A probabilistic load shedding concept considering highly volatile local generation

Automatic load shedding is the ultimate countermeasure against imbalance in a power system and can effectively help preventing large blackouts. Taking into account a high penetration of renewable energy sources (RES) in the distribution grid, a clear distinction between load and generation at the PCC becomes increasingly more difficult. For that reason an adaptation of frequency relay parameters and their locations of installation are necessary. In Europe this is rest on a multi-step plan based on values such as the yearly peak load. In this paper a novel probabilistic method for automatic load shedding is presented that uses the average values instead of peak values for load shedding. Its applicability is verified by a dynamic power system model that was developed to compare the classical and novel probabilistic load shedding principle. The method is verified using data from a German TSO.     

Degradation analysis of the core components of metal plate proton exchange membrane fuel cell stack under dynamic load cycles

The durability of metal plate proton exchange membrane fuel cell (PEMFC) stack is still an important factor that hinders its large-scale commercial application. In this paper, we have conducted a 1000 h durability test on a 1 kW metal plate PEMFC stack, and explored the degradation of the core components. After 1000 h of dynamic load cycles, the voltage decay percentage of the stack under the current densities of 1000 mA cm^?2 is 5.67%. By analyzing the scanning electron microscopy (SEM) images, the surfaces of the metal plates are contaminated locally by organic matter precipitated from the membrane electrode assembly (MEA). The SEM images of the catalyst coated membrane (CCM) cross section indicate that the MEA has undergone severe degradation, including the agglomeration of the catalyst layer, and the thinning and perforation of the PEM. These are the main factors that cause the rapid increase in hydrogen crossover flow rate and performance decay of the PEMFC stack.     

Selection of features from power theories to compose NILM datasets

The load disaggregation concept is gaining attention due to the increasing need for optimized energy utilization and detailed characterization of electricity consumption profiles, especially through Nonintrusive Load Monitoring (NILM) approaches. This occurs since knowledge about individualized consumption per appliance allows to create strategies striving for energy savings, improvement of energy efficiency, and creating energy awareness to consumers. Moreover, by using feature extraction to devise energy disaggregation, one can achieve accurate identification of electric appliances. However, even though several literature works propose distinct features to be utilized, no consensus exists in the literature about the most appropriate set of features that ensure high accuracy on load disaggregation. Thus, beyond presenting a critical analysis of some significant features often selected in the literature, this paper proposes identifying the most relevant ones considering collinearity and machine learning algorithms. The results show that high-performance metrics can be achieved with fewer features than usually adopted in the literature. Moreover, it is demonstrated that the Conservative Power Theory can offer the most representative features for appliance identification, leading to efficient power consumption disaggregation.     

Failure load prediction and optimisation for adhesively bonded joints enabled by deep learning and fruit fly optimisation

Adhesively bonded joints have been extensively employed in the aeronautical and automotive industries to join thin-layer materials for developing lightweight components. To strengthen the structural integrity of joints, it is critical to estimate and improve joint failure loads effectually. To accomplish the aforementioned purpose, this paper presents a novel deep neural network (DNN) model-enabled approach, and a single lap joint (SLJ) design is used to support research development and validation. The approach is innovative in the following aspects: (i) the DNN model is reinforced with a transfer learning (TL) mechanism to realise an adaptive prediction on a new SLJ design, and the requirement to re-create new training samples and re-train the DNN model from scratch for the design can be alleviated; (ii) a fruit fly optimisation (FFO) algorithm featured with the parallel computing capability is incorporated into the approach to efficiently optimise joint parameters based on joint failure load predictions. Case studies were developed to validate the effectiveness of the approach. Experimental results demonstrate that, with this approach, the number of datasets and the computational time required to re-train the DNN model for a new SLJ design were significantly reduced by 92.00% and 99.57% respectively, and the joint failure load was substantially increased by 9.96%.     

移动式计量装置验收专用负荷箱的研制

本项目着力研发一种移动式计量装置验收专用负荷箱,可依据现场实际情况将其接入到专变低压出线处,提供稳定的测试负荷电流,完成计量装置验收关键步骤。主要的技术内容:通过接入电容器组,提供计量装置验收带负荷测试所需的电流,按不同容量电容器组配置合适分组空气开关,保护电容器组,降低同时投入时的冲击电流。本项目制作的计量装置验收专用负荷箱将使用高强度箱体,并制作不同容量的负荷箱以满足不同的计量装置验收负荷要求,以提高计量装置验收工作质量和率,降低电能计量差错风险。     

真空热处理炉布料矩阵优化仿真分析

为了获得更高的加热效率和更好的温度均匀性,采用有限元软件建立了真空热处理炉加热过程仿真模型,并耦合PID算法用于温度控制。通过与实测温度对比,验证了仿真模型的准确性。借助该模型,模拟研究了布料矩阵对两种典型形状零件在真空热处理炉内加热特性的影响。模拟装炉时基于零件几何形状特征,对圆棒形工件采用顺排、叉排和环形排列3种形式,对圆盘形工件采用横排式和竖排式。研究结果表明:尽管零件形状和数量相同,但是随着布料矩阵的变化,加热效率和温度均匀性都会改变。对于圆棒形工件,采用环形排列不仅可以提高内部工件的加热速率,而且相较于叉排式可以将最大温差减小36 ℃;对于圆盘形工件,由水平式改为竖直式布料可以将最大温差由248 ℃减小至171 ℃。     

Study on the relationship between the particle size distribution and the effectiveness of the K‐powder fire extinguishing agent

The relationship between the particle size distribution and the extinguishing effectiveness of the new K‐powder fire extinguishing agent has been studied experimentally, to explore the reason of the great extinguishing efficiency exhibited by the new K‐powder fire extinguishing agent on Class B fire (liquid fuel fire). The results of the experiment showed that the extinguishing effectiveness increased along with the decrease of the particle size distribution. In addition, a sharp discontinuity appeared around the limiting size, about 40 μm. The powder with the particle size below 40 μm exhibited highly effective extinguishing with the minimum effective extinguishing concentration C_xr = 23 g·m^?3, while the powder with the particle size above 40 μm exhibited little fire extinguishing efficiency. Compared with other fire extinguishing agents produced by different substances, the new K‐powder fire extinguishing has the bigger limiting size. That means, in the same particle size distribution, the new K‐powder fire extinguishing agent contains more highly effective powder than others contain, and is more effective.     

Reliability of design approaches for axially loaded offshore piles and its consequences with respect to the North Sea

In the near future, several offshore wind farms are planned to be built in the North Sea. Therefore, jacket and tripod constructions with mainly axially loaded piles are suitable as support structures. The current design of axial bearing resistance of these piles leads to deviant results regarding the pile resistance when different design methods are adopted. Hence, a strong deviation regarding the required pile length must be addressed. The reliability of a design method can be evaluated based on a model error which describes the quality of the considered design method by comparing measured and predicted pile bearing resistances. However, only few pile load tests are reported with regard to the boundary conditions in the North Sea. This paper presents 6 large-scale axial pile load tests which were incorporated within a new model error approach for the current design methods used for the axial bearing resistance, namely API Main Text method and cone penetration test (CPT)-based design methods, such as simplified ICP-05, offshore UWA-05, Fugro-05 and NGI-05 methods. Based on these new model errors, a reliability-based study towards the safety was conducted by performing a Monte-Carlo simulation. In addition, consequences regarding the deterministic pile design in terms of quality factors were evaluated. It is shown that the current global safety factor (GSF) prescribed and the partial safety factors are only valid for the API Main Text and the offshore UWA-05 design methods; whereas for the simplified ICP-05, Fugro-05 and NGI-05 design methods, an increase in the required embedded pile length and thus in the GSF up to 2.69, 2.95 and 3.27, respectively, should be considered to satisfy the desired safety level according to DIN EN 1990 of β = 3.8. Further, quality factors for each design method on the basis of all reliability-based design results were derived. Hence, evaluation of each design method regarding the reliability of the pile capacity prediction is possible.     

考虑温度影响的排气系统断裂原因仿真分析

针对某汽车排气系统在使用中发生断裂故障的现象,采用有限元方法,考虑实际工况中温度的影响,对排气系统进行热模态与热疲劳性能仿真分析。得出在高温载荷作用下,排气系统的模态频率有所下降,某阶模态频率下降至发动机激励频率附近。排气系统在高温使用工况下的疲劳寿命大幅下降,且疲劳寿命最小处与实际断裂位置相同。得出了高温环境对排气系统疲劳性能有重要影响,而结构中存在的共振现象进一步加剧了排气系统的疲劳失效,确定了排气系统断裂故障产生的主要原因。     

生物滴滤床法降解二氯甲烷废气的因素影响特征

二氯甲烷作为溶剂广泛应用于制药行业，其挥发性废气对人类健康和大气环境的危害极大。本文采用生物滴滤床对某制药厂浓度范围在0.02~2g/m³的二氯甲烷废气进行了为期132天的中试规模实验。在适宜的停留时间、温度、喷淋量和pH等实验条件下，控制适当的进气浓度可得到高效去除效率并且废气出口浓度达标。实验揭示了生物膜内生物降解是过程的限制因素，结果表明，在喷淋量为1200L/h、进气浓度范围为0.45~0.65g/m³时该生物系统去除效率最高可达98.9%，最大去除负荷可达EC_max=155.25g/(m³·h)。随着进气浓度的增加，去除负荷随之增大，而去除效率下降，废气出口浓度超标，表明生物滴滤系统已处于反应控制。此外，间歇实验表明，该生物系统具有良好的稳定性。指出生物滴滤床的设计、运行取决于当地的二氯甲烷废气排放标准。