泵站压力管道振动特性分析及减振优化设计

为探究泵站压力管道的不同布置形式对管道振动的影响,选取宁夏盐环定泵站工程二泵站#1压力管道为研究对象,建立基于流固耦合的泵站压力管道水流ALGOR数值模型,并采用DASP振动测试系统获取振动信号对模拟结果进行验证,分析压力管道水流流态对管道振动的激励特征并提出优化设计方案。结果表明,压力管道进水管处、支管总管相接处及总出水管处均有强烈的振动,但进水管的振动较出水总管振动更为强烈;减振优化设计方案中,调整支管距离对降低水流对管道振动的激励效果微弱,增大管径及改变总管走向对其效果较好,其中总管走向在2°～5°之间较佳,不仅能降低管道振动,而且能减少泵站能耗损失。研究结果可为高扬程泵站压力管道的优化设计提供理论依据。     

抽油井不压井作业装置及抽油泵底阀设计

江苏油田的部分油井存在油管短路、地层高压低渗、漏失严重等问题,这些问题造成压井作业困难,并且压井作业过程中的井控与环境污染风险较大。为了进行不压井检泵作业,同时缩短检泵之后的产量恢复周期,进行了不压井作业技术研究,并研制了不压井作业装置。为解决起下抽油杆过程中的防喷问题,改进了抽油泵底阀结构,该结构可实现起下抽油杆过程中油管不带压、无溢流,并保障起下油管过程中的井控安全。该技术在江苏油田现场应用9井次,效果良好。     

基于目标级联技术的含风电互联电网机组组合策略

针对含风电互联电网日前安全约束机组组合的规模大、约束复杂、求解困难等问题,提出基于目标级联分析技术的分散协调优化策略。将问题分解为负责区域间边界节点电压相角协调的上层优化问题和以并行方式独立优化各区域发电计划的下层优化问题。下层优化以弃风电量期望和电量不足期望,量化各区域内风电、负荷预测误差,以及常规机组强迫停运等系统运行不确定性所带来的风险,并以罚函数的形式引入目标函数,以综合优化系统可靠性与经济性。2区域12节点系统和IEEE RTS96三区域互联系统算例仿真验证所建模型和算法的有效性。     

机电复合作用下发电电动机磁极连接线建模及应力分析

针对抽水蓄能机组发电电动机转子磁极连接线现有设计校核往往仅考虑单一机械应力作用,提出计及机端短路故障的机电复合作用下发电电动机磁极连接线建模及应力分析方法。首先,基于有限元方法建立某抽水蓄能机组发电电动机转子结构有限元模型,得到磁极连接线不同工况下单一机械应力结果,然后建立机端三相短路故障下发电电动机电磁场有限元模型,得到计及故障下电磁力作用的机电复合应力结果。结果表明,磁极连接线飞逸工况下承受机械应力约为额定工况时的2倍,电磁力对磁极连接线不同区域影响不均,受力方向和大小的变化规律与机械应力不同,机电复合作用下会造成磁极连接线局部应力激增。     

A flexible air separation process: 1. Design and steady-state optimizations

The flexible operation of energy-intensive processes, such as cryogenic air separation, has economic potential due to increasing fluctuations of the electricity markets. Multiproduct air separation processes with high ratios of liquid product are very promising for flexible operation due to storable products. We present a process design with an integrated liquefication cycle and liquid assist operation, that facilitates a high liquid product ratio and a flexible process operation. We use a mechanistic dynamic process model in steady-state process optimizations covering the wide operational range of the proposed process. The optimization results show that the power demand can be varied in a range from 3.5 to 28 MW without violating operational constraints by changing the nitrogen and oxygen production rates. Thus, the proposed process is a promising air separation candidate for flexible operation with respect to fluctuating electricity markets.     

Binary whale optimization algorithm: a new metaheuristic approach for profit-based unit commitment problems in competitive electricity markets

This article presents a metaheuristic approach, the binary whale optimization algorithm (BWOA), to solve complex, constrained, non-convex, binary-nature profit-based unit commitment (PBUC) optimization problems of a price-taking generation company (GenCo) in the electricity market. To simulate the binary-nature PBUC problem, the continuous, real-value whale position/location is mapped into binary search space through various transfer functions. This article introduces three variants of BWOA using tangential hyperbolic, inverse tangent (arctan) and sigmoidal transfer functions. The effectiveness of the BWOA approaches is examined in test systems with different market mechanisms, i.e. an energy-only market, and energy and reserve market participation with different reserve payment methods. The simulation results are presented, discussed and compared with other existing approaches. The convergence characteristics, solution quality and consistency of the results across different BWOA variants are discussed. The superiority and statistical significance of the proposed approaches with respect to existing approaches is also presented.     

Modeling and optimization of ammonia process: Effect of hydrogen unit performance on the ammonia yield

The main object of this research is the development of a mathematical framework to simulate a commercial ammonia plant and obtaining the optimal operating conditions of process at steady state condition. The considered ammonia plant consists of steam and autothermal reforming reactors, low and high temperature shift converters, hydrogen purification section, methanation, and ammonia synthesis reactors. The catalytic reactors are heterogeneously modeled based on the mass and energy balance equations considering heat and mass transfer resistances in the gas and catalyst phases. In addition, an equilibrium model is applied to simulate the absorption column. Then, the accuracy of developed framework is investigated against plant data. The results show that the internal mass transfer resistance in the commercial catalyst limits the syngas production in the reforming section. In the second step, an optimization problem is formulated to enhance the ammonia production considering safety and operating limitations. The formulated optimization problem is handled employing the genetic algorithm. The results show that more syngas production in the optimized hydrogen unit is one of the main reasons for higher ammonia synthesis in the considered plant. Applying optimal conditions on the process increases ammonia production potential from 1890 to 2179 mol s⁻¹.     

300MW等级锅炉变工况低负荷稳燃能力数值模拟与预测

采用数值模拟软测量技术,在保证锅炉燃烧稳定和炉内温度较高水平的条件下,预测300 MW等级锅炉在实际运行中可降低到25%负荷稳定燃烧,并经过现场低负荷稳燃实验对结果进行验证。针对一次风速调整、磨煤机投运方式调整和配风方式及运行氧量调整三种方式对低负荷稳燃能力的影响进行分析,结果表明:在降负荷过程中调平一次风速偏差并适当降低一次风速,投运相邻层燃烧器,关小周界风,适当降低二次风量的同时适当降低运行氧量有利于提高低负荷稳燃特性。     

An improved cuckoo search algorithm and its application in vibration fault diagnosis for a hydroelectric generating unit

This article presents an improved cuckoo search (ICS) algorithm based on the parametric adaptation mechanism and non-uniform mutation. In the ICS algorithm, the biased random walk operator is modified to take advantage of the neighbourhood information of the current solution, and then the control parameters of step size, discovery probability and scaling factor are directly integrated into the optimized problems. Meanwhile, the non-uniform mutation operation is used to adaptively tune the search step of the current optimal solution. To evaluate the feasibility and efficiency of the presented algorithm, three groups of benchmark test functions are employed to perform the validation analysis. Subsequently, to diagnose the vibration fault of a hydroelectric generating unit, a combinational model is built, which combines ICS with a back-propagation neural network (ICSBP). The experimental results indicate that ICS is competitive on the optimization problems, and the ICSBP approach can effectively improve the accuracy of vibration fault diagnosis for a hydroelectric generating unit.     

基于遗传萤火虫算法的含风电电力系统机组组合研究

随着风能资源的广泛应用,机组组合问题求解愈显复杂。以减少煤耗费用提高系统经济性为目标,提出一种采用遗传萤火虫算法求解含风电电力系统机组组合问题的新方法。引入遗传算法双矩阵通路判断及约束修复策略,提高了初始解生成质量及产生速度;再利用萤火虫算法求解连续负荷经济优化分配,给出自适应交叉概率,从而提高了算法的收敛速度。应用所提算法对经典10机系统优化仿真表明,与其他算法相比,该方法能合理安排机组组合,提高系统供电的经济性,具有较好的实用价值。