A Framework for Cybersecurity Alert Distribution and Response Network (ADRIAN)

Security Information and Event Management (SIEM) platforms are critical for organizations to monitor and manage their security operations centers. However, organizations using SIEM platforms have several challenges such as inefficiency of alert management and integration with real-time communication tools. These challenges cause delays and cost penalties for organizations in their efforts to resolve the alerts and potential security breaches. This paper introduces a cybersecurity Alert Distribution and Response Network (Adrian) system. Adrian introduces a novel enhancement to SIEM platforms by integrating SIEM functionalities with real-time collaboration platforms. Adrian leverages the uniquity of mobile applications of collaboration platforms to provide real-time alerts, enabling a two-way communication channel that facilitates immediate response to security incidents and efficient SIEM platform management. To demonstrate Adrian’s capabilities, we have introduced a case-study that integrates Wazuh, a SIEM platform, to Slack, a collaboration platform. The case study demonstrates all the functionalities of Adrian including the real-time alert distribution, alert customization, alert categorization, and enablement of management activities, thereby increasing the responsiveness and efficiency of Adrian’s capabilities. The study concludes with a discussion on the potential expansion of Adrian’s capabilities including the incorporation of artificial intelligence (AI) for enhanced alert prioritization and response automation.

Research on Distribution Network Automation and Distribution Network Planning Mode

Based on the research of distribution network automation and distribution network planning mode, the analysis of the significance of urban distribution network automation must be performed at the first place. Combined with the problems existing in China’s current distribution network, it is concluded that, establish effective hardware support system, data sharing and feeder automation to ensure automation safety;strengthen power distribution and power line material testing to improve distribution automation system and distribution network planning;research methods of improving the professional skills and comprehensive quality of professionals.

Development and Implementation of GSM-Based Distribution Automation System with Graphic User Interface in Nigeria Electric Power Distribution Network

Lack of up-to-date information on efficient operation and maintenance of EPDS （electric power distribution systems）, Nigeria is addressed by designing and implementing an indigenous real-time monitoring and diagnosis system. The system encompasses the development of software driven hardware positioned at the remotely located sub-stations at the low voltage level to keep track of the network in real-time. The detection of faults exploits threshold passing algorithm through continuous monitoring of the network power quality. Communication between the RTU （remote terminal unit） and the DCC （distribution control center） which is based on GSM is initiated by disturbance. The DCC performs fault evaluation processing using the received data and predetermined faults signatures to determine the nature of disturbance and presents the result in graphic user interface environment. A fault reporting time of 2 s was achieved. The developed system exhibits a high degree of accuracy and manifests no spurious reports during testing. The resultant system limits the effects of interruption and increases power availability by reducing the down time. The system strengthens engineering and management capabilities required to enhance reliability by providing information about the network health status.

Three Projects of Intelligent Distribution Automation System in East Asia

Intelligent distribution automation system （IDAS） was developed based on distribution automation system that was installed in all distribution offices of Korea. IDAS was designed the combined system with the function of supervisory control and data acquisition （SCADA） and distribution automation system （DAS） for network operation from substation to high voltage customer, and it has been installed in Vietnam, China and Indonesia. This paper explains the project scope, system configuration, and the function of each sy stem.

东海OBN和三维DAS-VSP数据的联合采集与处理方法研究

近年来,光纤传感技术已经应用于地面地震数据、海洋地震数据、井中地震数据和井地联合地震数据的采集,推动了光纤传感技术在地球物理特别是地震数据采集中的应用。井地或井海联合地震勘探是陆地或海洋三维地震与三维DAS-VSP勘探相结合形成的三维立体地震勘探方法,利用井海联采的三维DAS-VSP数据,可以获得地下井周围准确的时深关系、地层速度、反褶积算子、球面扩散补偿因子、吸收衰减因子、各向异性参数和井筒周围的高分辨率构造成像,这些参数可以基于井驱处理提高陆地或海洋三维地震数据的处理质量。在中国东海某OBN数据勘探中首次开展了井下套管内铠装光缆同步采集的三维DAS-VSP数据的处理方法研究以及成像处理。首先,采用常规的三维VSP数据成像处理技术对三维DAS-VSP数据进行常规处理,具体处理流程包括:观测系统定义、预处理、初至拾取、静校正、振幅补偿、反褶积、波场分离、速度分析与建模和利用上行反射波进行井周围地层的构造成像;然后,再根据海上三维DAS-VSP数据下行多次波的特点,研发了海上三维DAS-VSP数据的下行多次波成像技术,扩展了三维DAS-VSP数据成像范围,提高了三维DAS-VSP数据成像的整体质量。与本工区早期的三维OBC数据成像结果相比,本次三维DAS-VSP数据的下行多次波成像结果表明,井周围三维构造成像质量得到了显著改进,大幅度扩展了成像范围;新采集的OBN数据和三维DAS-VSP数据的成像结果展示了更为详细和较高分辨率的构造成像,基于新的成像资料,对储层顶部和储层内流体的识别与追踪变得更加容易和清晰。井海联采技术生产效率高且成本低,既能快速获得三维DAS-VSP数据及成像,还能对三维海洋地震数据进行井驱提高分辨率处理。此外,三维OBN或OBC数据和三维DAS-VSP数据还能够进行融合处理,实现井地或井海同步采集数据的联合偏移成像,可以大幅度提高三维海洋地震数据的成像品质,值得在有条件的地方推广应用。

采用非稳相偏振滤波的DAS-VSP数据P/S波分离方法及其应用

分布式光纤声学传感(DAS)因成本低、易布设以及高密度采样等优势正成为重要的地震观测技术,尤其是越来越多地与垂直地震剖面(VSP)结合,用于主动地震勘探或被动地震监测.DAS传感器通过感知弹性波场产生的轴向应变或应变速率来观测地震波场振动.然而,目前单分量DAS-VSP数据未完整地记录地下弹性波场的三维矢量振动信号,因此如何从中分离出P波或S波用于后续地震成像与参数反演是重要且很有挑战的课题.以弹性波传播理论为基础,本文根据P波和S波的频散关系估算接收点处各自的偏振方向,通过随频率和空间位置变化的偏振滤波实现DAS-VSP数据的P/S波分离.理论模型合成数据与东海实际DAS-VSP数据实验结果表明,该方法能有效地将P波和S波信号从单分量DAS-VSP数据中分离出来,可为后续纵横波速度反演、PP与PS波成像提供关键的数据预条件处理.

Spatial distribution modeling of subsurface bedrock using a developed automated intelligence deep learning procedure:A case study in Sweden

Due to associated uncertainties,modelling the spatial distribution of depth to bedrock(DTB) is an important and challenging concern in many geo-engineering applications.The association between DTB,the safety and economy of design structures implies that generating more precise predictive models can be of vital interest.In the present study,the challenge of applying an optimally predictive threedimensional(3D) spatial DTB model for an area in Stockholm,Sweden was addressed using an automated intelligent computing design procedure.The process was developed and programmed in both C++and Python to track their performance in specified tasks and also to cover a wide variety of diffe rent internal characteristics and libraries.In comparison to the ordinary Kriging(OK) geostatistical tool,the superiority of the developed automated intelligence system was demonstrated through the analysis of confusion matrices and the ranked accuracies of different statistical errors.The re sults showed that in the absence of measured data,the intelligence models as a flexible and efficient alternative approach can account for associated uncertainties,thus creating more accurate spatial 3D models and providing an appropriate prediction at any point in the subsurface of the study area.

e-Automation,an Architecture for Distributed Industrial Automation Systems

Due to the complexity of modern industrial systems, a conventional automation system is not capable of providing sufficient information management and high-level intelligent approaches, as achieving these functionalities requires the support of comprehensive data management and coordination between system devices and heterogenous information. This paper proposes the concept of e-Automation, in which computer networking and distributed intelligence agent technologies are applied to industrial automation systems, and presents a hardware and software architecture that implements this concept. An open infrastructure based on multi-agent systems is employed in the proposed architecture of e-Automation, which aims to allow the implementation of diverse tasks and to permit greater configurability than can be obtained from a traditional system. To evaluate our proposed e-Automation concept, this paper presents a case study of substation information management which adopts the proposed e-Automation architecture in power system domain.

Aggregator Based RPL for an IoT-Fog Based Power Distribution System with 6LoWPAN

Advanced Metering Infrastructure(AMI)forms an important part in Smart Grids.Routing the data effectively from smart meters to the Edge/Fog node requires an efficient routing protocol.Routing Protocol for Low Power Lossy Area Network(RPL)is a standard routing protocol for IPv6 over Low Power Personal Area Network(6LoWPAN).In a Power Distribution system all the smart meters together form 6LoWPAN network.They communicate with the fog router,which acts as the 6LoWPAN gateway.ContikiRPL was evaluated using Cooja Network simulator for a power distribution network topology.The nodes which were far away from the fog node gave low Packet Delivery Ratio(PDR)and large End to End delay.This paper proposes an aggregation RPL scheme by modifying the existing Contiki RPL.The smart meter nodes communicate to the aggregator,which communicates to the fog node.The results show that the aggregation scheme has 35.6%increase in PDR,lesser hop count and 13.24%decrease in End to End delay on an average compared to existing RPL.

Method of Fault Area ＆ Section Location for Non-solidly Earthed Distribution System

中国中压配电网以架空线为主，多为小电流系统，单相接地故障占到电网故障总数的80％以上，但中国配网自动化系统基本上没有小电流接地故障定位功能，使配网自动化系统在提高可靠性的作用上大打折扣。给出一种小电流接地故障区段定位新方法，在线路上配置广域相量测量固定测点，获取小电流电网单相接地故障特征信息。基于测点相邻矩阵区段起始测点标识向量和故障路径标识向量概念，提出确定故障区间边界节点算法。物理模拟实验和挂网测试表明：该故障分区分段定位方法能够在线求解小电流接地故障段边界节点，缩小线路维护巡视范围。确定故障区间边界节点算法还可用于确定故障区相关负荷开关，为线路维护和馈线自动化提供依据。

Optimal Partitioning of Distribution Networks for Micro-Grid Operation

A great concern for the modern distribution grid is how well it can withstand and respond to adverse conditions. One way that utilities are addressing this issue is by adding redundancy to their systems. Likewise, distributed generation (DG) is becoming an increasingly popular asset at the distribution level and the idea of microgrids operating as standalone systems apart from the bulk electric grid is quickly becoming a reality. This allows for greater flexibility as systems can now take on exponentially more configurations than the radial, one-way distribution systems of the past. These added capabilities, however, make the system reconfiguration with a much more complex problem causing utilities to question if they are operating their distribution systems optimally. In addition, tools like Supervisory Control and Data Acquisition (SCADA) and Distribution Automation (DA) allow for systems to be reconfigured faster than humans can make decisions on how to reconfigure them. As a result, this paper seeks to develop an automated partitioning scheme for distribution systems that can respond to varying system conditions while ensuring a variety of operational constraints on the final configuration. It uses linear programming and graph theory. Power flow is calculated externally to the LP and a feedback loop is used to recalculate the solution if a violation is found. Application to test systems shows that it can reconfigure systems containing any number of loops resulting in a radial configuration. It can connect multiple sources to a single microgrid if more capacity is needed to supply the microgrid’s load.

Multi Agent Based Power Distribution System Restoration—A Literature Survey

Multi agent system (MAS) is one of the most dominant research wings which consist of several agents who interact with each other to achieve a common objective. MAS has been developed for a wide range of applications in power systems. Power system restoration is a main application of that. Researchers present several architectures for fault identification, isolation and restoration of the power system. This paper presents a complete literature review on available architectures for power distribution restoration and future trends in MAS based power system restoration.

Energy Saving on Distribution of Liquid Animal Feeds at Pigsty Farms

This paper focused on the task of reducing power consumption and improving energy efficiency in the technological process of distribution liquid feeds in a pigsty. The liquid feeds in a pigsty are distributed to the stables via pipelines. A centrifugal pump driven by an electric motor is used to supply the liquid feed and to move it through the pipeline. The electric motor is the major electric energy consumer in the process. As shown by experimental data and as following the theory, there is a non-linear relation between the electric motor power, the pump throughput and feed humidity. The purpose of the paper is to calculate such an optimal value of the electric motor power that provides the minimal energy consumption on the process of feed distribution. The problem is solved by the Lagrange multiplier method of nonlinear mathematical programming, taking into account geometrical parameters of the pipeline, humidity and portions volumes of distributed feed. The energy saving effect is estimated and reducing power consumption is shown.

A Parallel Approach for Real-Time Power Flow in Distribution Networks

The new reality of smart distribution systems with use of generation sources of small and medium sizes brings new challenges for the operation of these systems. The complexity and the large number of nodes requires use of methods which can reduce the processing time of algorithms such as power flow, allowing its use in real time. This paper presents a known methodology for calculating the power flow in three phases using backward/forward sweep method, and also considering other network elements such as voltage regulators, shunt capacitors and sources of dispersed generation of types PV （active power and voltage） and PQ （active and reactive power）. After that, new elements are introduced that allow the parallelization of this algorithm and an adequate distribution of work between the available processors. The algorithm was implemented using a multi-tiered architecture; the processing times were measured in many network configurations and compared with the same algorithm in the serial version.

传统DAS分布系统5G用户速率提升方案

传统DAS分布系统作为室内无线网络覆盖的重要手段,在4G时代积累了庞大的规模。面向5G高速率要求,如何更好地盘活传统DAS分布系统是5G室内覆盖的重要课题。本文研究了传统DAS分布系统5G用户速率提升的多种解决方案,为5G室内覆盖建设提供了丰富的建设手段,具有较高的参考价值。

基于DAS技术的地下通信光缆路由寻址

提出一种基于分布式声波传感(DAS)技术的光缆寻址方法,在南京晓庄学院方山校区内开展实验研究,使用MATLAB对采集到的数据进行处理,得到其特征图,后使用OpenCV对该图像进行处理,在获得路由的同时计算出井内预留光缆的长度,路由巡纤结果与规划图一致。研究结果表明,DAS技术可用于通信光缆巡纤,排查光缆的线路和路由,该技术可用于光缆修复和网络扩充前对预留光纤的长度是否足够进行判断,以确定具体的修复和扩充策略,大大减少工程时间。

基于多尺度增强级联残差网络的DAS地震资料背景噪声衰减方法

由于复杂强背景噪声的影响,分布式光纤声学传感(Distributed Optical Fiber Acoustic Sensing,DAS)采集的地震记录普遍信噪比较低。如何有效抑制背景噪声,恢复弱上行反射信息,切实提升DAS记录信噪比,已成为资料处理领域的热点问题之一。针对复杂DAS背景噪声消减问题,提出了一种多尺度增强级联残差网络(Multiscale Enhanced Cascade Residual Network,MECRN)。MECRN具有双路径级联残差网络结构,通过双路径机制提取DAS记录浅层信息。在此基础上,引入空洞卷积和多尺度模块提取DAS记录的多尺度特征,并通过跳跃连接导入浅层特征,在避免有效特征损失的同时,提升网络的特征提取能力。最后,通过残差学习整合局部和全局特征,并对重建特征细化,进一步提升了MECRN的去噪能力。模拟和实际DAS资料处理结果均表明,MECRN可以有效地压制DAS记录中的复杂背景噪声,准确恢复弱反射信号,显著提升处理DAS资料的能力。

浅谈配网自动化光纤通信系统施工技术

为了保证配网自动化光纤通信系统的稳定运行和信号的可靠传输,论文简要介绍了配网自动化光纤通信系统,对配网自动化光纤通信技术在施工过程中的施工要求、关键要点和注意事项进行了探究。

基于人工智能技术的分布式数据库重复记录自动检测系统设计

以人工智能技术为基础前提的分布式数据库重复记录自动检测的方式,以提高数据库查询时的准确率以及查询效率。设计系统首先对数据信息进行对应的特征提取,而后通过权衡函数对样本信息进行整合,通过自适应分解得到相应的目标函数并求解,结合灰狼算法以及Shingle完成数据查询。经过算例验证,改进设计方式准确率均超过90%,平均耗时在35 s以内,满足自动查询快速精确的要求。

集中式馈线自动化配电网供电可靠性评估

计及集中式馈线自动化的配电网可靠性评估尚存在较多研究空白,且多数研究仅计及故障停电的影响,在考虑预安排检修容量约束的情况下,计及负荷转供影响,结合馈线自动化的类型及运行逻辑,依据馈线自动化相关技术指标,对恢复供电过程中出现的负荷点进行详细分类,推导出不同类型负荷期望恢复供电时间和配电网供电可靠性指标计算公式。结合算例进行分析可知,不同终端配置下馈线系统平均停电持续时间SAIDI可减少0.95~1.08 h/(用户·a),说明了优化终端配置可有效提高配电网供电可靠性,证明了所提评估方法的准确性和实用性,并比较了不同终端配置对可靠性的影响。