Optimization of the Gas Generator in Composite Power System with Tip-Jet Rotor

The key and bottleneck of research on the tip-jet rotor compound helicopter lies in the power system. Computational Fluid Dynamics (CFD) was used to numerically simulate the gas generator and rotor inner passage of the tip-jet rotor composite power system, studying the effects of intake mode, inner cavity structure, propellant components, and injection amount on the characteristics of the composite power system. The results show that when a single high-temperature exhaust gas enters, the gas generator outlet fluid is uneven and asymmetric;when two-way high-temperature exhaust gas enters, the outlet temperature of the gas generator with a tilted inlet is more uniform than that with a vertical inlet;adding an inner cavity improves the temperature and velocity distribution of the gas generator's internal flow field;increasing the energy of the propellant is beneficial for improving the available moment.

Power Consumption Characteristics Research on Mobile System of Electrically Driven Large-Load-Ratio Six-Legged Robot

The electrically driven large-load-ratio six-legged robot with engineering capability can be widely used in outdoor and planetary exploration.However,due to the particularity of its parallel structure,the effective utilization rate of energy is not high,which has become an important obstacle to its practical application.To research the power consumption characteristics of robot mobile system is beneficial to speed up it toward practicability.Based on the configuration and walking modes of robot,the mathematical model of the power consumption of mobile system is set up.In view of the tripod gait is often selected for the six-legged robots,the simplified power consumption model of mobile system under the tripod gait is established by means of reducing the dimension of the robot’s statically indeterminate problem and constructing the equal force distribution.Then,the power consumption of robot mobile system is solved under different working conditions.The variable tendencies of the power consumption of robot mobile system are respectively obtained with changes in the rotational angles of hip joint and knee joint,body height,and span.The articulated rotational zones and the ranges of body height and span are determined under the lowest power consumption.According to the walking experiments of prototype,the variable tendencies of the average power consumption of robot mobile system are respectively acquired with changes in duty ratio,body height,and span.Then,the feasibility and correctness of theory analysis are verified in the power consumption of robot mobile system.The proposed analysis method in this paper can provide a reference on the lower power research of the large-load-ratio multi-legged robots.

自动驾驶环境下交通-配电网协同优化运行

为深入分析耦合电力-交通网在混行条件下产生的协同优化效果,提出自动驾驶环境下交通-配电网协同优化策略。建立智慧交通-配电系统协同运行框架,并分析自动驾驶与人工驾驶汽车的行驶特性,构建基于变分不等式的交通网动态混合均衡模型;结合基于二阶锥规划的配电网动态最优潮流模型,设计两阶段迭代求解算法实现耦合网络协同运行仿真。通过与现有单一车型场景及非协调运行情况对比分析,探究在需求高峰时段混行环境下的优化运行效果,最终结果证明了所提协同优化策略的优越性,使得网络综合运行成本相较现有场景有了显著降低,实现了自动驾驶汽车渗入这一新场景下的耦合网络优化运行。

融合K-means聚类和序列分解的实车锂电池剩余使用寿命预测

电动汽车锂离子动力电池健康状态(SOH)衰退过程受使用工况影响存在较多波动,导致模型预测精度下降,在锂电池剩余使用寿命(RUL)短期预测时,SOH波动情况不可忽略,为了准确预测SOH短期内波动情况,须从实车上传的锂电池运行数据中提取有效的健康因子。本文建立一种联合分布特征输入和序列分解融合的锂电池RUL预测方法,使用K-means聚类方法构建车辆锂电池运行过程的联合分布特征,并通过S-G滤波器对SOH衰退曲线进行序列分解,分别使用长短时记忆神经网络(LSTM)和多层感知机(MLP)对趋势部分和波动部分进行预测,融合得到最终预测结果。理论分析和实车采集数据验证表明,融合模型可以在预测车辆锂电池RUL短期衰退趋势的同时预测SOH的波动情况,有较高的短期预测精度。

面向新型电力系统运行的数据-物理融合建模综述

构建新型电力系统是我国实现碳达峰、碳中和目标的关键,将给电力工业带来深刻变革与挑战。数据-物理融合建模(简称融合建模)是一类新兴的建模技术,能够同时发挥物理机理与数据的价值,有望成为新型电力系统重要的分析工具。为此,该文首先梳理融合建模的相关概念与应用场景,讨论近年来国内外的研究趋势与热点。进而从技术特征和融合模式两方面,提出针对融合模型的分析框架。同时,聚焦于新型电力系统运行领域,全方位总结整理融合建模在应对现有技术挑战方面的潜在优势及不足,并展望未来研究与工程实践的重点发展领域。

高功率腔体滤波器的电磁-热-力多物理场智能代理模型及快速预测

电磁多物理场计算在模拟高功率微波器件方面至关重要。为了快速且精确地获取高功率腔体滤波器中由电磁引发的多物理场响应,本文构建了一种基于数据驱动的电磁多物理场代理模型。首先利用有限元方法建立腔体滤波器的多物理场响应数据库,随后基于该数据库构建数据驱动的人工神经网络代理模型。结果对比表明:该代理模型能够精确且快速地预测高功率腔体滤波器在不同输入功率下的S参数曲线,预测精度超过98%,预测时间少于0.2 s;相较于传统的电磁多物理场数值计算方法,计算速度提升了3个数量级以上。因此,本文代理模型的快速精确预测能力对新型高功率微波器件的稳定性分析、可靠性评估和优化设计具有重要的理论指导意义和实际工程应用价值。

融合拓扑信息的配电网电压-功率灵敏度估计数据驱动方法

为解决配电网量测数据多重共线性导致电压-功率灵敏度估计精度低的问题,提出融合拓扑信息的数据驱动方法.首先,将电压-功率灵敏度矩阵分解为主成分矩阵和次成分矩阵两部分,其中主成分与配电网拓扑密切相关,次成分为主成分与实际值的误差.然后,分两阶段依次估计主成分和次成分,分别建立基于二次规划的数据驱动模型.第一阶段模型的关键是基于配电网拓扑信息的约束,第二阶段模型的关键是次成分与主成分比值为微小量的约束.最后,采用实际配电网量测数据和IEEE 33节点系统验证所提方法的精度和效率,并与常规最小二乘回归、岭回归、LASSO回归方法对比,仿真结果表明所提方法的精度具有数量级的显著提升.

基于自编码器-受限时序卷积网络的数据驱动配电网无功优化策略

配电网中可再生能源渗透率的提高带来了频繁的电压越限问题。作为一种被广泛研究的方法,无功优化方法已经成功应用到配电网中以降低网损、优化电压质量。该文提出一种基于自编码器-受限时序卷积网络的新型数据驱动配电网无功优化策略,该策略通过3个阶段来协调光伏逆变器、电容器组等多种多时间尺度的无功调节设备。首先,将无功优化问题建模为混合整数二阶锥规划问题,求解出历史最优无功调度策略;然后,使用历史运行数据和最优策略训练所提网络模型,并通过矫正层规避不合理结果;在实际运行中,训练好的模型依据系统测量值给出无功优化策略以应对配电网的波动。最后,通过改进IEEE 33节点算例仿真实验验证,所提方法能够达到混合整数二阶锥模型98.80%的准确度而仅消耗其7.14%的时间;与其他流行的深度学习方法相比,具有更佳的性能和更好的实用性。

基于BWOA-GAM-BiGRU的火电厂SCR系统出口NOx排放预测

提出了一种基于数据驱动结合全局注意力机制与双向门控循环单元深度神经网络的选择性催化还原系统出口NOx排放预测模型,并使用黑寡妇优化算法对网络超参数进行自动寻优。对某300MW电厂选择性催化还系统的历史运行数据进行深度挖掘,确定模型输入变量并校准各输入变量与NOx排放量之间的时延并重构样本序列。实验结果显示,所提出模型的预测结果比典型预测模型具有更高预测精度和更好的泛化能力。

基于GA-ADAM优化的BPNN配电网潮流计算

潮流计算是电力系统运行与控制的基础。为解决配电网可再生能源渗透率不断增加带来的负荷点电压波动的不确定性,以及传统电力系统潮流数据收集能力不足导致潮流计算不准确等问题。本文提出了一种基于数据驱动的潮流分析模型,构建了一种基于BPNN结合GA-ADAM优化算法模型来分析随机性下配电网的潮流计算方法。首先,引入潮流初值信息、拓扑结构特征以及功率因数指标构建训练集,通过对回归模型的训练,充分挖掘节点电压与功率之间的映射关系。其次,使用GA-ADAM算法优化模型初值和权重参数。最后,基于IEEE-33节点配电网模型进行验证,本文模型潮流计算的最大误差3.93×10^(-3),平均绝对误差1.46×10^(-3),均方根误差1.81×10^(-3),优化后的BPNN潮流计算电压误差值降低37.66%。实际算例仿真结果表明,与其他方法比较,本文构建的模型各误差指标小、准确度高,提高了潮流计算的效率和准确性。

基于改进小波包结合CS-BP的地面驱动螺杆泵故障诊断

针对目前地面驱动螺杆泵故障诊断存在效率不高、精度不足、损耗资源的问题,提出通过引入功率谱细化的思想改进小波包变换,再结合布谷鸟搜索(cuckoo search,CS)优化反向传播(back propagation,BP)神经网络的诊断方法。首先,通过改进的小波变换对螺杆泵有功功率分解重构得到特征向量;其次,与瞬时流量、进口回压等参数进行归一化处理,作为BP神经网络的输出层信息;再次,使用布谷鸟搜索寻优得到BP神经网络的权值和阈值,建立CS-BP故障诊断模型;最后,应用于螺杆泵不同故障类型的诊断,并通过与目前的主流诊断方法进行诊断效果的分析比较。结果表明,对于螺杆泵不同类型故障诊断的平均精度达到95.6%,对比分析证明了所提方法的可行性与优越性。

Environmental life cycle assessment of Indian coal-fired power plants

Coal is the backbone of the Indian power sector. The coal-fired power plants remain the largest emitters of carbon dioxide, sulfur dioxide and substantial amounts of nitrogen oxides, which are associated with climate and health impacts. Various CO2 mitigation technologies （carbon capture and storage--CCS） and SO2/NOx mitigation technologies （flue gas desulfurization and selective catalytic reduction） have been employed to reduce the environmental impacts of the coal-fired power plants. Therefore, it is imperative to understand the feasibility of various mitigation technologies employed. This paper attempts to perform environmental life cycle assessment （LCA） of Indian coal-fired power plant with and without CO2, SO2 and NOx mitigation controls. The study develops new normalization factors for India in various damage categories, using the Indian emissions and energy consumption data, coupled with the emissions and particulate emission to come up with a final environmental impact of coal-fired electricity. The results show a large degree of dependence on the perspective of assessment used. The impact of sensitivities of individual substances and the effect of plant efficiency on the final LCA results is also studied.

Multi-train modeling and simulation integrated with traction power supply solver using simplified Newton–Raphson method

Multi-train modeling and simulation plays a vital role in railway electrification during operation and planning phase. Study of peak power demand and energy consumed by each traction substation needs to be deter- mined to verify that electrical energy flowing in its railway power feeding system is appropriate or not. Gauss-Seidel, conventional Newton-Raphson, and current injection methods are well-known and widely accepted as a tool for electrical power network solver in DC railway power supply study. In this paper, a simplified Newton-Raphson method has been proposed. The proposed method employs a set of current-balance equations at each electrical node instead of the conventional power-balance equation used in the conventional Newton-Raphson method. This concept can remarkably reduce execution time and computing complexity for multi-train simulation. To evaluate its use, Sukhumvit line of Bangkok transit system （BTS） of Thai- land with 21.6-km line length and 22 passenger stopping stations is set as a test system. The multi-train simulation integrated with the proposed power network solver is developed to simulate 1-h operation service of selected 5-min headway. From the obtained results, the proposed method is more efficient with approximately 18 % faster than the conventional Newton-Raphson method and just over 6 % faster than the current injection method.

Neutronics Optimization of LiPb-He Dual-Cooled Fuel Breeding Blanket for the Fusion-Driven sub-critical System

The concept of the liquid Li17Pb83 and Helium gas dual-cooled Fuel Breeding Blanket (FBB) for the Fusion-Driven sub-critical System (FDS) is presented and analyzed. Taking self-sustaining tritium (TBR >1.05) and annual output of 100 kg or more fissile 239Pu (FBR > 0.238) as objective parameters, and based on the three-dimensional Monte Carlo neutron-photon transport code MCNP/4A, a neutronics-optimizated calculation of different cases was carried out and the concept is proved feasible. In addition, the total breeding ratio ( BR = TBR + FBR ) is listed corresponding to different cases.

基于CNN-SVM的核电厂轴承故障诊断方法

为提升核电厂旋转机械部件的故障诊断准确率,以及增强诊断模型泛化能力,本文提出了一种基于卷积神经网络和支持向量机的滚动轴承故障诊断方法。对轴承原始振动信号进行连续小波变换,得到其时频图;然后,使用预训练好的卷积基对小波时频图进行特征提取,获取深层特征,并将这些深层特征正则化处理后,使用主成分分析法对其进行降维;将得到的特征数据输入到基于粒子群优化的支持向量机中,从而实现滚动轴承的故障诊断。实验结果表明:该方法对不同负载工况下的多类滚动轴承故障具有良好的诊断效果,并且在噪声干扰下也能保持较好的效果,与其他方法相比,其抗噪稳定性更好,泛化能力更强。

Key Problems of Cold Power Spinning of Ti-15-3 Alloy

The key problems of cold power spinning of Ti-15-3 alloy are studied. Reasonable billet preparation methods are presented to improve crystal structure and avoid crack of billet. Influences of original wall thickness, reduction rate and feed rate on expanding in diameter are analyzed and some methods to prevent expanding in diameter are given.

Characterization of Self-driven Cascode-Configuration Synchronous Rectifiers

This paper presents a cascode configuration synchronous rectifier device based on silicon MOSFET and Schottky diode,which can replace traditional power diode directly.This structure has self-driven ability with simple external circuit,and the conduction characteristic is preferable to a power diode.Static characterization and switching behavior analysis of proposed structure are conducted in this paper.The switching process is illustrated in detail using real model which considers the parasitic inductances and the nonlinearity of junction capacitors.The real time internal voltage and current value during switching transition are deduced with the equivalent circuit.To validate the analysis,two voltage specification rectifiers are built.Finally,double-pulse test results and the practical design example verify the performance advantages of proposed structure.

DC-DC变换器事件触发仿真方法的参数选择与精度提升方法研究

电力电子变换器的高阶事件触发仿真方法缺乏对参数选择及仿真精度关系的研究。结合电力电子变换器的特点,基于事件触发的理论对电力电子变换器仿真过程进行分析,并提出一套基于事件触发算法实现的电力电子变换器仿真方法。针对多组变换器并联与考虑寄生参数瞬态过程2类变换器典型病态问题进行研究与测试,并归纳了算法阶数及量子大小的选取与仿真精度的非线性关系,总结得到不同问题下电力电子变换器事件触发仿真的参数选择及仿真精度优化方法。仿真结果验证了事件触发方法仿真的可行性和拓展性。

Investigation on some key problems of large power AC-DC-AC converter

China is an important country in iron and steel industry.Power electronics converters are widely used.For the cold rolling mills of high speed,AC-DC-AC converters should be used.In the paper,the design and the control system of the large power three-level AC - DC - AC converter with IGCTs is investigated,and a back-to-back large power three-level AC - DC - AC converter with IGCTs has been got. With a series experiments,the performance of the converter is examined.The experiment result indicates the converter reaches the design requirement and it shows excellent performance.The converter system has been put into use safely.It is estimated that the AC - DC - AC converter system will be used in the drive systems for rolling mills in the near future.

考虑大规模风光分层接入的配电网多层协调无功优化方法

大量风光新能源分层、多点接入给配电网运行带来了电压越限等负面影响,增加了不同电压等级无功协同优化的难度。兼顾不同电压等级调节需求,从模型降维等值的角度,提出了基于等值模型的配电网多层协调无功优化方法。该方法分别针对含有无功调节设备及没有无功调节设备的两种台区系统,利用神经网络对大量台区相关运行数据进行训练得到台区拟合模型,形成不可控和可控两种类型的台区等值模型,并用这两类拟合模型分别代替两类台区系统的物理模型,使台区以数据驱动的方式参与配电网无功优化,形成馈线物理模型和台区拟合模型组成的单一电压等级物数混合优化调度模型。将原多层无功优化问题转换为单层系统优化问题,再对该单层系统无功优化调度问题进行求解。该方法可降低配电网系统优化计算规模,从而减小计算量,以无功优化数学模型与数据驱动方法相结合的方式,实现配电网馈线-台区多层协调无功优化。通过算例验证了所提方法对于解决分布式风光分层接入所导致电压越限问题的可行性、有效性和优越性,能够保障配电网的经济安全稳定运行。