2回注系数0．6＋整体空分系数0．2。     

混合多目标骨干粒子群优化算法在污水处理过程优化控制中的应用

通过对污水生化处理过程的分析,选取能耗和罚款最低为优化目标,建立污水生化处理过程多目标优化控制模型。为了提高Pareto最优解集的收敛性和多样性,提出一种基于Pareto支配和分解的混合多目标骨干粒子群优化算法（HBBMOPSO）。该方法采用带自适应惩罚因子的分解方法选取个体引导者,采用Pareto支配和拥挤距离法维护外部档案和选取全局引导者。此外,采用精英学习策略增强粒子跳出局部Pareto前沿的能力。最后,将HBBMOPSO与自组织模糊神经网络预测模型和自组织控制器相结合,实现污水生化处理过程溶解氧和硝态氮设定值的动态寻优、智能决策和底层跟踪控制。利用国际基准仿真平台BSM1进行实验验证,结果表明所提HBBMOPSO方法在保证出水水质参数达标的前提下,能够有效降低污水处理过程的能耗。     

Investigation of a Model-Based Deep Reinforcement Learning Controller Applied to an Air Separation Unit in a Production Environment

The need for load flexibility and increased efficiency of energy-intensive processes has become more and more important in recent years. Control of the process variables plays a decisive role in maximizing the efficiency of a plant. The widely used control models of linear model predictive controllers (LMPC) are only partly suitable for nonlinear processes. One possibility for improvement is machine learning. In this work, one approach for a purely data-driven controller based on reinforcement learning is explored at an air separation plant (ASU) in productive use. The approach combines the model predictive controller with a data-generated nonlinear control model. The resulting controller and its control performance are examined in more detail on an ASU in real operation and compared with the previous LMPC solution. During the tests, stable behavior of the new control concept could be observed for several weeks in productive operation.     

求解石油生产过程设定点优化的进化算法

引言石油生产过程与任何输入输出系统一样,长期以来积累了其注水井的注入率和生产井的产出率等丰富历史数据,通过对这些数据的分析,可以得到有关各注水井和各生产井的连通性信息,实时优化各注水井的最优注入率和各生产井的最优产出率,并及时调整各注入井和各生产井对应控制系统的设定值,可使石油开采过程保持在最优工况下运行[1-2]。     

活性污泥法脱氮除磷工艺优化设计的灵敏度分析

以ASM2D为机理模型对活性污泥法脱氮除磷工艺进行优化设计,在满足出水水质标准的前提下,使总设计费用达到最低,对优化模型中的各种参数进行灵敏度分析。结果表明,不同种类参数的灵敏度差别很大,其中目标函数中各参数对结果影响最大,最大灵敏度达到-99.02%;进水组分、化学计量系数和动力学参数的最大灵敏度分别为16.06%、11.9%和7.60%。随着排放标准的下降,系统的总费用也随之减少。对优化设计中参数进行灵敏度分析可以得出一些重要参数对结果的影响程度,为参数校正和结果输出提供理论依据。     

Optimization of an operating domestic wastewater treatment plant using elitist non-dominated sorting genetic algorithm

Multi-objective optimization of an operating domestic wastewater treatment plant is carried out using binary coded elitist non-dominated sorting genetic algorithm. Activated sludge model with extended aeration is used for optimization. For optimal plant operation, two different optimization problems are formulated and solved. The first optimization problem involves single-objective function to estimate kinetic parameters in activated sludge model using available plant data by minimizing the weighted sum-of-square errors between computed and plant values. The second optimization problem involves single-, two- and three-objective functions for efficient plant monitoring. In second category problem, objective functions are based on plant performance criteria (i.e., maximizing the influent flow rate of wastewater and minimizing the exit effluent concentration) and economic criteria (i.e., minimizing the plant operating cost). The important decision variables are: mean cell-residence time, mixed liquor suspended solid concentration in the reactor and underflow sludge concentration. Unique solution is obtained for the single-objective function optimization problem whereas a set of non-dominated solutions are obtained for the multi-objective optimization problems. A set of optimal operating conditions are proposed based on the present optimization study, which enhances the plant performance without affecting the discharge effluent quality. Finally, sensitivity analyses of the model results to the kinetic parameters and the kinetic parameters to the GA parameters are carried out to know the sensitivity of the obtained results with changes in the input parameter space.     

基于负荷划分数据和支持向量机的火电厂燃烧过程建模

为建立燃烧过程稳态模型,首先利用稳态检测算法提取稳态样本;针对稳态数据中的不均衡性,提出了一种基于负荷划分数据的方法,即根据负荷工况将样本划分成训练子集与测试子集,以提高模型的泛化性能。利用单因素图形分析方法确定3个模型参数的搜索范围,将网格搜索与交叉验证相结合选择最优的模型参数,在此基础上建立了一个300 MW燃煤火电厂机组锅炉燃烧过程的支持向量机模型,包括锅炉效率、NO_x排放量、排烟温度和飞灰含碳量4个过程输出。结果表明,经过参数优化的4个输出模型均具有很好的泛化性能。     

Optimized integration of renewable energy technologies into Alberta’s oil sands industry

An energy optimization model for the integration of renewable technologies into the energy infrastructure of the oil sands industry is presented. The proposed model determines the optimal configuration of oil producers and the energy infrastructure required to meet their energy demands. The model is geared toward the minimization of cost subject to carbon dioxide emission constraints. A mixed integer non-linear optimization model is developed that simultaneously optimizes capacity expansion and new investment decisions of conventional and renewable energy technologies. To illustrate its applicability, the proposed model was applied to a case study using data reported in the literature for various years of oil sands operations. A rolling horizon approach was implemented to determine the effect of investment decisions of previous operational years on the selection of new investment options. Results were compared with and without the incorporation of renewable energy technologies. The results obtained indicate that the proposed model is a practical tool that can be employed to evaluate and plan oil sands and energy producers for future scenarios. Moreover, the results show that renewable energy technologies have significant potential in reducing reliance on fossil-fuel based technologies and their associated CO₂ emissions. The emission constraints set for the operational year 2025 can only be achieved by the incorporation of renewables in the energy production mix.     

冷热电联供系统设计和运行集成优化

冷热电联供是提高能源综合利用效率的有效途径,其系统设计与运行策略通常相互耦合,因此实施联供系统的集成优化至关重要。本文同时考虑全生命周期内的投资与运行成本,提出以年度总成本最小化为优化目标,结合联供系统中燃气轮机、余热锅炉、吸收式制冷机等设备特性方程,以及针对以电定热、以热定电和混合热电三类典型运行策略,设置了冷、热和电三种负荷需求能量平衡方程,最终构建了包含固定电/热效率和动态电/热效率的联供系统设计与运行集成优化模型。所提方法应用于典型商业楼宇的冷热电联供系统优化设计,结果表明,只有通过综合运用混合热电运行策略、动态电/热效率和全年负荷特性数据,才有望获得合理可行的最优设计方案。     

HTR-PM大范围变负荷的MA自适应优化算法

为应对电网负荷需求的变化，球床模块式高温气冷堆核电站示范工程(HTR-PM)在设计上具备大范围变负荷运行以满足电网负荷的能力。由于无法获得大范围变负荷精确适用的模型，使得基于模型的操作优化面临挑战。为处理模型与对象的失配，提出HTR-PM大范围变负荷的MA(modifier adaptation)自适应优化算法。MA自适应优化算法利用过程反馈信息修正优化模型，促进优化模型与对象优化命题的一致性，进而有助于基于模型的操作优化收敛至对象的最优操作。借助信赖域框架，MA自适应优化算法可基于模型评价自适应更新模型、调整修正的优化模型的应用范围，确保在合适操作空间内求解优化模型。而且，信赖域框架还降低了算法性能对算法参数的敏感性。MA自适应优化算法在HTR-PM双堆同步大范围变负荷中的应用验证了方法的有效性。     

Enriched Air or Pure Oxygen as Oxidant for Gas‐to‐Liquid Process with Microchannel Reactors

The syngas production step is one of the most costly steps in a gas‐to‐liquid plant. Commonly, oxygen is used as an oxidant in the reforming step. However, through the introduction of microchannel reactors, the use of enriched air may be justified. The merits of using enriched air versus pure oxygen are analyzed by utilizing an autothermal reformer, with microchannel reactors in the once‐through Fischer‐Tropsch (FT) step. Pure oxygen is provided by a cryogenic air separation unit (ASU) and enriched air by use of air separation membranes. Pure oxygen requires a smaller FT reactor volume, which means lower reactor costs at the expense of having a costly cryogenic ASU to produce pure oxygen. The operating cost of the ASU is lower than that of the air membrane, but the installed cost is higher.     

水煤浆装置氧泵因"晃电"跳停原因分析及对策

简单介绍了水煤浆装置空分氧泵变频器的电气控制原理.分析了氧泵变频器因系统"晃电"而导致空分高压液氧泵跳停的情况.通过采取一些有针对性的措施,确保空分氧泉稳定运行.     

大型煤化工空分技术与设备发展现状

介绍了国内大型煤化工项目空分设备的发展现状,结合大唐多伦煤化工项目空分装置的实际应用情况和天津荣成钢厂空分装置设计情况,分析了国内大型空分设备的设计能力,概述了国内大型空分装置静设备和动设备的制造能力,并分析了空分系统压缩机组的应用情况,在此基础上给出了煤化工项目选用大型空分设备的建议。     

Optimal design and integration of an air separation unit (ASU) for an integrated gasification combined cycle (IGCC) power plant with CO2 capture

The air separation unit (ASU) plays a key role in improving the efficiency, availability, and operability of an oxygen-fed integrated gasification combined cycle (IGCC) power plant. An optimal integration between the ASU and the balance of the plant, especially the gasifier and the gas turbine (GT), has significant potential for enhancing the overall plant efficiency. Considering the higher operating pressure of the GT, an elevated-pressure air separation unit (EP-ASU) is usually favored instead of the conventional low-pressure air separation units (LP-ASU). In addition, a pumped liquid oxygen (PLOX) cycle is usually chosen if the operating pressure of the gasifier is high. A PLOX cycle helps to improve plant safety and availability and to decrease the capital cost by reducing the size of the oxygen compressor or by eliminating it completely. However, the refrigeration lost in withdrawn liquid oxygen must be efficiently recovered. This paper considers five different configurations of an ASU with PLOX cycle and compares their power consumptions with an EP-ASU with a traditional gaseous oxygen (GOX) cycle. The study shows that an optimally designed EP-ASU with a PLOX cycle can have similar power consumption to that of an EP-ASU with GOX cycle in the case of 100% nitrogen integration. In the case of an IGCC with pre-combustion CO₂ capture, the lower heating value (LHV) of the shifted syngas, both on a mass and volumetric basis, is in between the LHV of the unshifted syngas from an IGCC plant and the LHV of natural gas, for which the GTs are generally designed. The optimal air integration in the case of a shifted syngas is found to be much lower than that of an unshifted syngas. This paper concurs with the existing literature that the optimal integration occurs when air extracted from the GT can be replaced with the nitrogen from the ASU without exceeding mass/volumetric flow limitations of the GT. Considering nitrogen and air integration between the ASU and the GT, this paper compares the power savings in an LP-ASU with a PLOX cycle to the power savings in an EP-ASU with GOX cycle and EP-ASU with PLOX cycle. The results show that an LP-ASU with a PLOX cycle has less power consumption if the nitrogen integration levels are less than 50-60%. In addition, a study is carried out by varying the concentration of nitrogen and steam in the fuel diluents to the GT while the NOx level was maintained constant. The study shows that when the nitrogen injection rate exceeds 50%, an EP-ASU with a PLOX cycle is a better option than an LP-ASU with a PLOX cycle. This paper shows that an optimal design and integration of an ASU with the balance of the plant can help to increase the net power generation from an IGCC plant with CO₂ capture.