Smart Transmission Grid Research Articles

Adaptive electronic relay for smart grid based on self-healing protection.

The protection system is crucial for grid stability and safeguarding essential components, including generators, transformers, transmission systems, and power connections. The smart grid system increases the flexibility and complexity of the power system, making fault detection and isolation the primary challenges for the protection system. This paper presents an optimal protection solution using an adaptive electronic relay to enhance reliability and enable self-healing. The proposed protection algorithm quickly detects faults and automatically isolates them from the rest of the healthy system in 25ms. The relay operation algorithm has been validated using MATLAB SIMULINK software. The results confirm the effectiveness of the proposed smart electronic relay in various sections of the smart grid system, including transformers, transmission and distribution.

Empowering the Future : The Vision of Smart Transmission Grids

In the quest for an adaptable, dependable, and sustainable energy supply, the modern power grid necessitates a transformative upgrade towards intelligence. While substantial efforts have been devoted to envisioning and advancing smart power grids in the United States and Europe, the focus has predominantly centered on the distribution grid and demand-side management, leaving the holistic perspective of the transmission grid within the context of smart grids somewhat obscured. This paper proposes a distinct vision for the future of smart transmission grids, delineating their pivotal attributes. In this envisioned framework, each smart transmission grid emerges as a cohesive, integrated system comprising three interrelated smart components: smart control centers, smart transmission networks, and smart substations. The paper meticulously outlines the characteristics and functionalities of each of these three essential components, elucidating the enabling technologies necessary to realize their envisioned capabilities. By conceptualizing smart transmission grids as multifaceted systems driven by intelligent components, this vision underscores the potential for enhancing grid efficiency, reliability, and sustainability. Through the seamless integration of advanced control centers, transmission networks, and substations empowered by cutting-edge technologies, smart transmission grids aim to optimize grid operations, facilitate dynamic energy management, and foster resilience against emerging challenges and disruptions.

The application of the internet of things technology in the smart grid

The development of electric power and the energy industry is an important guarantee for national economic development. With the explosion of population and the development of science and technology, the power system needs to be more intelligent and networked to facilitate management and optimization. In recent years, the Internet of Things (IoT) technology has continued to develop through the combination of Internet technology and sensor technology, and the fast network transmission speed as well as the miniaturization and refinement of sensing can help the construction of the smart grid. This paper analyzes the application of IoT technology in the smart grid, including different types of smart grid architecture and the practical application of the IoT technology in the whole process of power transmission. Besides, the paper also discusses different application links and network levels. At present, the IoT technology has been applied to the smart grid information collection, transmission, and processing process, participating in information management in the power station, power transmission, substation, and other links. However, due to the complexity of processing the massive data of the power grid and the multiple network connections during the transmission process, ensuring the security of information and networks has become a challenge. While realizing high-speed communication, it is necessary to ensure the security of users as well as the information communication and networks.

Smart grid line fault detection based on deep learning image recognition algorithm

Abstract Amid the rapid evolution of smart grids, stringent demands for reliability, safety, and efficiency have escalated for transmission lines. Nevertheless, given their extensive coverage and the complexity of their environments, traditional inspection techniques struggle to meet the rigorous standards of real-time monitoring and precision. This paper introduces a novel fault detection approach for smart grid transmission lines, leveraging advanced deep-learning image recognition algorithms. This method improves the YOLOv5 series models by combining the Convolution Attention Module (CBAM), Bidirectional Feature Pyramid Network (BiFPN), and MobileNet-V3 as the feature extraction network of YOLOv5 to achieve defect detection of hardware on transmission lines. CBAM improves the model’s sensitivity to tiny defects by focusing on key areas and features. BiFPN improves detection accuracy and robustness through efficient fusion of multi-scale features. Furthermore, the integration of MobileNet-V3 enhances both the efficiency and precision of feature extraction, ultimately elevating the overall model’s performance. Experimental results show that compared with the original YOLOv5 model, the improved algorithm can achieve 92.89% accuracy and 84.10% recall, which is better than other mainstream target detection algorithms. Especially in the detection of defects in small targets and complex backgrounds, the improved model shows stronger robustness and adaptability. This provides strong technical support for the efficient operation and maintenance of smart grids.

Assessment of extremely low frequency electric and magnetic field of 400kV transmission lines and substations in Oman

The present study is centered on the investigation of longitudinal and lateral profiles of Extremely low-frequency Electromagnetic field experiments conducted at three distinct locations in Oman. The investigation encompasses findings obtained from 400kV transmission lines and substations. The analysis of electric and magnetic fields emitted by transmission lines was conducted using an EHP-50F E&H field analyzer sensor set and an environmental meter. The measurements were conducted at 400kV transmission lines or to a distance of the insignificant field at the high-voltage substation, various components such as power transformers, CT (current transformers), PT (potential transformers), circuit breakers, reactors, earth switches, transport couplers, lightning arrestors, and other. This research in Oman marks the initial exploration of various factors pertaining to the Oman Electricity Transmission Company (OETC) and its technical standards, which are founded on optimal practices. These factors encompass the interphase spacing, the spacing between conductors within a bundle of twin conductors, the configuration of phases on a tower, the crosssectional area of conductors, and similar considerations. The proposed study aims to support the Sultanate of Oman's objective of establishing a high-quality smart transmission grid by 2030. This system will facilitate the efficient, reliable, and secure transfer and distribution of power, while also offering economic benefits. This research aims to cater to the needs of students and engineers by offering a highly practical approach that utilizes appropriate equipment. This article presents a systematic approach to the implementation of a smart transmission grid, incorporating the aforementioned attributes.

Research on the Structural Optimization of the Clean Energy Industry in the Context of Dual Carbon Strategy—A Case Study of Sichuan Province, China

As a major province for hydroelectric power in China, Sichuan Province has witnessed a great amount of seasonal characteristics in its hydroelectric power, endowing the clean energy industry in Sichuan with the characteristics of unstable supply in different seasons, strong power transmission capacity, and low production capacity of other non-fossil energy sources (except hydroelectric power). In this study, the mathematical model method was used to construct a structural optimization model of the clean energy industry in Sichuan Province, and to enable a quantitative analysis of the rationalization of the clean energy industrial structure in Sichuan Province. The results are proved from the cost-effectiveness of low carbon emission that hydroelectric power > wind power > photovoltaic power > natural gas > coal > oil. This study shall find the theoretical structure of the clean energy industry in Sichuan Province in 2030 with a prediction of Sichuan Province’s total future energy output and a constraint of its industrial structure model of clean energy. This paper suggests that Sichuan Province should give priority to the development of non-fossil energy sources, increase the development and utilization of power transmission channels in wet seasons, and develop clean energy and high energy consumption industries and the construction of pumped storage power stations, so as to reduce and avoid the waste of energy resources. It is also suggested that Sichuan Province should focus on developing clean energy with the capability of peak shaving, such as hydrogen energy and natural gas, while developing smart grid and long-distance transmission technology to strengthen energy conservation and emissions-reduced power generation. On this basis, Sichuan will focus on the development and utilization of natural gas as an alternative to high-carbon energy, with a view to optimizing its industrial structure of clean energy and helping China achieve the dual-carbon goals.

Pretrained Configuration of Power-Quality Grayscale-Image Dataset for Sensor Improvement in Smart-Grid Transmission

The primary source of the various power-quality-disruption (PQD) concerns in smart grids is the large number of sensors, intelligent electronic devices (IEDs), remote terminal units, smart meters, measurement units, and computers that are linked by a large network. Because real-time data exchange via a network of various sensors demands a small file size without an adverse effect on the information quality, one measure of the power-quality monitoring in a smart grid is restricted by the vast volume of the data collection. In order to provide dependable and bandwidth-friendly data transfer, the data-processing techniques’ effectiveness was evaluated for precise power-quality monitoring in wireless sensor networks (WSNs) using grayscale PQD image data and employing pretrained PQD data with deep-learning techniques, such as ResNet50, MobileNet, and EfficientNetB0. The suggested layers, added between the pretrained base model and the classifier, modify the pretrained approaches. The result shows that advanced MobileNet is a fairly good-fitting model. This model outperforms the other pretraining methods, with 99.32% accuracy, the smallest file size, and the fastest computation time. The preprocessed data’s output is anticipated to allow for reliable and bandwidth-friendly data-packet transmission in WSNs.

Optimal Frequency Control Management of Grid Integration PV/Wind/FC/Storage Battery Based Smart Grid Using Multi Objective Particle Swarm Optimization MOPSO and Model Predictive Control (MPC)

This article forecasts the performance of smart-grid electrical transmission systems and integrated battery/FC/Wind/PV storage system renewable power sources in the context of unpredictable solar and wind power supplies. The research provided a hybrid renewable energy sources smart grid power system electrical frequency control solution using adaptive control techniques and model predictive control (MPC) based on the Multi-Objective Practical Swarm Optimization Algorithm MOPSO. To solve the problems of parameter tuning in Load Frequency Control, the suggested adaptive control approach is utilized to accomplish on-line adjustment of the Load Frequency Control parameters. During the electrical grid's integration, the system under investigation is a hybrid Wind/PV/FC/Battery smart grid with variable demand load. To achieve optimal outcomes, all of the controller settings for various units in power grids are determined by means of a customized objective function and a particle swarm optimization method rather than a regular objective function with fluctuating restrictions. To suppress the consumption and generation balance, MPCs were designed for each of the Storage Battery, Wind Turbine Generation, and the model Photovoltaic Generation. In addition, demand response (real-time pricing) was used in this scheme to reduce the load frequency by adjusting the controlled loads. The suggested control strategy is evaluated in the Simulink /MATLAB environment in order to analyse the suggested approach's working in the power system, as well as its effectiveness, reliability, robustness, and stability. The simulation findings show that the proposed control method generally converges to an optimal operating point that minimises total user disutility, restores normal frequency and planned tie-line power flows, and maintains transmission line thermal restrictions. The simulation results further indicate that the convergence holds even when the control algorithm uses inaccurate system parameters. Finally, numerical simulations are used to illustrate the proposed algorithm's robustness, optimality, and effectiveness. In compared to previous methodologies, the system frequency recovers effectively and efficiently in the event of a power demand disturbance, as demonstrated. A sensitivity test is also performed to assess the suggested technique's effectiveness.

A method of data transmission technology for line condition monitoring in smart transmission grid

In order to make the operation of the line more safe and reliable, the state monitoring is needed and the remote transmission of data is realized on this basis. This paper proposes a variety of communication modes suitable for transmission line condition monitoring data transmission. The corresponding communication system design is given for different application conditions. The development and application of data transmission technology for condition monitoring of transmission lines are discussed in combination with two different schemes of typical design and distributed intelligent fault diagnosis system.

Data compression techniques for Phasor Measurement Unit (PMU) applications in smart transmission grid

Abstract The advances in Wide Area Measurement Systems (WAMS) and deployment of a huge number of phasor measurement units (PMUs) in the grid are generating big data volume. This data can be used for a variety of applications related to grid monitoring, management, operation, protection, and control. With the increase in this data size, the respective storage capacity needs to be enhanced. Also, communication infrastructure readiness remains bottleneck to transfer this big data. One of the probable solutions could be transmitting compressed data. This paper presents techniques for data compression in the smart transmission system using singular values decomposition (SVD) and the eigenvalues decomposition (EVD). The SVD and EVD based principal component analysis (PCA) techniques are applied to the real-time PMU data collected from extra-high voltage (EHV) substations of transmission utility in the western regional grid of India. Adequacy of data is checked by Kaiser-Meyer-Olkin (KMO) test in order to have the satisfactory performance of these techniques towards achieving the objective of efficient data compression. Results are found satisfactory gives compression more than 80% using real time data.

A network design algorithm for multicast communication architectures in smart transmission grids

In future smart transmission grids, there are distributed applications that will benefit from the deployment of Internet Protocol (IP) multicast technology for communication. Sharing of Routable-Sample Values (R-SV) and Routable-GOOSE among the digital substations for wide-area monitoring, protection, and control (WAMPAC) applications will be needed. Using multicast for distribution of R-SVs is resource-efficient and offers a simpler configuration with only the interested substations needing reconfiguration. However, the demands for such concurrent delivery of R-SV data will put constraints on the underlying supporting networking infrastructure. For example, it must be ensured that the paths taken to route data traffic are within the bounds of delay to achieve the aims of the WAMPAC application. In this paper, we look at the problem of network topology augmentation through link additions. We present a heuristic algorithm that finds a set of links to be added to a network topology such that the multicast distribution tree for a multicast configuration is bounded by latency, which is set as the hop-count threshold. Our results show that by adding a few new links to the network topology, the delay incurred by the multicast traffic from sources to destinations can be reduced.

A mitigation scenario for Latin American power-related carbon dioxide emissions

ABSTRACT The International Energy Agency (IEA) has proposed an ambitious carbon dioxide emission mitigation scenario with specific recommendations for Latin American and the Caribbean (LAC) countries. However, this mitigation scenario entails significant limitations. The expected electricity production for the region is quite low compared to global average figures. This situation could endanger the sustainable development of the region. In this paper, we discuss an alternative mitigation scenario that seeks the compliance of both climate objectives and future energy requirements. This new scenario is based on the widespread integration of smart grids and renewable energies. High capacity smart transmission grids could enlarge existing transnational electricity markets. Results show that Latin America could contribute with 4.1% of the global mitigation effort up to 2040 (the IEA’s 450 S scenario for the region is 3.6%) with an additional investment of 7% in large-scale renewable-based generation plants and HDVC transmission links. As a main result, future regional generation output is aligned with the requirements of national policy scenarios outlined at the climate convention.

Strategic management of stochastic power losses in smart transmission grids

Strategic management of stochastic power losses in smart transmission grids

Enhancing WAMS Communication Network Against Delay Attacks

Smart grid is a typical cyber-physical system, which presents the dependence of power system operations on cyber infrastructure for control, monitoring, and protection purposes. The rapid deployment of synchrophasor measurements units (PMUs) supporting wide area measurement system (WAMS) in the smart grid transmission system has opened opportunities to enhance the grid operations through the introduction of WAMS applications. However, the increased deployment of synchrophasor technologies increases the effective attack surface available to attackers and exposes WAMS applications. Such applications have strict and stringent delay requirements, e.g., end-to-end delay as well as delay variation between measurements from different PMUs. In this paper, we present a mathematical model for constructing forwarding trees for PMUs’ measurements which satisfy the end-to-end delay as well as the delay variation requirements of WAMS applications at data concentrators. We illustrate that simple shortest path routing will result in larger fraction of data drop and that our method will achieve better delivery rate. We also validate our method against delay attacks using real-time co-simulation.

Optimal Tree Construction Model for Cyber-Attacks to Wide Area Measurement Systems

The rapid deployment of phasor measurements in smart grid transmission system has opened opportunities to utilize new applications and enhance the grid operations. Thus, the smart grid has become more dependent on communication and information technologies, such as wide area measurement systems (WAMSs). WAMS are used to collect real-time measurement from sensors across widely dispersed areas. Such systems will improve real-time monitoring and control; however, recent studies have pointed out that the use of WAMS introduces significant vulnerabilities to the smart grid that can be leveraged by attackers. Therefore, preventing or reducing the damage of cyber attacks is critical to the security of the smart grid. In this paper, we focus on the relation between cyber-attack propagation and IP multicast routing, which is an essential aspect to the collection of phasor measurement units (PMUs) measurements. To this extent, we formulate the problem as the construction of a multicast tree that minimizes the propagation of cyber-attacks, while satisfying real-time and capacity requirements. The proposed attack propagation multicast tree is evaluated using IEEE 14-bus, IEEE 24-bus, IEEE 39-bus, the New England 39-bus, and IEEE 57-bus test systems.

Highlighting the Deficiencies in Some Existing Optimal PMU Placement Techniques

Synchrophasor technology is receiving a global acceptance for electric power grid Wide Area Measurement System, (WAMS), an important function in a smart power transmission grid. A critical challenge in the synchrophasor technology deployment is the optimal choice of Phasor Measurement Unit (PMU) locations on the power grid. Researchers have proposed several techniques and algorithms in this respect. This work evaluated some of the major techniques and established that the available techniques and the factors they considered are not sufficient for a real-life optimal PMU placement (OPP). It also pointed to a method that could be applied to achieve a practical and robust solution for effective PMU placement for synchrophasor applications in a real-life electric power grid. It, therefore, calls for a shift in paradigm in the studies for the optimal PMU placement locations.

A PMU-Based Method for Smart Transmission Grid Voltage Security Visualization and Monitoring

With the rapid growth of usage of phasor measurement units (PMUs) for modern power grids, the application of synchronized phasors (synchrophasors) to real-time voltage security monitoring has become an active research area. This paper presents a novel approach for fast determination of loading margin using PMU data from a wide-area monitoring system (WAMS) to construct the voltage stability boundary (VSB) of a transmission grid. Specifically, a new approach for online loading margin estimation that considers system load trends is proposed based on the Thevenin equivalent (TE) technique and the Mobius transformation (MT) technique. A VSB is then computed by means of real-time PMU measurements and is presented in a complex load power space. VSB can be utilized as a visualization tool that is able to provide real-time visualization of the current voltage stability situation. The proposed method is fast and adequate for online voltage security assessment. Furthermore, it enables us to significantly increase a system operator’s situational awareness for operational decision making. Simulation studies were carried out using different sized power grid models under various operating conditions. The simulation results are shown to validate the capability of the proposed method.

Application of WAMS and SCADA Data to Online Modeling of Series-Compensated Transmission Lines

Transmission line parameters are indispensable prerequisites for power system studies such as power flow analysis, state estimation, congestion management, protective relaying, etc. Since the line parameters vary in time due to various reasons such as environmental condition changes, online estimation of line parameters is thus crucial to assure reliable outcome of system studies. Phasor measurement units (PMUs), as the basis of measurement infrastructure in a smart transmission grid, turn out the online estimation of transmission line parameters feasible. In this paper, a practical method for online estimation of series-compensated transmission lines parameters is devised in which PMU and supervisory control and data acquisition data are jointly used. To do so, the nonlinear weighted least square error algorithm is employed. Additionally, the proposed method is extended to set forth the parameter estimation of three-phase model of a transmission line needed for unbalanced system studies. Unlike the existing methods, which necessitate PMU installation at both sides of the lines, the proposed method works with few PMUs and has admirable practical merits in nowadays power systems. Case studies through software and hardware simulation efforts demonstrate validity of the modeling approach.

A Multi-Objective Framework for Enhancing the Reliability and Minimizing the Cost of PMU Deployment in Power Systems

Wide-area monitoring, protection, and control (WAMPAC) is a key factor in the implementation of smart transmission grids. WAMPAC has a crucial role in detection and prevention of widespread events with an ultimate goal of improving the electricity service reliability. Several mathematical techniques were proposed for the optimal phasor measurement units (PMU) placement (OPP) problem which represents the first step toward the development of WAMPAC. These techniques consider either the solution to the network observability or realization of specific PMU applications. This paper proposes a multi-objective framework for OPP which emphasizes the reliability of power systems. The objective functions minimize the investment cost and maximize the system reliability. Since the objectives are in conflict, the non-dominated sorting genetic algorithm II approach is adopted as an intelligent state sampling tool to find non-dominated solutions (Pareto front). The final placement scheme among Pareto points is chosen by a Fuzzy decision making approach.

Reliable Communication Networks for Smart Grid Transmission Systems

In this paper, we discuss the communications reliability requirements posed by the smart power grid with a focus on communications in support of wide area situational awareness. Implementation of wide area situational awareness relies on both transmission substation networks and wide area optical networks. We study the reliability of a sample communications network of the California Power Grid and find that its reliability falls short of proposed requirements. To overcome this issue, we consider the problem of designing the substation network and the wide area network to meet the reliability requirements while minimizing the network cost. For the wide area network design problem, we propose two alternate design approaches, namely: (1) following the power lines and (2) a mesh based design interconnecting the nodes. For the first approach we develop two greedy iterative heuristics and a heuristic integer linear programming (H-ILP) model using minimum cut-sets for network reliability optimization. The greedy iterative algorithms outperform the H-ILP approach in terms of cost, but require a larger amount of computing resources. Both proposed models are in fact complementary and thus provide a framework to optimize the reliability of smart grid communications networks restricted to following the power lines. In the second approach a greenfield mesh network method is proposed based on starting with a minimum spanning tree which is then augmented through a greedy heuristic into a mesh. Comparative numerical results show that the reliable mesh design has advantages in terms of the number of links and total link distance needed.