Economic Evaluation of Power System Flexibility by Commercial Air Conditioner Control with Large Penetration of Photovoltaic Generation

High penetration of intermittent renewable energy such as photovoltaic (PV) and wind power could cause shortage of power system flexibility. Demand response is expected to help supply ancillary service instead of the conventional power plant. Commercial air conditioners are a promising responsive load for demand response because they account for a large proportion of power consumption in the power system. We calculate a system operation cost and hourly operation pattern of each power plant by using the optimal power generation model considering flexibility supply from controlling commercial air conditioner. We obtained the following results as an effect of commercial air conditioner control. (1) The power generation of oil fired power plants decreases at peak time and annual fuel cost of oil fired plant is reduced by approximately 30% at most in Kanto area. (2) The percentage of rated operation mode of LNG combined cycle plants increases. (3) Curtailed energy rate of PV decreases because a power storage amount by pumped hydropower generation increases. (4) Required battery capacity to reduce PV curtailed amount decreased by combining battery energy storage system in case of high penetration of PV.     

The control of paracetamol particle size and surface morphology through crystallisation in a spray dryer

The parameters governing the crystallisation of paracetamol using various conventional techniques has been extensively studied, however the factors influencing the drug crystallisation using spray drying is not as well understood. The aim of this work was to investigate the crystallisation of an active pharmaceutical ingredient through evaporative crystallisation using a spray dryer to study the physicochemical properties of the drug and to use semi-empirical equations to gain insight into the morphology and particle size of the dried powder. Paracetamol solutions were spray dried at various inlet temperatures ranging from 60 °C to 120 °C and also from a series of inlet feed solvent compositions ranging from 50/50% v/v ethanol/water to 100% ethanol and solid-state characterisation was done. The size and morphology of the dried materials were altered with a change in spray drying parameters, with an increase in inlet temperature leading to an increase in particle Sauter mean diameter (from 3.0 to 4.4 µm) and a decrease in the particle size with an increase in ethanol concentration in the feed (from 4.6 to 4.4 µm) as a result of changes in particle density and atomised droplet size. The morphology of the dried particles consisted of agglomerates of individual crystallites bound together into larger semi-spherical agglomerates with a higher tendency for particles having crystalline ridges to form at higher ethanol concentrations of the feed.     

Adaptive neuro-fuzzy algorithm applied to predict and control multi-phase flow rates through wellhead chokes

A Takagi-Sugeno adaptive neuro-fuzzy inference system (TSFIS) model is developed and applied to a dataset of wellhead flow-test data for the Resalat oil field located offshore southern Iran, the objective is to assist in the prediction and control of multi-phase flow rates of oil and gas through the wellhead chokes. For this purpose, 182 test data points (Appendix 1) related to the Resalat field are evaluated. In order to predict production flow rate (Q_L) expressed as stock-tank barrels per day (STB/D), this dataset includes four selected input variables: upstream pressure (Pwh); wellhead choke sizes (D64); gas to liquid ratio (GLR); and, base solids and water including some water-soluble oil emulsion (BS&W). The test data points evaluated include a wide range of oil flow rate conditions and values for the four input variables recorded. The TSFIS algorithm applied involves five data processing steps: a) pre-processing, b) fuzzification, c) rules base and adaptive neuro-fuzzy inference engine, d) defuzzification, and e) post-processing of the fuzzy model. The developed TSFIS model for the Resalat oil field database predicted oil flow rate to a high degree of accuracy (root mean square error = 247 STB/D, correlation coefficient = 0.9987), which improves substantially on the commonly used empirical algorithms used for such predictions. TSFIS can potentially be applied in wellhead choke fuzzy controllers to stabilize flow in specific wells based on real-time input data records.     

Fluid flow and heat transfer with nail dipping method in mould during continuous casting process

ABSTRACT

The character and cause of sliver defect on IF steel sheet surface are studied by means of SEM, unstable flow in mould could induce surface velocity and level fluctuations, leading to surface defects during continuous casting of steel. The nozzle clogging is a serious problem during the continuous casting of steel, due to its influence on the casting operations and products quality. In this study, the nail dipping method for measuring surface velocity and flow direction in molten steel were employed. The fluid flow in mould of whole casting sequence was investigated, especially during the nozzle clogging conditions. The results showed that when nozzle clogging occurred in the 7th heat, the flow velocities on R and L side of nozzle were 0.280 and 0.402?m/s, respectively. The surface defect ratio of hot-rolled and cold-rolled plates increases with the increase of heat flux deviation on both sides of the mould copper. The different clogging per cent on both sides of the nozzle will lead to asymmetry flow, the surface velocity is higher with the small clogging per cent side compared to that of relatively large per cent clogging side.     

大方坯结晶器电磁搅拌器结构优化

为改善连铸结晶器内钢液的流动状况，采用有限元法和有限容积法研究了大方坯结晶器电磁搅拌器结构对连铸结晶器内电磁场、流场和温度场分布的影响。结果表明，新型结晶器电磁搅拌器在400 A、3 Hz时产生的电磁力比传统结晶器电磁搅拌器在500 A、3 Hz时产生的电磁力更加均匀，对结晶器内钢液的扰动更强，可提高结晶器内的传热效率，有助于初始凝固坯壳和等轴晶的形成，改善方坯质量。     

基于多层感知器的气液两相流流型识别方法

通过对电阻层析成像数据采集原理和深度学习网络的研究,提出了一种基于阵列电阻值和多层感知器深度学习网络相结合的流型识别方法。利用电阻层析成像系统中的16个电极传感器来获取流型样本数据,并构建出流型识别数据库,然后对多层感知器深度学习网络进行训练,获得可以识别不同流型的网络。实验结果表明,采用阵列电阻值结合多层感知器网络对流型进行学习和识别的方法,流型识别准确率可以达到95%,解决了流型图像生成过程与数据特征预选过程中流型特征损失的问题,流型识别性能得到了提高。     

Unsteady natural convection magnetohydrodynamic stagnation point flow with assisting and opposing characteristics: Buongiorno model

In this investigation, the flow of an unsteady mixed convection boundary layer viscous nanofluid on a stretchable sheet is considered. The flow examination is affected by a magnetic field. The reason for the examination exhibited is to create models for nanomaterials that incorporate the Brownian movement and thermophoresis phenomena. The created nonlinear standard differential condition is illuminated numerically utilizing the Runge-Kutta-Gill technique and the start program. The different factors of speed, temperature, and concentration are reported and discussed. The examination shows that the speed, temperature, and concentration are lower in contrast with the consistent stream on account of an assisting flow, whereas the opposite situation is noticed in the opposing flow case. The effects of Brownian movement and thermophoresis in the concentration case are totally different.     

入口长度对旋转直通式迷宫气封流场及流场力的影响

迷宫密封的转子和定子部件之间的流场和流场力直接影响转子的振动和稳定性。为了深入了解迷宫密封的流场和流场力特性,选取旋转直通式迷宫气封为研究对象,利用稳态CFD分析方法,研究密封入口长度对旋转直通式迷宫气封泄漏、流场和流场力的影响。考虑和不考虑入口预旋的影响,计算不同入口长度的旋转直通式迷宫气封的泄漏量、流场速度流线、总压强分布、流体压力和流体黏滞力。结果表明:随着入口长度的增大,密封流场泄漏量先增加后减小,转子表面流体压力和流体黏滞力先增加后快速减小;入口长度影响着直通式迷宫气封流场力,存在一个特定的入口长度,使转子表面的流体压力和流体黏滞力最大;当考虑入口预旋时,泄漏量、流体压力和流体黏滞力均有所减小。     

某型发动机自反馈调节阀动态仿真分析

基于FLUENT软件提供的计算方法和物理模型，利用动网格技术及用户自定义函数（User-define Function，UDF），对发动机预燃室调节阀的自反馈调节过程进行动态数值模拟，并分析阻尼参数对调节效果的影响。结果表明：自反馈机构可实现对不同压力扰动的及时响应，具有稳定流量的效果，改变阻尼参数可对调节响应速度和流量稳定性进行优化，其中摩擦力对调节影响最显著。