Power Line Communication Research Articles

Cooperative Bit Allocation in In-Band Full-Duplex Power Line Communication

Cooperative Bit Allocation in In-Band Full-Duplex Power Line Communication

Investigation of Equivalent Radiated Emissions of Photovoltaic Power Line Communications through Scaled Model

Investigation of Equivalent Radiated Emissions of Photovoltaic Power Line Communications through Scaled Model

Power Line Communication Application for Enhanced Partial Discharge Monitoring: From Theory to Application

Power Line Communication Application for Enhanced Partial Discharge Monitoring: From Theory to Application

Detection of Apparent Defects in HPLC/Dual Mode Portable Sorting Device Based on Deep Learning and Image Processing

Abstract As the growth of automated detection technology, traditional manual detection has gradually been replaced. To improve the effectiveness of defect detection, a HPLC/dual mode portable sorting device with deep learning and image processing is raised for apparent defect detection. The product image is segmented using flood filled mean shift method, and defect detection is achieved using Yolo v3 algorithm. An LME2918 chip is the main component of the communication module in the portable device. Based on experimental data, image segmentation accuracy can range from 80% to 100%, and image matching accuracy can range from 85% to 95%. Under the power line carrier mode, the average success rate of apparent defect detection in portable sorting devices can reach 85%, and the change in success rate is not significant, indicating that the detection is relatively stable; Under wireless communication mode, the average success rate can reach 83%, and the change in success rate is relatively obvious, because wireless communication is easily affected by the external environment. The experimental data shows that the defect detection effect of the HPLC/dual mode portable sorting device based on deep learning and image processing meets the design requirements.

A Tutorial on Modem Coupling Circuits for Low-Voltage Power-Line Communications: Operating Principles, Trade-Offs, Design, and Safety

A Tutorial on Modem Coupling Circuits for Low-Voltage Power-Line Communications: Operating Principles, Trade-Offs, Design, and Safety

Design and Analysis of Reliable Current Differential Protection Through Improved Power-Line Communication

Design and Analysis of Reliable Current Differential Protection Through Improved Power-Line Communication

Design and Implementation of Drive and Control System for Ultrasonic Motor over Power Line Communication

In this study, remote control application of an ultrasonic motor (USM) has been achieved over the power line communication (PLC) system. Fast, practical, affordable and effective operating mode is essential for the USM. This study aimed to develop an original, efficient, effective and economical method. Drive and control of USM control has been succeeded with the developed PLC control system. A two-phase high-frequency inverter, a power line transmitter, and a power line receiver circuits have been designed to drive and control of the ultrasonic motor. Required measurements are acquired from the power line to select the most suitable communication frequency and coupling circuit impedance for the PLC system. For the communication frequency and impedance value measurements the receiver and the transmitter circuits have been designed. The PLC-controlled system has been tested for different operating conditions of the ultrasonic motor. USM control has been accomplished over the existing power line without using extra cables and interfaces for communication. The obtained results show that the PLC-controlled system is practical, reliable, cost-effective, and feasible for the remote control of the USM. This research contributes a new and essential perspective for the PLC-based remote control studies in addition to the USM drive and control strategies.

The Environmental Impacts of Radio Frequency and Power Line Communication for Advanced Metering Infrastructures in Smart Grids.

In the neighborhood area network (NAN), the advanced metering infrastructure (AMI) enables a bidirectional connection between the smart meter (SM) and the data concentrator (DC). Sensors, such as smart meter nodes or environmental sensor nodes, play a crucial role in measuring and transmitting data to central units for advanced monitoring, management, and analysis of energy consumption. Wired and wireless communication technologies are used to implement the AMI-NAN. This paper delves into a novel approach for optimizing the choice of communication medium, air for radio frequency (RF) or power lines for power line communication (PLC), between the SM and DC in the context of the AMI-NAN. The authors methodically select the specific technologies, RF and NB-PLC (narrowband power line communication), and meticulously characterize their attributes. Then, a comparative analysis spanning rural, urban, and industrial settings is conducted to evaluate the proposed method. The overall reliability performance of the AMI-NAN system requires a packet error rate (PER) lower than 10%. To this end, an efficient approach is introduced to assess and enhance the reliability of NB-PLC and RF for AMI-NAN applications. Simulation results demonstrate that wireless communication is the optimal choice for the rural scenario, especially for a signal-to-noise ratio (SNR) lower than 25 dB. However, in urban environments characterized by higher SNR values and moderately dense networks, NB-PLC gains prominence. In denser networks, it outperforms wireless communication, exhibiting a remarkable 10 dB gain for a bit error rate (BER) of 10-3. Moreover, in industrial zones characterized by intricate network topologies and non-linear loads, the power line channel emerges as the optimal choice for data transmission.

Adaptive overcurrent protection scheme coordination in presence of distributed generation using radial basis neural network

The operational performance of conventional overcurrent protection relay coordination connected to a distribution network is adversely affected by the penetration of distributed generators (DG) at different buses in the network. To address this problem, this paper proposes a novel adaptive protection coordination scheme using a radial basis function neural network (RBFNN), which automatically adjusts the overcurrent relay settings, i.e., time setting multiplier (TSM) and plug setting multiplier (PSM) based on the penetration of DGs. Short circuit currents and voltages measured at different buses are acquired using the remote terminal units (RTU) connected to different buses within the terminal network. Communication between the various remotes and local end station RTUs is through hybrid communication systems of fiber optic and power line communication system modules. The new adaptive overcurrent protection scheme is applied to the IEEE 33-bus distribution network with and without DGs, for single and multi-DG penetration using both the ETAP and MATLAB software. The simulation results show the proposed scheme significantly improves the protection coordination.

Ergodic Capacity of Power Line Communication System for Applications of Power Distribution Networks with Amplify- and- Forward Relaying

Ergodic Capacity of Power Line Communication System for Applications of Power Distribution Networks with Amplify- and- Forward Relaying

Study of Conducted Emission Characteristics Induction Stoves on 9 kHz-30 MHz Frequency

The presence of increasingly sophisticated and innovative cooking utensils such as induction cookers has changed the way of cooking by providing a high level of efficiency. Induction cookers are also a breakthrough in reducing carbon emissions and making them an important choice in energy conservation efforts. The use of induction stoves in the community still faces several obstacles such as relatively high prices, significant power consumption, and the need for special cooking containers. In addition, the development of induction stove technology can produce electromagnetic emissions in the form of conduction emissions. Conducted emission is electromagnetic interference caused by electronic devices through conductors which can be interpreted as noise currents that propagate on the conduction path and have the potential to interfere with other electronic equipment through voltage sources. In the same power grid, conducted emissions caused by induction stoves can also interfere with data signals using Power Line Carrier (PLC) at a frequency of 30-500 kHz. This study aims to understand and identify patterns of electromagnetic wave emission, namely conduction emissions produced by induction stoves. The main focus is on conducted emissions, which can affect the performance of such electronic devices. The results of research related to the characteristics of the conducted emission value of this induction stove are expected so that this household device is safer and more comfortable to use by the community and can provide a reference for the further development of induction stove technology. The test method was carried out on 4 (four) brands of induction stoves C, A, M and P under various operating conditions and cooking modes both individually and simultaneously in the frequency range of 9 KHz-30 MHz through Electromagnetic Compatibility (EMC) testing. The measured parameter is a Quasi Peak (QP) value, in accordance with CISPR standard 14.1:2020. Based on measurements in the frequency range of 9 kHz-30 MHz, individual conditions were obtained that some of the induction stoves used in this study were above the threshold values required in CISPR 14.1:2020. Based on measurements with the condition that the induction stove is operated simultaneously, the level of conducted emission decreases and there is a disturbance at a new frequency beyond the disturbance frequency at individual conditions.

Research on the development of AloT sensing module for new energy power information collection

Abstract In order to improve the ability of power communication technology to support large-scale and massive services of smart electricity consumption, this paper designs a sensing model to collect information on new energy electricity consumption. Using the arrival rate calculation method of intelligent IoT, the information on new energy electricity users is collected, and the environmental measurement data is collected with the help of intelligent sensors. Monitoring the concurrency factor of all sensors in the operation state, collecting queuing theory packet loss rate through utilization maximization objective function, and setting the average queuing length of communication nodes. On this basis, the voltage amplitude of the electrical energy sampling point is measured, and the Gaussian perceptual loss vector with non-zero mean and heteroskedasticity is performed to iteratively converge the constraint matrix and error covariance. The results show that the maximum relative errors for service delay and packet loss rate are 16.8% and 7.0%, respectively. As bandwidth increases, the queuing delay and packet loss rate decrease. The broadband power line carrier can reach up to 210 Mbps, and the micropower wireless rate can reach 38.5 kbps. The annual cycle characteristics fluctuate widely, but the cumulative error of electricity load prediction results is lower, and the prediction accuracy is high. It shows that the electricity consumption information collection sensing model provides an important reference for building a new communication network with low cost, high speed and reliability for smart electricity consumption.

Information aggregation and data compression based on PLC for distributed photovoltaic integration

The massive integration of distributed photovoltaics (PVs) into power grid causes rapid growth of data collection, which has put significant pressure on power line communication (PLC). Edge computing enables efficient data compression on edge-side gateway to reduce data size. However, it still faces challenges such as the coupling between transmission delay and compression delay, as well as the coupling between data compression ratio selection and gateway selection. In this paper, we formulate the information aggregation and data compression problem to minimize the total delay, and develop a delay-aware upper confidence bound (UCB) algorithm. It sets the negative value of delay as the learning reward to achieve delay-aware learning, and jointly optimizes gateway and data compression ratio selection based on upper confidence bound ranking and Karush-Kuhn-Tucker (KKT) conditions. Simulation results demonstrate the superior performance of the proposed algorithm.

A review on the empirical characterization of the low voltage distribution grid as a communication channel for power line communications

The electrical grid was not designed for the transmission of communication signals, which are affected by impedance variations, attenuation, and Non-Intentional Emissions (NIEs) in their propagation through the Low Voltage (LV) distribution grid. For this reason, the characterization of the electrical grid as a transmission medium is of vital importance for the correct development of Power Line Communications (PLC) technologies and the optimization of the opportunities offered by the LV distribution grid as a communication infrastructure. This paper deals with the state-of-the-art, challenges to be faced and future work of the characterization based on field trials in real scenarios. First, the features of Narrowband Power Line Communications (NB-PLC) and Broadband Power Line Communications (BB-PLC) technologies are outlined, including a brief comparison between the already developed NB-PLC protocols and providing an overview of the evolution of BB-PLC. Then, the parameters to be measured on the characterization of the LV grid are described, in addition to including the particularities and problems of the measurement systems designed for this aim. Finally, the state of the art and future work concerning the characterization of the outdoor LV grid as a transmission medium based on field trials are gathered.

Application of G.hn Broadband Powerline Communication for Industrial Control Using COTS Components

Broadband powerline communication is a technology developed mainly with consumer applications and bulk data transmission in mind. Typical use cases include file download, streaming, or last-mile internet access for residential buildings. Applications gaining momentum are smart metering and grid automation, where response time requirements are relatively moderate compared to industrial (real-time) control. This work investigates to which extent G.hn technology, with existing, commercial off-the-shelf components, can be used for real-time control applications. Maximum packet rate and latency statistics are investigated for different G.hn profiles and MAC algorithms. An elevator control system serves as an example application to define the latency and throughput requirements. The results show that G.hn is a feasible technology candidate for industrial IoT-type applications if certain boundary conditions can be ensured.

Performance Evaluation CSMA/CA in MAC Layer and Markov Gaussian Memory Impulse Noise Channels in PHY Layer

There is memory impulse noise in urban outdoor/indoor mobile channels, underwater acoustic channels, powerline communications (PLC) channels, etc. The prior works about network performance evaluation in impulse noise channels considered both the impulse noise in the physical (PHY) layer and CSMA/CA in the media access control (MAC) layer but they used simpler memoryless impulse noise model. In this paper, we propose to use 3-D Markov chain and power iteration method to analyze the throughput of CSMA/CA protocols with finite queue and more general memory impulse noise. The numerical results show that when the impulse noise is strong (impulse noise to Gaussian noise ratio R=150), the normalized throughput would be significantly lower than the case without impulse noise (R=0). Therefore, throughput analysis considering the impulse noise effect is essential.

Power Line Carrier (PLC) sebagai Media Pendeteksi Phasa Pelanggan Tegangan Rendah

With so many distribution substations and the number of household customers, most of whom are single-phase low voltage customers, customer phase verification becomes very important in the load balancing proces. The customer phase detection system that has been studied previously, using radio frequency communication media over the air, is considered less valid if used in border areas between 2 (two) distribution substations. It is felt that the low voltage customer phase detection method will be more valid if it is carried out via Power Line Carrier (PLC) media, namely data communication via electrical lines. And this system consists of two devices, namely a transmitter (called the Master) which is installed on the LV Panel and a receiver (called the Slave) which is carried by the mobile to the detected phase point Short distance phase detection using Power Line Carrie from transmitter to receiver has a 100% success rate in one sub-panel with a transfer speed of 9600 baudrate, with an average detection time for short distances of 5 seconds. For long distance detection, sometimes the detection time is relatively long (± 120 seconds) or even failed, possibly due to the quality of the connection along the conductor being detected, thus causing noise in the network.

Towards a low-cost sustainable broadband solution in rural areas of low and middle-income countries: Tanzania’s backhaul perspective

Although broadband internet has proven to accelerate the fulfilment of the information and communication for development (ICT4D) agenda, connectivity issues persist in some regions of the world, particularly in rural areas of Low and Middle-Income Countries (LMICs) which host 93% of the unconnected global population. Due to the lack of economic feasibility in these locations for service providers, International Telecommunication Union (ITU) has been advocating for low-cost sustainable solutions in such areas. Among the challenging broadband infrastructure segment seems to be the backhaul (middle-mile) as rural areas are remotely located from the backbone end-points. With Tanzania exemplifying LMICs, this paper presents a Techno-Economic Analysis (TEA) to compare the widely utilized backhaul (Microwave) and the promising Broadband over Power Line (BPL) towards achieving low-cost broadband solutions. To demonstrate technical viability in terms of capacity, Pathloss and MATLAB were utilized from which both technologies demonstrated the broadband-suitably capacity (161Mbps for Microwave and 168.99Mbs for BPL). From economic perspective, the Total Cost of Ownership (TCOs) for both technologies were determined using a Cost Model; BPL fared better as the cost of establishing one microwave link could have established almost 6 BPL links. Apart from adding to the body of knowledge on TEAs involving backhauls, this paper informs policymakers and other related stakeholders on the potential cost-benefit of BPL towards curbing the existing broadband connectivity gap.

Adaptive Load Balancing for Dual-Mode Communication Networks in the Power Internet of Things

As an important part of the power Internet of Things, the dual-mode communication network that combines the high-speed power line carrier (HPLC) mode and high-speed radio frequency (HRF) mode is one of the hot directions in current research. Since non-uniform transmission demands for power consumption information can lead to link congestion among nodes, improving the network load-balancing performance becomes a critical issue. Therefore, this paper proposes a load-balancing routing algorithm for dual-mode communication networks, which is achieved in dual-mode communication networks by adding alternate paths and proxy coordinator (PCO) node election mechanism. Simulation results show that the proposed algorithm achieves the load-balanced distribution of power consumption information transmission. The proposed scheme reduces the delay and packet loss rate, as well as improving the throughput of dual-mode communication compared to existing routing algorithms.

A UAV Intelligent System for Greek Power Lines Monitoring.

Power line inspection is one important task performed by electricity distribution network operators worldwide. It is part of the equipment maintenance for such companies and forms a crucial procedure since it can provide diagnostics and prognostics about the condition of the power line network. Furthermore, it helps with effective decision making in the case of fault detection. Nowadays, the inspection of power lines is performed either using human operators that scan the network on foot and search for obvious faults, or using unmanned aerial vehicles (UAVs) and/or helicopters equipped with camera sensors capable of recording videos of the power line network equipment, which are then inspected by human operators offline. In this study, we propose an autonomous, intelligent inspection system for power lines, which is equipped with camera sensors operating in the visual (Red-Green-Blue (RGB) imaging) and infrared (thermal imaging) spectrums, capable of providing real-time alerts about the condition of power lines. The very first step in power line monitoring is identifying and segmenting them from the background, which constitutes the principal goal of the presented study. The identification of power lines is accomplished through an innovative hybrid approach that combines RGB and thermal data-processing methods under a custom-made drone platform, providing an automated tool for in situ analyses not only in offline mode. In this direction, the human operator role is limited to the flight-planning and control operations of the UAV. The benefits of using such an intelligent UAV system are many, mostly related to the timely and accurate detection of possible faults, along with the side benefits of personnel safety and reduced operational costs.