Grid Deployment Research Articles

Advanced Controller System with Hybrid Renewable Sources Enabling Vehicle-To-Grid and Grid-To-Vehicle Operations

Power demand is rising worldwide, forcing the search for an alternative source to solve the imminent power crisis, which is expected to be accomplished through the deployment of grid synchronized electric vehicles (EV). Wind and solar energy are incorporated into this integration to those concerns. One smart grid innovation that permits energy exchange between the EV and the grid is vehicle to grid (V2G) technology. For the purpose of charging EVs, this research proposes employing hybrid energy. Here, the neighboring household’s linear and non linear demands are powered by the excess electricity from the photovoltaics (PV) panel, wind turbine, and AC generator that is utilized to charge the EV battery. Because of its dependability and independence from the real system model, a proportional integral (PI) controller is used to maximize the DC voltage extracted from the PV panel. The improved DC voltage overall is a result of the SEPIC converter’s improved DC output. Concurrently, an AC generator is incorporated into the system to supply extra power to the grid. An artificial neural network (ANN) controller is used to convert the power generated by the PV panel’s Sepic conversion process into an improved output that is then converted to AC using a 3 phase Voltage Source Inverter (VSI). Harmonic components in the VSI output are corrected with an LC filter to ensure grid compatibility and safe current injection into the grid. This paper discusses the usage of a bidirectional converter to adjust the EV battery’s voltage. MATLAB 2021a / Simulink software is used to simulate and validate the proposed approach.

Network Security Challenges and Countermeasures for Software-Defined Smart Grids: A Survey

The rise of grid modernization has been prompted by the escalating demand for power, the deteriorating state of infrastructure, and the growing concern regarding the reliability of electric utilities. The smart grid encompasses recent advancements in electronics, technology, telecommunications, and computer capabilities. Smart grid telecommunication frameworks provide bidirectional communication to facilitate grid operations. Software-defined networking (SDN) is a proposed approach for monitoring and regulating telecommunication networks, which allows for enhanced visibility, control, and security in smart grid systems. Nevertheless, the integration of telecommunications infrastructure exposes smart grid networks to potential cyberattacks. Unauthorized individuals may exploit unauthorized access to intercept communications, introduce fabricated data into system measurements, overwhelm communication channels with false data packets, or attack centralized controllers to disable network control. An ongoing, thorough examination of cyber attacks and protection strategies for smart grid networks is essential due to the ever-changing nature of these threats. Previous surveys on smart grid security lack modern methodologies and, to the best of our knowledge, most, if not all, focus on only one sort of attack or protection. This survey examines the most recent security techniques, simultaneous multi-pronged cyber attacks, and defense utilities in order to address the challenges of future SDN smart grid research. The objective is to identify future research requirements, describe the existing security challenges, and highlight emerging threats and their potential impact on the deployment of software-defined smart grid (SD-SG).

Smart Grid Technologies and Their Role in Sustainable Energy Management

Purpose: The general objective of this study was to analyze smart grid technologies and their role in sustainable energy management. Methodology: The study adopted a desktop research methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low cost technique as compared to field research, as the main cost is involved in executive’s time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library. Findings: The findings reveal that there exists a contextual and methodological gap relating to smart grid technologies and their role in sustainable energy management. Preliminary empirical review revealed that smart grid technologies significantly transformed energy management by enhancing sustainability, reliability, and efficiency through advanced metering, real-time analytics, and improved communication networks. These technologies enabled better integration of renewable energy sources, reduced greenhouse gas emissions, and empowered consumers with detailed energy usage information, leading to cost savings and increased energy efficiency. However, challenges such as high implementation costs, infrastructure needs, regulatory hurdles, and cybersecurity risks were identified. The study highlighted the importance of continued research, supportive policies, and public engagement to optimize smart grid deployment and achieve a more sustainable energy system. Unique Contribution to Theory, Practice and Policy: The Diffusions of Innovations Theory, Socio- Technical Systems Theory and Actor- Network Theory may be used to anchor future studies on smart grid technologies. The study recommended adopting a multidisciplinary approach to smart grid research, enhancing interoperability through standardized protocols, and investing in workforce training. It emphasized supportive regulatory frameworks, including incentives and dynamic pricing models, to promote smart grid adoption. Public awareness and engagement were deemed crucial, suggesting educational campaigns to increase consumer participation. The study highlighted the importance of international collaboration for knowledge sharing and called for continuous investment in research and development to drive technological advancements and ensure the sustainability and efficiency of smart grid systems.

The political economy of mini-grid electricity development and innovation in Kenya

Accessible and affordable energy services are a prerequisite for socioeconomic growth and poverty reduction. Yet it is estimated that 600 million people in sub-Saharan Africa will not have access to electricity in 2030. Recent research suggests that universal access to electricity will be achieved through a mix of centralized and decentralized systems and that the diffusion of these technologies is a socio-technical process involving multiple actors. These actors include firms, networks, energy users, and government agencies that interact within a political landscape to deliver innovation within energy service systems. Thus, factors related to the political economy can impact the process of innovation and warrant analysis. This study aims to provide an analysis of the political economy factors that can influence the emergence of mini grid electricity development in the African context exemplified in Kenya as a case study. The study uses the Technology Innovation Systems (TIS) lens as an analytical framework to provide a critical analysis of how political economy factors have influenced the development of mini grid electricity in Kenya. The result shows that despite the presence of some favorable conditions for innovation, political economy factors significantly impede the deployment of mini grids in Kenya. Power and vested interests have created negative competition between public and private developers, limiting knowledge and information diffusion between actors and stalling mini grid developments where they are most needed.

Smart grid deployment: from a bibliometric analysis to a survey

Smart grids are one of the last decades' innovations in electrical energy. They bring relevant advantages compared to the traditional grid and significant interest from the research community. Assessing the field's evolution is essential to propose guidelines for facing new and future smart grid challenges. In addition, knowing the main technologies involved in the deployment of smart grids (SGs) is important to highlight possible shortcomings that can be mitigated by developing new tools. This paper contributes to the research trends mentioned above by focusing on two objectives. First, a bibliometric analysis is presented to give an overview of the current research level about smart grid deployment. Second, a survey of the main technological approaches used for smart grid implementation and their contributions are highlighted. To that effect, we searched the Web of Science (WoS), and the Scopus databases. We obtained 5,663 documents from WoS and 7,215 from Scopus on smart grid implementation or deployment. With the extraction limitation in the Scopus database, 5,872 of the 7,215 documents were extracted using a multi-step process. These two datasets have been analyzed using a bibliometric tool called bibliometrix. The main outputs are presented with some recommendations for future research.

Campus Grid Deployment with Automation

Campus Grid Deployment with Automation

A Study Article of DLMS to IOT Protocol

Abstract: The DLMS (Device Language Message Specification) protocol plays a crucial role in energy metering and management. It provides a standardized communication framework for exchanging data between utility meters and data collection devices. The protocol enables interoperability, remote meter reading, and supports efficient management of energy consumption, billing, and grid operations. The DLMS protocol is essential for Internet of Things (IoT) applications as it provides a standardized method for communication between Internet of Things devices and energy meters. This facilitates the seamless integration of energy data into IoT platforms, enabling efficient monitoring, analysis, and management of energy consumption in smart grid and smart city deployments. To this end, we have developed a prototype DLMS to IoT gateway that is based on either STM32 or any other IoT module. However, we encountered a challenge in testing the prototype since we couldn't get any digital meter to conduct hands-on testing..

THE IMPACT OF SMART GRIDS ON ENERGY EFFICIENCY: A COMPREHENSIVE REVIEW

Smart grids have emerged as a key technology in the quest for energy efficiency and sustainability. This review provides a comprehensive analysis of the impact of smart grids on energy efficiency, highlighting key findings, challenges, and future directions. Smart grids leverage advanced sensing, communication, and control technologies to optimize the generation, distribution, and consumption of electricity. By enabling two-way communication between utilities and consumers, smart grids improve grid reliability, reduce energy losses, and facilitate the integration of renewable energy sources. One of the key findings of this review is the significant impact of smart grids on energy efficiency. Studies have shown that smart grids can reduce energy consumption by enabling real-time monitoring and control of energy usage. This not only helps consumers reduce their electricity bills but also reduces the overall carbon footprint of the electricity sector. However, the deployment of smart grids faces several challenges, including high upfront costs, interoperability issues, and data privacy concerns. Addressing these challenges will be crucial for the widespread adoption of smart grid technologies. Looking ahead, the future of smart grids holds great promise for further improving energy efficiency. Emerging trends such as the Internet of Things (IoT) integration, artificial intelligence (AI) algorithms, and distributed energy resources (DERs) management are expected to drive further innovation in smart grid technologies. In conclusion, smart grids have a transformative impact on energy efficiency, offering significant benefits for consumers, utilities, and the environment. However, addressing challenges such as cost and interoperability will be crucial for realizing the full potential of smart grids. By embracing emerging trends and technologies, stakeholders can further enhance the efficiency and sustainability of the electricity sector.
 Keywords: Impact, Smart Grid, Energy, Efficiency, Review.

Implementing Smart Grid Technology in Developing Countries: Challenges, Opportunities, and Pathways to Sustainable Energy Solutions

The integration of smart grid technology is becoming crucial for developing countries to address the increasing energy demands and to transition towards sustainable and reliable electricity systems. This paper discusses the significant challenges these nations face, such as outdated infrastructure, high transmission and distribution losses, and limited access to electricity. With electricity consumption projected to grow by over 50% by 2030 in emerging markets and developing economies, smart grids offer benefits including enhanced reliability, reduced losses, and better integration of renewable energy sources. However, high upfront costs, lack of skilled personnel, inadequate regulatory frameworks, and resistance to change pose substantial barriers. This study explores the potential of smart grids to transform energy systems, presenting case studies of successful implementations and highlighting strategies for overcoming barriers. Emphasis is placed on innovative financing models, capacity building, technology leveraging, and stakeholder engagement as pathways to sustainable smart grid deployment.

RETINA: Distributed and secure trust management for smart grid applications and energy trading

The rapid adoption of smart grids demands robust security and efficiency measures due to their critical role in delivering electricity and their potential for customer-oriented benefits. This article presents an innovative framework, named RETINA, which provides a resilient and secure energy trading mechanism within smart grid systems. RETINA tackles the inherent security and infrastructure challenges in smart grids by establishing a trust-based security layer and facilitating energy transactions through blockchain technology. Our proposed solution integrates Public Key Infrastructure (PKI) and the Web of Trust (WoT) concepts, promoting decentralized communication channels and robust key management. We further introduce a smart contract-based energy trading mechanism that factors trust, distance, and energy type (green or non-green) in the cost calculation. The utility and robustness of RETINA have been validated in a virtualized testbed environment with 500 nodes, demonstrating superior performance in terms of scalability and resilience compared to the existing WoT scheme. Furthermore, RETINA successfully enables a secure and efficient energy trading scheme, promoting the use of renewable energy sources and promptly recovering from market manipulation attacks. Future enhancements will include applying it to a realistic smart grid deployment and integrating additional functionalities. This groundbreaking solution can potentially revolutionize the smart grid ecosystem, addressing its current limitations and propelling the industry toward a future of advanced and secure energy exchange.

Privacy and security issues in smart grids: A survey

Smart grids have emerged as a transformative technology in the energy sector, enabling efficient electricity management, improved reliability, and integration of renewable energy sources. The necessity to promote smart grid (SG) has been recognized with a strong consensus. The SG integrates electrical grids and communication infrastructures and forms an intelligent electricity network working with all connected components to deliver sustainable electricity supplies. Many advanced communication technologies have been identified for SG applications with a potential to significantly enhance the overall efficiency of power grids. However, the widespread deployment of smart grids raises concerns about the privacy and security of the data collected and transmitted by these systems. To address these concerns, this paper proposes a comprehensive framework for ensuring privacy and security in smart grid systems. This framework includes encryption techniques, access control mechanisms, and robust authentication protocols. Additionally, this paper discusses the importance of user awareness and education in mitigating privacy and security risks. The research contributes to the existing literature on smart grid privacy and security by providing insights specific to the information technology security domain. The findings of this manuscript will be valuable for policymakers, energy providers, and researchers working towards the development of secure and privacy-preserving smart grid systems.

Characterizing optimal LPWAN access delay in massive multi-RAT smart grid deployments

Massive machine-type communications services penetrating the market, such as smart grids, differ from conventional services characterized by stochastic arrival patterns. Requiring permanent end device (ED) connectivity, control centers poll EDs over regular time intervals, leading to batch message arrivals that affect the mean access delay at the air interface. In addition, the smart grid requires high reliability and network availability that can be achieved by utilizing multiple radio access technologies in EDs. Radio access technologies (RATs), i.e., narrowband internet of things (NB-IoT) and long-term evolution machine type communication (LTE-M), have been identified as promising solutions for these use-cases. This work first reports results of an extensive performance evaluation measurement campaign showing that LTE-M can be considered a preferred option and NB-IoT as a possible backup solution for smart grids. We also show that none of the selected technologies can fully meet the requirements of smart grid use cases. We then develop a theoretical model and corresponding association algorithm for balancing traffic load between two low-power wide area network (LPWAN) technologies to minimize the mean access delay. Our results demonstrate that the optimized usage of multi-RAT EDs considerably increases the number of supported EDs operating in polling-based mode. For 500EDs utilizing a single LTE-M technology, the mean access delay is over two seconds — contradicting the minimum requirements of smart grid applications. On the other hand, multi-RAT EDs running the developed algorithm increase the service capacity by up to six times (up to 3000EDs) while still satisfying the two-second latency budget.

Iron-based catholytes for aqueous redox-flow batteries

Redox-flow batteries (RFBs) are promising electrochemical energy storage devices to load-level intermittent power from renewable energy. In particular, aqueous RFBs using aqueous electrolytes possess several advantages over nonaqueous ones, such as low fabrication cost, nontoxicity, safety, and environmental benignity. Therefore, developing high-performance, abundant, less-expensive iron-based catholytes for aqueous RFBs is essential toward their wide deployment in a power grid. In this Perspective, we summarize the recent progress of iron-based catholytes for aqueous RFBs. We emphasize that iron-based catholytes possess widely ranged redox potentials (−1.0 to 1.5 V vs standard hydrogen electrodes) and solubility in water (0.2–4.0 mol L−1), thereby providing a wide range of cell performance. The molecular design, such as ligand functionalization, counter ion mixing, and asymmetrization, allows for rationally improving solubility, redox potential, and energy density. Furthermore, we demonstrate a simple evaluation method of the redox potential of iron-based catholytes using the calculated energy levels of the lowest unoccupied molecular orbital of ligand molecules. Finally, we rationalize the design strategy of iron-based catholytes for advanced aqueous RFBs.

Node Deployment Strategy Based on Improved Particle Swarm Algorithm in Three-dimensional Underwater Sensor Networks

To enhance the monitoring quality of the underwater three-dimensional target area and address issues such as uneven node distribution, inadequate coverage, and poor connectivity in traditional deployment strategies, a new node deployment strategy based on grid deployment with a variable weight particle swarm algorithm has been proposed in this research paper. Its goal is to minimize the quantity of deployed nodes while maintaining the coverage and connectivity of the three-dimensional wireless sensor networks (UWSNs). Simulation results demonstrate that this deployment strategy leads to good performance of the sensor network, and our approach ensures maximum coverage with the same number of nodes.

Smart grid technologies and application in the sustainable energy transition: a review

ABSTRACT The smart grid is a product of the advances in computer and communication technology and power electronics that creates a more resilient, reliable and one that supports a two-way flow of electricity and information. The smart grid enables more uptake of the variable renewables like wind, solar and variable loads like the plug-in cars and improves the efficiency of power systems and facilitate several products and services supported by the grid like automatic healing and re-routing of power in case of a fault and demand side management. The deployment and use of smart grids will enhance the realization of shared goals of grid stakeholders, promote energy security, enable economic growth, and help in the mitigation of climate change.

Assessing electric mobility and renewable energy synergy in a small New Caledonia Island community

ABSTRACT In this paper, we evaluate the synergy between variable renewable energy (VRE), electric mobility, and Vehicle to Grid (V2G) deployment for a small community transitioning to a low-carbon economy. We propose an integrated deterministic modeling approach that accurately describes electric mobility activity within the electric grid in the ETEM-SG long-term capacity expansion model. This approach allowed us to keep the entire approach in the linear programming domain. We then perform a scenario analysis on the Isle of Pines case. The results show that V2G is essential for electric vehicles to make a positive contribution to the electric system by providing a supply–demand balance service. The deployment of electric vehicles allows reaching a VRE penetration rate of up to 94%, at no additional cost compared to a solution without electric vehicles, and even with a global-cost reduction of up to 5.3% thanks to a decrease of the capacity of stationary battery packs needed for storage.

Cell-Free UAV Networks: Asymptotic Analysis and Deployment Optimization

Recently, cell-free (CF) architectures, in which every user can potentially communicate with every base station, have received a lot of attention. This paper considers the uplink of fully and partially centralized CF networks where unmanned aerial vehicles serve as flying base stations (FBSs). A subset of FBSs participates in the reception of each user and a subset of users is received by each FBS. Deterministic equivalent expressions, exact asymptotically in the subset sizes and approximate for finite dimensions thereof, are derived for the spectral efficiency under Rician fading. Capitalizing on these expressions, the FBS deployment problem is investigated for different receiver architectures. The nonconvex deployment problem, tackled through a combination of gradient-based and Gibbs sampling algorithms, results in a superior performance with respect to a square grid deployment; this superiority extends to the minimum and aggregate spectral efficiency for both fully and partially centralized cell-free networks.

Impact of plug-in electric vehicles on grid integration with distributed energy resources: A review

The rise of electric vehicles (EVs) has a massive impact on the electricity grid due to the electrification of vehicles in the transportation sector. As a result, various techniques are needed to minimize the effects of charging on the grid. One of these techniques is having intelligent coordination between the various components of the EV charging network. This ensures that the network has enough electricity to support the charging needs of the vehicles. This article provides an overview of the many aspects of the EV industry and its charging infrastructure. It also provides a step-by-step approach for implementing the Vehicle to Grid (V2G) deployment, the utilization of recordings from the data by the EV battery through Artificial Intelligence and the cost-benefit analysis from effective utilization of the V2G method. The paper also explores the various aspects of the EV market and the role of aggregators and consumers. Finally, it assesses the possibility of expansion of the EV charging and grid integration system and outlines its challenges and solutions.

Grid Deployment Scheme for Enhancing Network Performance in Underwater Acoustic Sensor Networks

Grid Deployment Scheme for Enhancing Network Performance in Underwater Acoustic Sensor Networks

Lightweight Multidimensional Encrypted Data Aggregation Scheme With Fault Tolerance for Fog-Assisted Smart Grids

Encrypted data aggregation is an effective approach to preserve power consumption data confidentiality as well as reduce communication overhead in smart grids. As the core component of smart grids, smart meters periodically report encrypted multidimensional data to an aggregator gateway. However, heavy computation and communication overhead may hinder the wide applications of smart meters. Besides, once the secret key is leaked, encrypted data will be broken, thereby violating users’ privacy. In this article, we present a lightweight multidimensional encryption data aggregation (MD-EDA) scheme, enabling a grid control center to retrieve fine-grain aggregated data in a confidential way. In particular, each fog node is installed at the edge of networks, playing the role of aggregator gateway for data verification and aggregation in the same grid area. MD-EDA prevents adversaries from extracting valuable data even if the secret key is compromised. MD-EDA exploits Shamir secret-sharing technique to achieve transmission fault tolerance mechanism from smart meters to a corresponding fog node. The performance evaluation demonstrates the lightweight computation advantages of MD-EDA in the deployment of fog-assisted smart grids.