Impact of Electric Vehicles on a Carbon Constrained Power System—A Post 2020 Case Study

Electric vehicles (EVs) offer great potential to move from fossil fuel dependency in transport once some of the technical barriers related to battery reliability and grid integration are resolved. The European Union has set a target to achieve a 10% reduction in greenhouse gas emissions by 2020 relative to 2005 levels. This target is binding in all the European Union member states. If electric vehicle issues are overcome then the challenge is to use as much renewable energy as possible to achieve this target. In this paper, the impacts of electric vehicle charged in the all-Ireland single wholesale electricity market after the 2020 deadline passes is investigated using a power system dispatch model. For the purpose of this work it is assumed that a 10% electric vehicle target in the Republic of Ireland is not achieved, but instead 8% is reached by 2025 considering the slow market uptake of electric vehicles. Our experimental study shows that the increasing penetration of EVs could contribute to approach the target of the EU and Ireland government on emissions reduction, regardless of different charging scenarios. Furthermore, among various charging scenarios, the off-peak charging is the best approach, contributing 2.07% to the target of 10% reduction of Greenhouse gas emissions by 2025.

Loss-of-Main Monitoring and Detection for Distributed Generations Using Dynamic Principal Component Analysis

In this paper, our previous work on Principal Component Analysis (PCA) based fault detection method is extended to the dynamic monitoring and detection of loss-of-main in power systems using wide-area synchrophasor measurements. In the previous work, a static PCA model was built and verified to be capable of detecting and extracting system faulty events;however the false alarm rate is high. To address this problem, this paper uses a well-known ‘time lag shift’ method to include dynamic behavior of the PCA model based on the synchronized measurements from Phasor Measurement Units (PMU), which is named as the Dynamic Principal Component Analysis (DPCA). Compared with the static PCA approach as well as the traditional passive mechanisms of loss-of-main detection, the proposed DPCA procedure describes how the synchrophasors are linearly auto- and cross-correlated, based on conducting the singular value decomposition on the augmented time lagged synchrophasor matrix. Similar to the static PCA method, two statistics, namely T2 and Q with confidence limits are calculated to form intuitive charts for engineers or operators to monitor the loss-of-main situation in real time. The effectiveness of the proposed methodology is evaluated on the loss-of-main monitoring of a real system, where the historic data are recorded from PMUs installed in several locations in the UK/Ireland power system.

A review on COLREGs-compliant navigation of autonomous surface vehicles:From traditional to learning-based approaches

A growing interest in developing autonomous surface vehicles(ASVs)has been witnessed during the past two decades,including COLREGs-compliant navigation to ensure safe autonomy of ASVs operating in complex waterways.This paper reviews the recent progress in COLREGs-compliant navigation of ASVs from traditional to learning-based approaches.It features a holistic viewpoint of ASV safe navigation,namely from collision detection to decision making and then to path replanning.The existing methods in all these three stages are classified according to various criteria.An in-time overview of the recently-developed learning-based methods in motion prediction and path replanning is provided,with a discussion on ASV navigation scenarios and tasks where learning-based methods may be needed.Finally,more general challenges and future directions of ASV navigation are highlighted.

Residential electrical vehicle charging strategies:the good,the bad and the ugly

In recent years,a wide variety of centralised and decentralised algorithms have been proposed for residential charging of electric vehicles(EVs).In this paper,we present a mathematical framework which casts the EV charging scenarios addressed by these algorithms as optimisation problems having either temporal or instantaneous optimisation objectives with respect to the different actors in the power system.Using this framework and a realistic distribution network simulation testbed,we provide a comparative evaluation of a range of different residential EV charging strategies,highlighting in each case positive and negative characteristics.

1.12MW高速永磁电机多物理场综合设计

高速电机设计时即要满足电磁性能要求,又要满足机械特性的要求,还需满足冷却与温升的要求,因此高速电机的设计是一个多物理场迭代综合设计过程。针对高速电机的多物理场一体化设计过程,本文基于电磁场-转子强度-转子动力学-流体场与温度场等对一台1.12MW,18 000r/min的高速永磁电机进行了综合设计,在多物理场仿真分析的基础上,得到了满足电磁性能、转子强度、临界转速和电机温升的综合设计结果,并加工了一台样机,进行了电机性能实验、转子机械特性实验以及温升实验,实验结果与计算结果相吻合,验证了本文仿真分析与设计方法的可行性,对大功率高速永磁电机的设计与发展具有一定的借鉴意义。

1.12MW高速永磁电机不同冷却方案的温度场分析

针对大功率高速永磁电机体积小、损耗密度大、散热困难且永磁体在高温下易发生不可逆退磁的问题,本文基于一台1.12MW,18 000r/min的高速永磁电机,设计了混合通风螺旋水道、轴向通风螺旋水道以及轴向通风直槽水道三种风冷与水冷相结合的散热方案,并建立了三种方案的温度场计算模型,基于流固耦合法,对三种方案的温度分布进行了比较与分析,同时基于轴向通风螺旋水道的冷却方案,加工了一台样机,并进行了温升实验,实验结果与计算结果相吻合,验证了仿真分析的正确性,对大功率高速永磁电机的设计与发展具有一定的借鉴意义。

Introduction to the Special Issue on Advanced Security for FutureMobile Internet:A Key Challenge for the Digital Transformation

Mobile internet technologies have transformed our daily lives,allowing us to connect,communi-cate,and access various services and applications anytime and anywhere.These technologies are set to play a significant role in the next generation of digital transformation,further increasing their impact by integrating with emerging technologies like 6G,quantum computing,and generative AI.

Multi-person vision tracking approach based on human body localization features

This paper presents a multi-person vision tracking approach based on human body localization features to address the problem of interactive object localization and tracking in a home monitoring scenario.Firstly,the human body localization model is used to obtain the 3D position of the human body,which is then used to construct the human body motion model based on the Kalman filter method.At the same time,the human appearance model is constructed by fusing human color features and features of the histogram of oriented gradient to better characterize the human body.Secondly,the human body observation model is constructed based on the human body motion model and appearance model to measure the similarities between the human body state sequence in the historical frame and the human body observation result in the current frame,and the cost matrix is then obtained.Thirdly,the Hungarian maximum matching algorithm is employed to match each human body in the current and historical frames,and the exception detection mechanism is simultaneously constructed to further reduce the probability of human tracking and matching failure.Finally,a multi-person vision tracking verification platform was constructed,and the achieved average accuracy was 96.6%in the case of human body overlapping,occlusion,disappearance,and appearance;this verifies the feasibility and effectiveness of the proposed method.

非参数非线性系统的变量选择及研究进展

本文考虑非参数非线性系统的变量选择问题,所谓变量选择是指,判断哪些变量对系统的输出有实质性影响并构造算法将它们辨识出来.由于"维数灾难",非线性系统随着维数增加而使得辨识需要的数据量呈指数速度上升,因而有必要从数据量趋于无穷、数据量有限和系统结构等不同角度来研究非参数非线性系统的变量选择问题.针对上述不同情形,本文分别给出变量选择算法和收敛性结论,并给出数值例子以验证理论结果的有效性,结果显示数值模拟与理论分析一致.