Distributed Management System Research Articles

Development of portable deterioration diagnosis device for oil filled transformers based on near‐infrared spectroscopic information

AbstractA transformer plays a key role in electric power distribution system; therefore, when the transformer fails, several electrical components may get affected. As a result, diagnosing the deterioration of transformers is important for the management of electric power distribution system. The furfural content in the insulating oil of a transformer is widely used as an indicator of deterioration because furfural is generated by the decomposition of insulating paper. However, analyzing the furfural content is time consuming because of the requirement of a professional and the complexity of the diagnosis process. In this study, we propose a novel method for analyzing the amount of furfural in the insulating oil based on near‐infrared spectroscopic data obtained using the developed portable spectrometer, which can be used for the on‐site analysis at transformer installation sites. We selected wavenumbers with high correlation coefficients between the furfural content of oil and the spectroscopic data and estimated the furfural content by partial least squares regression. The results suggest that the furfural content can be analyzed in a few minutes using a small amount of oil through a portable diagnostic device.

Smart Water Management Grid

The Smart Water Management Grid (SWMG) lever- age the power of the Internet of Things (IoT) to revolutionize water management, ensuring efficiency, sustainability, and reliability in water distribution systems. By integrating sensors such as level monitoring, pressure monitoring, leakage control, and pH sensors, these grids enable real-time monitoring and intelligent decision-making to optimize water usage and minimize wastage. One crucial aspect of smart water grids is level monitoring, which tracks water levels in reservoirs, tanks, and pipelines. By continuously monitoring water levels, authorities can ensure optimal storage and distribution, preventing shortages or over- flows. Pressure monitoring sensors further enhance efficiency by maintaining optimal pressure throughout the distribution network, minimizing energy consumption and reducing the risk of pipe bursts. Leakage control is another significant feature facilitated by IoT sensors in smart water grids. Advanced leak detection sensors can pinpoint even minor leaks in the system, enabling swift repairs and preventing significant water losses. This proactive approach not only conserves water but also reduces operational costs and mitigates potential damage to infrastructure and the environment. Moreover, integrating pH sensors into the water grid allows for real-time monitoring of water quality. Maintaining proper pH levels is critical for ensuring safe and potable water supply. By detecting variations in pH levels, authorities can promptly identify and address potential contamination issues, safeguarding public health and preventing waterborne diseases.

Minimizing the impact of electric vehicle charging station with distributed generation and distribution static synchronous compensator using PSR index and spotted hyena optimizer algorithm on the radial distribution system

This research investigates the impact of electric vehicle charging station on power loss, voltage stability, and reliability within radial distribution systems. With the escalating use of electric vehicles, understanding these effects is crucial for ensuring the stability and efficiency of radial distribution systems infrastructure. The study formulates the electric vehicle charging station allocation problem as a multi-objective function, integrating power loss, voltage stability, and reliability metrics expressed as the PSR index. Using the IEEE 69-bus system as a test system, the research explores the ramifications of electric vehicle charging station integration and proposes strategies to mitigate their effects. An innovative combination of distributed generation and distribution static compensator are employed to alleviate the impact of electric vehicle charging station on radial distribution systems. A recent optimization methodology called spotted hyena optimizer algorithm is introduced to determine optimal electric vehicle charging station locations, with results compared to other existing algorithms. The study assesses potential power losses induced by additional electric vehicle loads, explores strategies to optimize charging rates for minimizing resistive losses, and evaluates voltage stability and reliability implications. The important results include objective function values obtained using various algorithms: Spotted hyena optimizer algorithm (0.7683), cuckoo search algorithm (0.7709), bat algorithm (0.8035), and African vultures optimization algorithm (0.7856). The findings demonstrate that the proposed algorithm outperforms other algorithms in minimizing the objective function value, indicating its efficacy in optimizing electric vehicle charging station placement within radial distribution systems. In conclusion, this research contributes valuable insights into the challenges associated with integrating electric vehicle charging station into radial distribution systems and provides innovative solutions for optimizing electric vehicle charging station placement, thereby advancing the understanding and management of distribution systems in the context of electric vehicle adoption.

Power Hardware-in-the-Loop Smart Inverter Testing with Distributed Energy Resource Management Systems

The increasing integration of grid-connected photovoltaic (PV) inverters and inverter-based resource (IBR) systems into the power grid emphasizes the critical need for standardized procedures to ensure their reliability and effective grid support functions. This research is driven by the gap in standardized testing methodologies for smart inverters, which are pivotal for the stability and quality of power in distributed energy systems. We used a Power Hardware-in-the-Loop (PHIL) laboratory setup to conduct a comprehensive analysis of smart inverters within a simulated real-world grid environment. Our approach integrates a Distributed Energy Resource Management System (DERMS) with PHIL testing to evaluate the smart inverter’s performance across various operational modes. The detailed test protocols mimic real-world grid conditions, enabling the examination of the inverter’s dynamic response to grid disturbances, control strategies, and communication protocols. The primary aim of this study is to rigorously test and validate the primary functions of smart inverters, focusing on their impact on overall grid stability and power quality management. This includes advanced features like Volt–VAR, Volt–Watt, dynamic power factor control, and the seamless integration of smart inverters into DERMSs and Advanced Distribution Management Systems (ADMSs). Furthermore, we aim to bridge the current gap in standardized testing procedures, contributing to the establishment of robust standards and operating protocols for smart inverter integration into the grid.

Hierarchically Distributed Energy Management in Distribution Systems: An Error-Tolerant and Asynchronous Approach

Hierarchically Distributed Energy Management in Distribution Systems: An Error-Tolerant and Asynchronous Approach

Detecting clusters and tracing management of water distribution system using space–time scan statistics and utility network modeling

Water-quality incidents in the water supply can occur because of errors in pressurization plant operations, leaks, and pollutant infiltration. They lead to citizen complaints about water quality. Identifying high-risk areas and contributing factors for accidents helps to prevent incidents. Here, a predictive analysis technique based on a geographic information system and complaint data was developed using SaTScan, a space–time statistical analysis program. High-risk clusters were identified using maximum log-likelihood ratios, relative risks, and Monte Carlo hypothesis testing. After a red water accident, high-risk clusters (C6–C9) were concentrated in one area. The relative risk of C7 before the accident was 4.58, double that of C2 (2.21). Using ArcGIS, a utility network dataset was created for the water-supply infrastructure in the high-risk cluster area. A utility network model enables flow simulation of the target water supply and tracing of the scope of influence. Downstream analysis of the trace showed that C8 had the greatest expected range of damage following an accident. To address this issue, four valves requiring controls were identified. C6 was predicted to suffer the most significant damage in an accident because it was closest to the water purification plant and had the largest pipe diameter.

Bibliometric Analysis of Risk Management of Water Distribution System

This study aims to provide valuable insights that can contribute to future research directions, policy formulation, and management of water distribution systems to avoid potential risks. This research was conducted using bibliometric analysis of articles related to the topic under study. This research methodology is designed to carry out bibliometric analysis of literature related to water distribution systems, using the VOSviewer and Publish or Perish 8 applications. Research findings show that passenger transportation, satisfaction, and development are the three main keywords and additional keywords related to the research topic. Based on data from the Public Transportation Satisfaction Study, it can be concluded that the number of studies continues to increase from 2000 to 2023, with the highest number in 2021. The research trend regarding public transportation satisfaction continues to grow every year and will continue to increase in the coming years.

A Branch-and-Price Algorithm for an Integrated Online and Offline Retailing Distribution System with Product Return

This study identifies critical inefficiencies within a dual-channel operation model employed by a fast fashion company, particularly the independent operation of three logistics distribution systems. These systems result in high operational costs and low resource utilization, primarily due to redundant vehicle dispatches to meet the distinct demands of retail store replenishment, online customer orders, and customer return demands, as well as random and scattered return requests leading to vehicle underutilization. To address these challenges, we propose a novel integrated logistics distribution system design and management method tailored for dual-channel sales and distribution businesses. The approach consolidates the three distribution systems into one cohesive framework, thus streamlining the delivery process and reducing vehicle trips by combining retail and customer visits. An optimization algorithm is introduced to factor in inventory and distribution distance, aiming to achieve global optimization in pairing retail store inventory with online customer orders and unifying the distribution of replenishment products, online products, and returned products. The paper contributes to the field by introducing a new variation of the Vehicle Routing Problem (VRP) that arises from an integrated distribution system, combining common VRP issues with more complex challenges. A custom Branch-and-Price (B&P) algorithm is developed to efficiently find optimal routes. Furthermore, we demonstrate the benefits of the integrated system over traditional, segregated systems through real-world data analysis and assess various factors including return rates and inventory conditions. The study also enhances the model by allowing inventory transfers between retail stores, improving inventory distribution balance, and offering solutions for scenarios with critically low inventory levels. Our findings highlight a significant reduction in total operating cost savings of up to 49.9% and vehicle usage when using the integrated distribution system compared to independent two-stage and three-stage systems. The integrated approach enables the utilization of vacant vehicle space and the dynamic selection and combination of tasks, preventing unnecessary mileage and space wastage. Notably, the integration of inventory sharing among retail stores has proven to be a key factor in generating feasible solutions under tight inventory conditions and reducing operational costs and vehicle numbers, with the benefits amplified in large-scale problem instances.

Energy Optimization in Water Distribution System and Pump Scheduling

Efficient management of water distribution systems are critical for providing consistent water supply while reducing energy usage and operational expenses. This research proposes a unique method for improving water distribution and pump scheduling. The suggested system leverages ultrasonic sensors to monitor water levels in storage tanks, then dynamically changes pump operation and valve settings depending on real-time demand and tank levels. A mobile application gives users remote access to system controls, allowing them to work from anywhere. By combining sensor data with intelligent algorithms, the system optimizes pump scheduling to fulfill water demand while conserving energy and lowering system losses. The creation and implementation of such a system have tremendous potential to improve the performance and sustainability of water distribution networks.

Shape factor analysis of a magnetohydrodynamics mixed convective Nimonic 80A/water nanofluid flow over a moving wedge in the presence of thermal radiation

One of the most common problems faced in the industries is the lack of proper heat energy and temperature distribution management systems. The study of the effects of thermal radiation and magnetohydrodynamics on a water-based nanofluid flow with various shapes of the nanoparticle Nimonic 80A, over a moving wedge, is yet to be studied by any researcher. Being a superalloy of nickel–iron–chromium, Nimonic 80A is often used in exhaust systems and chemical plants as an anti-corrosive agent. The mathematical model presented in this article was transformed using similarity transformations and solved using MATLAB bvp4c code. All the results and graphs were formulated after a positive outcome of our results with that available in the existing literature. Increases in velocity and temperature were observed with the increase in empirical shape factors of the nanoparticle for various parameters. Local Nusselt number and skin-friction coefficients decreased under the influence of augmenting shape factors of the nanoparticles. The velocity profile decreased at a rate of 1.5% while the temperature profile augmented by 0.24% for an augmenting magnetic parameter from M = 0.6 to 0.8 while the velocity profile increased for an increase in radiation parameter. An increment in the nanoparticle concentration resulted in incrementing streamline values and skin friction coefficient by 0.38% and 6.83%, respectively.

A scalable, dynamic, and secure traffic management system for vehicular named data networking applications

Several intelligent transport systems in vehicular networks (VANETs) rely on IP-based models for inter-vehicle communication. However, many approaches for Cooperative Intelligent Transport Systems and distributed systems are not secure and appropriate for VANETs, using specific technologies, centralized network architectures, or limited communication models. In addition, many applications are forced to deal with complex services that the network layer does not provide. This paper proposes NDN-Waze, a comprehensive distributed and lightweight system for vehicular traffic management using Named Data Networking as the main underlying communication protocol. NDN-Waze is a proof-of-concept design that has applications in vehicular route guidance, traffic and mobility monitoring, as well as roadside units as a service in urban areas. We use the NDN-Waze route guidance module to compare the VANET model via Named Data Networking (NDN) and Internet Protocol (IP). Our study employs traditional network metrics to support the hypothesis that the communication architecture has a direct impact on both efficiency and the quality of service operations. The simulation results demonstrate that NDN properties can override traditional IP-based forwarding proposals in VANET.

Water Distribution Systems: Integrated Approaches for Effective Utility Management

An extensive review of research advances in distribution system management was conducted to include methods, tools, and frameworks for integration. Sources included archival journals and water industry reports from research institutes, government regulators, and industry media covering case studies of advances that were implemented. Results showed that while effective management of water distribution systems requires an integrated approach, none of the available frameworks for one are in broad use in the water supply industry. Frameworks developed include a management standard of the American Water Works Association and Distribution System Optimization, a methodology for physical, hydraulic, and water quality performance assessment. The intelligent systems framework also offers a promising pathway to integration, but it lacks a definite structure. The voluntary aspect of adopting innovations within the fragmented and uncoordinated nature of the water utility industry poses a barrier to adoption of such innovations. Another barrier is the uncoordinated arrangements of water research stakeholders with different incentive structures. Intelligent water systems offer a way to incentive the utility industry to encourage implementation. They can provide a bottom-up approach where the utility industry can see advantages, as opposed to a top-down approach where they are expected to adopt a method without seeing clear benefits. Research to develop new and improved tools is needed, but the research roadmap should prioritize implementation.

Integrating Distributed Generation and Advanced Deep Learning for Efficient Distribution System Management and Fault Detection

Integrating Distributed Generation and Advanced Deep Learning for Efficient Distribution System Management and Fault Detection

Delay and Energy Efficient Offloading Strategies for an IoT Integrated Water Distribution System in Smart Cities

In the fast-moving world of information and communications technologies, one significant issue in metropolitan cities is water scarcity and the need for an intelligent water distribution system for sustainable water management. An IoT-based monitoring system can improve water distribution system management and mitigate challenges in the distribution network networks such as leakage, breakage, theft, overflow, dry running of pumps and so on. However, the increase in the number of communication and sensing devices within smart cities has evoked challenges to existing communication networks due to the increase in delay and energy consumption within the network. The work presents different strategies for efficient delay and energy offloading in IoT-integrated water distribution systems in smart cities. Different IoT-enabled communication network topology diagrams are proposed, considering the different water network design parameters, land cover patterns and wireless channels for communication. From these topologies and by considering all the relevant communication parameters, the optimum communication network architecture to continuously monitor a water distribution network in a metropolitan city in India is identified. As a case study, an IoT design and analysis model is studied for a secondary metropolitan city in India. The selected study area is in Kochi, India. Based on the site-specific model and land use and land cover pattern, delay and energy modeling of the IoT-based water distribution system is discussed. Algorithms for node categorisation and edge-to-fog allocation are discussed, and numerical analyses of delay and energy models are included. An approximation of the delay and energy of the network is calculated using these models. On the basis of these study results, and state transition diagrams, the optimum placement of fog nodes linked with edge nodes and a cloud server could be carried out. Also, by considering different scenarios, up to a 40% improvement in energy efficiency can be achieved by incorporating a greater number of states in the state transition diagram. These strategies could be utilized in implementing delay and energy-efficient IoT-enabled communication networks for site-specific applications.

Automated Over-the-Top Service Copyright Distribution Management System Using the Open Digital Rights Language

As the demand and diversity of digital content increase, consumers now have simple and easy access to digital content through Over-the-Top (OTT) services. However, the rights of copyright holders remain unsecured due to issues with illegal copying and distribution of digital content, along with unclear practices in copyright royalty settlements and distributions. In response, this paper proposes an automated OTT service copyright distribution management system using the Open Digital Rights Language (ODRL) to safeguard the rights of copyright holders in the OTT service field. The proposed system ensures that the rights to exercise copyright transactions and agreements, such as trading of copyright, can only be carried out when all copyright holders of a single digital content agree based on the Threshold Schnorr Digital Signature. This approach takes into account multiple joint copyright holders, thereby safeguarding their rights. Furthermore, it ensures fair and transparent distribution of copyright royalties based on the ratio information outlined in ODRL. From the user’s perspective, the system not only provides services proactively based on the rights information specified in ODRL, but also employs zero-knowledge proof technology to handle sensitive information in OTT service copyright distribution, thereby addressing existing privacy concerns. This approach not only considers joint copyright holders, but also demonstrates its effectiveness in resolving prevalent issues in current OTT services, such as illegal digital content replication and distribution, and the unfair settlement and distribution of copyright royalties. Applying this proposed system to the existing OTT services and digital content market is expected to lead to the revitalization of the digital content trading market and the establishment of an OTT service environment that guarantees both vitality and reliability.

Smart Animal Repelling Device: Utilizing IoT and AI for Effective Anti-Adaptive Harmful Animal Deterrence

The coexistence of human populations with wildlife often leads to conflicts in which harmful animals cause damage to crops and property and threaten human welfare. Certain limitations influence the effectiveness and environmental impacts of traditional methods used to repel animals. The present research outlines a growth of solutions that utilize the Internet of Things and machine learning techniques to address this issue. This study centers on a Smart Animal Repelling Device (SARD) that seeks to safeguard crops from ungulate assaults, substantially reducing production expenditures. This is achieved by developing virtual fences that use Artificial Intelligence (AI) and ultrasonic emission. This study introduces a comprehensive distributed system for resource management in Edge or Fog settings. The SARD framework leverages the principle of containerization and utilizes Docker containers to execute Internet of Things (IoT) applications in microservices. The software system inside the suggested structure can include various IoT applications and resources and power management strategies for Edge and fog computing systems. The experimental findings demonstrate that the intelligent animal-repellent system effectively uses animal detection on power-efficient computational methods. This implementation ensures the system maintains high mean average accuracy (93.25%) while simultaneously meeting real-time demands for anti-adaptive harmful animal deterrence.

Decentralized Energy Management of Multiagent Distribution Systems Considering the Grid Reliability and Agent Misbehavior

Decentralized Energy Management of Multiagent Distribution Systems Considering the Grid Reliability and Agent Misbehavior

Detection of Botnet in the loT Network

The ubiquity of Internet of Things (IoT) devices has prompted security concerns, particularly in the face of evolving botnet attacks. This paper investigates the impact of botnet attacks on IoT devices and proposes a network-based detection and prevention system employing signature and anomaly-based mechanisms. Notably, our methodology extends beyond traditional detection, focusing on proactively impeding bot creation. Leveraging a Linux-based distributed system, Security Information and Event Management (SIEM) tools, and custom rules, our approach encompasses distinct phases Preprocessing, Network Security Monitoring, Rule-based IDS System, and Analysis. Experimental results with diverse PCAP files demonstrate the efficacy of custom rules, significantly enhancing alert counts for various security aspects, including network trojan detection and privacy violations. The significant finding is the substantial increase in alert counts after the integration of custom rules, exemplified in the 1.1 GB PCAP file scenario. Network trojan detection surged from 585 to 988, emphasizing the heightened efficacy of rule-based measures. Privacy breaches and bad traffic alerts also experienced significant increments, showcasing the system’s improved sensitivity and responsiveness. This finding reinforces the pivotal role of custom rules in fortifying IoT network security comprehensively.

Preface

Preface It is our great pleasure to have you at the 2023 3rd International Conference on Smart Grid and Energy Internet (SGEI 2023), which took place in Chengdu, China from September 8th to 10th, 2023 (virtual conference). SGEI 2023 was successfully held and received unanimous praise from various experts and scholars all over the world.SGEI 2023 existed as an international forum for academic communications between experts and scholars in the fields of Smart Grid and Energy Internet. It promoted the research and developmental activities in related fields and scientific information interchange among all the participants, establishing research connections for them to find global partners for potential collaboration.After months of well preparation and hard work, the Proceedings of SGEI 2023 covering a bunch of papers, having been checked through rigorous review and processes to meet the requirements of publication, are smoothly published. These papers feature but are not limited to the following topics: Smart Power Distribution and Microgrid, Energy Strategy and Energy Internet, Energy and Distribution Management Systems, Power System Communication and Control, etc.We had about 80 participations both as speakers and participants, including researchers, industrial experts, teachers, students, and other practitioners. During the keynote speech part, each keynote speaker was given 30–40 minutes for keynote speech. Among them, Professor Ismail Musirin from Universiti Teknologi MARA, Malaysia performed a keynote speech. Most of his researches dealt with the algorithms and techniques development in solving problems in Power System involving Voltage Stability, Economic Power Dispatch, Transient Stability, Distributed Generation, Renewable Energy Optimization, Power System Optimization and Application of Artificial Intelligence in Power System. He has got 22 years of research experience in the field of Power System Engineering and has received numerous research grants from the Ministry of Higher Education, Malaysia (MOHE) and Ministry of Science, Technology and Innovation, Malaysia (MOSTI). The insightful speeches of each keynote speakers triggered interesting discussions and a good number of informal talks between all the participants.We would like to express our gratitude to the organizers, keynote speakers and all the participants of SGEI 2023, for their fruitful work and contribution to the success of the Conference. We are thankful to all the reviewers for providing constructive criticisms, stimulated comments and suggestions to the authors. Particularly, our special thanks go to Journal of Physics: Conference Series, for the endeavor of all its colleagues in publishing this paper volume.May this event be a spark that ignites many more new inventions in the fields related to smart grid and energy internet!The Committee of SGEI 2023List of Committee Member is available in this Pdf.

Retraction Notice: A Directed Acyclic Graph Based Architecture for Optimal Operation and Management of Reconfigurable Distribution Systems With PEVs

Retraction Notice: A Directed Acyclic Graph Based Architecture for Optimal Operation and Management of Reconfigurable Distribution Systems With PEVs