Electric Communication Network Research Articles

Synthesis of modeling and optimal management of smart grids

Smart grids may be characterized as the amalgamation of electrical grids, communication networks, specialized hardware, and computational intelligence (algorithms). This integration aims to oversee, regulate, and coordinate the generation, distribution, storage, and utilization of energy. Indeed, smart grid technologies have the potential to facilitate the distribution of substantial quantities of power generated from renewable sources. For this purpose, a comprehensive modeling approach is employed to simplify and enhance the feasibility of the task. It introduces a highly intricate system where modeling the components and relationships between entities proves challenging. Optimal energy management is necessary in this case. This paper provides a summary of an investigation into the modeling and optimal management of smart grids. In fact, this work allows a discussion of a hybrid system. Then we briefly introduce the domain of conceptual modeling within the enterprise.

Event-Triggered Distributed Secondary Control With Model-Free Predictive Compensation in AC/DC Networked Microgrids Under DoS Attacks.

This article presents an event-triggered distributed secondary control with predictive compensation based on the model-free predictive control under Denial-of-Service (DoS) attacks in ac/dc-networked microgrids. First, models of ac/dc networked microgrids in both electric network and communication network are established. On this premise, event-triggered distributed secondary control is proposed to solve the problems of strong communication burden and low-power distribution accuracy. Besides, aiming at the impact of DoS attacks on distributed secondary control, a compensation algorithm based on model-free predictive control is designed to estimate the control variables when the DoS attack occurs, which can improve the control performance and maintain the stable operation without a specific system structure system. Then, the convergence of event-triggered distributed secondary control with the condition of whether DoS attacks happen are analyzed. Finally, the effectiveness of the proposed control is verified on the hardware-in-loop (HIL) simulation platform consisting of the RT-LAB simulator, MATLAB/Simulink simulation model, and DSP controller.

AC power analysis for second-order memory elements

As the product of a circuit’s voltage and current, apparent power (S) is of paramount necessity and importance in electrical utilities, electronics, communication, and neural network systems. Based on the existing AC power analysis on the two-terminal passive elements (i.e., R, L, and C), some in-depth research on AC apparent power calculations for second-order memory elements and memristive systems is introduced to help with revealing their complex and unique non-linear phenomena. This paper derives the forms of real power, reactive power, and apparent power for the proposed second-order memory elements (i.e., MR, MC, and ML) and reveals the difference between ideal memory elements and traditional passive ones (i.e., R, C, and L). For all involved memory elements, harmonic values and an extra term occur in the expression of powers to represent their memory characteristics. Especially, the real power is a function of a circuit’s dissipative elements (usually resistances R), but not exactly the memristor (MR). Then, the corresponding curves could be depicted, which demonstrate the differences between R/C/L and MR/MC/ML and verified that harmonic values existed in SMR/SMC/SML, meaning that it would perpetually supply energy when operated with an alternating current.

A review on autonomous electric vehicle communication networks-progress, methods and challenges

Electric vehicles have gained significance owing to its unavoidable supporting factors including environmental impacts and climate features. It has been noticed over last few decades that the increased number of manufacturers have focused on electric propulsion-based technology either pure electric or hybrid form with the support of electric vehicles in the automotive market. The adoption of these electric vehicle has obviously increased its competitive nature while compared to traditional internal combustion engine system. Moreover, the electric vehicles (EVs) possess substantial potential, not only in minimizing carbon emission but also in assisting required energy storage to contribute to the distributed renewable generation. There exist several increases in electric vehicle usage, but their level of massive adoption and existence by automotive consumers is connected with its delivered performance. One such important feature is the autonomous electric vehicle communication networks. This research provides a comprehensive review on overview of the electric vehicles and will discuss various existing works on autonomous driving vehicles. The paper compares existing communication networks and nuances associated in the context of an autonomous electric vehicle. Also, it critiques the existing technology and provides suggestive future work in the field to make communication networks resilient. An extensive review makes it possible to ascertain future research directions in the EV research field, which would result in massive future and instantaneous EV perception in the automotive market.

A hybrid deep learning model for discrimination of physical disturbance and cyber-attack detection in smart grid

A smart grid (SG) consists of an interconnection of an electrical grid, communication, and information networks. The rapid developments of SG technologies have resulted in complex cyber–physical systems. Due to these complexities, the attack surfaces of SGs broaden, and their vulnerabilities to cyber–physical threats increase. SG security systems focus on the protection of significant units and sub-systems of communication and power networks from malicious threats and external attacks. False data injection attack (FDIA) is known as the most severe threat to SG systems. In this paper, a method of optimizing convolutional neural networks — long short-term memory (CNN-LSTM) with particle swarm optimization (PSO) to detect FDIA in the SG system is proposed. This model uses phasor measurement unit (PMU) measurements to detect an abnormal measurement value and determine the type of this anomaly. The complex hyperparameter space of the CNN-LSTM is optimized by the PSO. A detailed numerical comparison is made using the state-of-the-art deep learning (DL) architectures like LSTM, PSO-LSTM, and CNN-LSTM models to verify the accuracy and effectiveness of the proposed model. The results show that the model outperforms other DL models. In addition, the model has a high accuracy rate that provides decision support for the stable and safe operation of SG systems. In this respect, the proposed detection model is a candidate for building a more robust and powerful detection and protection mechanism.

Bayesian Networks based approach to enhance GO methodology for reliability modeling of multi-state consecutive-k-out-of-n: F system

As a success-oriented system reliability and safety analysis technique, GO methodology is widely used in the modeling and analysis scenarios of critical safety engineering systems with signal flow, such as nuclear, chemical industry, electric power transportation, wireless network and microwave communication network. Consecutive-k-out-of-n systems are also widely applied in these fields, but due to their relatively complex logic, there are no corresponding graphical modeling and calculation methods. In this paper, the basic GO methodology is extended to support the modeling and analysis of multi-state linear and circular consecutive-k-out-of-n: F system (MLC(k,n) &MCC(k,n)) models. Two new operators are defined in graphical modeling to represent the two types of complex system logic. The multi-state logic semantics of the new operators and mapping rules to Bayesian networks (BN) are given. And the programmable process is presented to transform the extended GO model into BN, and the reliability of the MLC(k,n)/MCC(k,n) is calculated. Finally, three cases are used to verify i) the correctness of the method supporting multi-state model, ii) the efficiency and ability of the algorithm, and iii) the forward calculation and reverse diagnosis of the MLC(k,n) and MCC(k,n) systems with external shared components.

Core Concept Of Bioelectronic Medicine And Their Theranostic Application In Cancer

Bioelectronic medicine is a way of treating in which the electrical communication networks of the body are altered to treat disease. Bioelectric circuitry in every cell creates a resting membrane potential as well as endogenous electric fields that regulate cell function and communication. The theory that cancer is caused by bioelectrical circuitry malfunctions in cells is now widely acknowledged. This opens up the possibility of using bioelectronic medicine to develop new cancer treatments by influencing the disease's bioelectrical properties. To meet societal and technical obstacles, today's individuals aspire to better their quality of life. So, in the midst of all of this, bioelectronic medicine has altered the way we practice medicine and has proven to dramatically enhance healthcare outcomes. This technique employs a variety of procedures, such as neuromodulation, to treat a specific disease, ailment, or damage. Interfacing electronics with nerves to specifically target the biological processes underlying diseases. In cancer, screening and early detection are crucial for the patient's therapy to be successful and for the patient's survival percentage to grow. For illness diagnosis, therapy, and follow-up, the development of analytical methods for non-invasive detection through the analysis of cancer biomarkers is crucial. Tumor biomarkers are substances or processes that indicate the existence of cancer in the body in clinical situations. These biomarkers can be detected using biosensors, which are popular alternatives to traditional approaches due to their speed, accuracy, and point-of-care applicability. Here we have discussed the consequences of current cancer treatments and bioelectronic medicine a combat for cancer diagnosis and treatment.

Optimal Reliability of a Smart Grid

This work presents the optimal reliability of a smart grid using Particle Swarm Optimization (PSO) and the Monte Carlo analysis. In the electrical grid, reliability defines the permanent supply of energy and the satisfaction of customers. This work proposes an OpenDSS-OMNet++ platform applied in the electrical grid and communication network to achieve the smart distribution grid. The aim consists to assess the capacity of the system according to various possibility and the automation level of the network. The 13-node IEEE system is implemented using the method and the proposed framework. In case of overload fault, the voltage drop is 45%, the SAIFI is 40 and with optimal allocation of distributed generation, the voltage drop moves to 2.3%, the SAIFI is 0.55. The energy losses go from 5232686.67 kWh/year to 211076.68 kWh/year, i.e. a difference of nearly 5021609.99 kWh/year. The final results indicate that our algorithm is efficient and reliable and can help companies of energy for future reliability trials and the progression of distributed generation in smart distribution grid.

Modelling cascading failure of a CPS for topological resilience enhancement

This study focuses on the cyber-physical system (CPS) consisting of interdependent electrical distribution and communication networks, where the two networks are mutually dependent. A small disturbance in either of them can trigger a cascade of faults within the entire network. To investigate the failure mechanism, first, two features that affect topological resilience (TR) are defined in this study: adaptation and recovery abilities. Second, the authors model the process of cascading failures that occur in this coupled system by introducing and developing the infrastructure interdependencies simulator. The process of cascading failures is based on percolation theory, and they present a detailed analysis of cascading failure in a standard IEEE 33-bus system coupled with the 33-node communication system. This study proves that the adaptation ability of a coupled system is even lower than a single system. This is due to the interdependencies between systems, and the study of the failure mechanisms helps planers to make a better decision in the recovery process. Finally, the modified shortest path search is used to optimise the repair sequence. Their numerical results validate that the recovery ability of the coupled system is increased through the optimisation, which contributes to the TR enhancement.

Secure Edge Electricity Data Aggregation Scheme for Low Voltage Transformer Areas

The smart grid system is the physical power infrastructure integrated with many intelligent electronic devices. It supports the two-way flow of energy as well as information. The smart meters are important intelligent devices, which account for the largest portion among all terminals in the smart grid. In many application scenarios, the master station need high frequency total electricity consumption information of each low voltage transformer area. It requires frequent data interchange between smart meters and master station. However, the electric communication network cannot provide enough bandwidth resource to support such high frequency data interchange. Edge Computing Nodes (ECNs), which can be deployed at different low voltage transformer areas, can achieve the electricity data aggregation at the edge side. The communication resource can be saved since only aggregated electricity data will be uploaded to the master station. Traditional data aggregation scheme requires the plaintext from smart meters. From the viewpoint of security and privacy-preserving, it is not safe to implement the data decryption operation at edge side. Therefore, the data aggregation scheme with ciphertext is required at the edge side. In this paper, we propose a secure edge electricity data aggregation scheme based on homomorphic public key encryption techniques. The ECNs will implement the electricity data aggregation with the ciphertext from different smart meters, and the aggregated data will be transmitted to the master station through communication network. The mater station can use its public key to obtain the total electricity consumption of each low voltage transformer area.

Design of Home Power Energy Management System Using Mixed Integer Linear Programming (MILP) Based on Extreme Learning Machine (ELM) Dynamic Pricing

Indonesia's electricity consumption has grown at an average of 4.2% per year over the past 15 years. This causes several problems such as environmental pollution and depletion of fossil energy sources. In order to overcome these problems, one of the things that can be done is saving electricity consumption. In this paper, home power management system (HPMS) application is developed with the goal for saving electricity consumption in order to minimize the daily operation cost. The HPMS system consists of smart electrical appliances, power units (grid and photovoltaic systems with energy storage), main controllers, web applications and communication networks. At the beginning of the day, the main controller will collect electricity equipment operation schedules and electricity prices from the grid and PV. Moreover, MILP, which is formulated with the operating constraints for electrical equipment, electricity prices (obtained from ELM predictions), and power resources, is used for solving the problem and will recommend the schedule of electricity resources with the most optimal costs for consumers. The simulation has been successfully tested with the results that HPMS can reduce electricity costs by more than 30%.

Analysis of Structural Changes Created by the Blast Effect

Abstract Unfortunately, people can’t live in peace in this century: many wars and terrorist attacks have been witnessed even within the last year. In the case of such attacks, both the people and the civil infrastructure is in danger [1-3]. The modern age (infrastructure) provides electrical networks and communication networks for the citizens. Without electricity and/or communications (e.g. the internet), urban life is paralysed. Explosions create heat and shock waves and their effects can potentially damage the wall and cables of a building as changes in the material structure occur. In this article, the authors introduce a blast load effect testing method in an empirical way. The metal microstructure deformation level is measurable by changes in resistance, because resistance is a physical property which depends on the crystal structure of the metal.

A home energy management system

In this study, an offline home energy management system that reduces electricity expense and peak demand without deteriorating residents’ contentment is considered. The main goal is to improve the system in the sense of reducing electricity expense, via interfering with appliances by means of interrupting as well as shifting their operation; and keeping up with the benefits of the newest technology, via plug-in hybrid electrical vehicle integration. The proposed offline home energy management system (OF-HEM) consists of smart electrical appliances, power resources (photovoltaic system, grid, backup battery), main controller, communication network and plug-in hybrid electrical vehicle. The main controller manages the power resources, appliances and plug-in hybrid electrical vehicle based on the solution of a mixed integer linear program with defined smart and energy-efficient operation constraints related to the smart appliances and power sources for data collected at the beginning of the day from the power resources and residents’ preferences. Conducted case studies demonstrate that OF-HEM significantly reduces electricity expenses and high peak demand.

Intelligent vehicle electrical power supply system with central coordinated protection

The current research of vehicle electrical power supply system mainly focuses on electric vehicles (EV) and hybrid electric vehicles (HEV). The vehicle electrical power supply system used in traditional fuel vehicles is rather simple and imperfect; electrical/electronic devices (EEDs) applied in vehicles are usually directly connected with the vehicle’s battery. With increasing numbers of EEDs being applied in traditional fuel vehicles, vehicle electrical power supply systems should be optimized and improved so that they can work more safely and more effectively. In this paper, a new vehicle electrical power supply system for traditional fuel vehicles, which accounts for all electrical/electronic devices and complex work conditions, is proposed based on a smart electrical/electronic device (SEED) system. Working as an independent intelligent electrical power supply network, the proposed system is isolated from the electrical control module and communication network, and access to the vehicle system is made through a bus interface. This results in a clean controller power supply with no electromagnetic interference. A new practical battery state of charge (SoC) estimation method is also proposed to achieve more accurate SoC estimation for lead-acid batteries in traditional fuel vehicles so that the intelligent power system can monitor the status of the battery for an over-current state in each power channel. Optimized protection methods are also used to ensure power supply safety. Experiments and tests on a traditional fuel vehicle are performed, and the results reveal that the battery SoC is calculated quickly and sufficiently accurately for battery over-discharge protection. Over-current protection is achieved, and the entire vehicle’s power utilization is optimized. For traditional fuel vehicles, the proposed vehicle electrical power supply system is comprehensive and has a unified system architecture, enhancing system reliability and security.

Abstract 17426: Pulmonary Vein Isolation ‘Rewires’ Electrical Communications to Enhance Small-world Network Topology During Atrial Fibrillation

Recent evidence suggests that pulmonary vein isolation (PVI) may perturb the electrophysiological substrate for maintenance of atrial fibrillation (AF). Our previous work indicates that information theory metrics can quantify electrical communications during arrhythmia. We hypothesized that PVI ‘rewires’ the electrical communication network during AF such that the topology exhibits higher levels of small-world network properties, with higher clustering coefficient and lower path length, than would be expected by chance. Thirteen consecutive patients (n=6 with prior PVI and n=7 without) underwent AF ablation using a 64-electrode basket catheter in the left atrium. Multielectrode recording was performed during AF for 60 seconds, followed by PVI. Mutual information was calculated from the time series between each pair of electrodes using the Kraskov-Stögbauer-Grassberger estimator. The all-to-all mutual information matrix (64x64; Figure, upper panels) was thresholded by the median and standard deviations of mutual information to build a binary adjacency matrix for electrical communication networks. The properties of small-world network ( swn ; ‘small-world-ness’) were quantified by the ratio of the observed average clustering coefficient to that of a random network over the ratio of the observed average path length to that of a random network. swn was expressed in normal Z standard deviation units. As the binarizing threshold increased, the Z-score of swn decreased (Figure, lower panel). However, the Z-score at each threshold value was consistently higher with prior PVI than those without (p<0.05). In conclusion, electrical communication network during AF with prior PVI is associated with higher levels of small-world network properties than those without. This finding supports the concept that PVI perturbs the underlying substrate. In addition, swn of electrical communication network may be a promising metric to quantify substrate modification.

The Power Cable Online Monitor and Protect in Application System

】 The solution of power optical cable online monitoring and cable protection equipment roasted the perfect combination of applications,which can be solved for fiber optic cable line protection, fault location and reduce equipment loss, improve security. Through optical protection equipment improvement, it can increase light protected internal OTDR monitoring channel to achieve the protection of optical communication services and the safeguard of the route line monitoring standby position, and the loss from the original equipment involved 7dB down 3dB, which effectively improve safety and quality of electric power communication optical fiber communication network, and improve management of power optical fiber communication network.

Hierarchical Communication Network Architectures for Offshore Wind Power Farms

Nowadays, large-scale wind power farms (WPFs) bring new challenges for both electric systems and communication networks. Communication networks are an essential part of WPFs because they provide real-time control and monitoring of wind turbines from a remote location (local control center). However, different wind turbine applications have different requirements in terms of data volume, latency, bandwidth, QoS, etc. This paper proposes a hierarchical communication network architecture that consist of a turbine area network (TAN), farm area network (FAN), and control area network (CAN) for offshore WPFs. The two types of offshore WPFs studied are small-scale WPFs close to the grid and medium-scale WPFs far from the grid. The wind turbines are modelled based on the logical nodes (LN) concepts of the IEC 61400-25 standard. To keep pace with current developments in wind turbine technology, the network design takes into account the extension of the LNs for both the wind turbine foundation and meteorological measurements. The proposed hierarchical communication network is based on Switched Ethernet. Servers at the control center are used to store and process the data received from the WPF. The network architecture is modelled and evaluated via OPNET. We investigated the end-to-end (ETE) delay for different WPF applications. The results are validated by comparing the amount of generated sensing data with that of received traffic at servers. The network performance is evaluated, analyzed and discussed in view of end-to-end (ETE) delay for different link bandwidths.

방호 시설 크기에 따른 전계강도 및 차폐 효과 비교

In modern times, threat of high power electromagnetic wave is increasing. When the electrical grid and communication network are attacked by these high power electromagnetic wave, the whole infrastructure is paralyzed. To protect the infrastructure from these high power electromagnetic wave threat, the shielding facility that can block high power electromagnetic wave is constructed. Also shielding effectiveness evaluation about the constructed facility is important. But, because of space efficiency and saving of construction cost to construct the actual shielding facility, the shielding room wall is generally adjacent to exterior concrete structures. As space between shielding facility wall and concrete structures is very small, arranging the transmitting antenna exterior shielding facility is realistically difficult. Therefore, in this research, The shielding effectiveness measurement plan in the state of exterior narrow space of HEMP shielding facility is presented. And to apply this plan, The influence of shielding effectiveness according to the size of the shielding facility is analyzed.

A Simulated Annealing-Based Overload Control Algorithm to Application Servers in Next Generation Electric Communication Networks

We study the overload control problem of application server in the next generation electric communication network in this paper. We introduce an energy efficiency overload control algorithm based on simulated annealing. Firstly, by considering the overload control and energy efficiency, we construct the relations function between the input rate control and energy efficiency using rate allocation. Then, we construct the optimal overload control model of energy efficiency by regarding this relation function as objective function and overload control as constraint conditions. Thirdly, we use simulated annealing algorithm to solve this model, and then obtain the optimal solution during the iterative process. The simulation results show that our algorithm is feasible and effective.

Vulnerability of Smart Grids With Variable Generation and Consumption: A System of Systems Perspective

This paper looks into the vulnerabilities of the electric power grid and associated communication network, in the face of intermittent power generation and uncertain demand within a complex network framework of analysis of smart grids. The perspective is typical for the system of systems analysis of interdependencies in a critical infrastructure (CI), i.e., the smart grid for electricity distribution. We assess how the integration of the two systems copes with requests to increase power generation due to enhanced power consumption at a load bus. We define adequate measures of vulnerability to identify the most limiting communication time delays. We quantify the probability that a reduction in the functionality of the communication system yields a faulty condition in the electric power grid, and find that a factual indicator to quantify the coupling strength between the two networks is the frequency of load-shedding actions due to excessive communication time delay. We evaluate safety margins with respect to communication specifications, i.e., the data rate of the network, to comply with the safety requirements in the electric power grid. Finally, we find a catastrophic phase transition with respect to this parameter, which affects the safe operation of the CI.