Smart Grid Solutions Research Articles

Scalability and Replicability Analysis in Smart Grid Demonstration Projects: Lessons Learned and Future Needs

This paper compares various approaches to the scalability and replicability analysis (SRA) of smart grid pilot projects, highlighting the need for a comprehensive SRA methodology as called for by the European Commission and International Energy Agency. This study addresses the need for a standardized SRA methodology and explores how three EU-funded projects—Platone, EUniversal, and IElectrix—adapted the general guidelines developed by the BRIDGE initiative. These guidelines provide recommendations for developing a comprehensive large-scale deployment analysis. The results show that while the guidelines are usable and flexible, project-specific conditions and data availability limitations—particularly in regulatory and technical analysis—can pose challenges. Some key recommendations to overcome these and facilitate future applications are identified. These include defining SRA methodologies and securing data-sharing agreements early. The lack of standardized approaches for presenting SRA results hampers cross-project comparison. Thus, creating an open-use case repository and updating the BRIDGE guidelines with more detailed examples, benchmarks, and reference networks is recommended. Additionally, linking SRA with cost–benefit analysis (CBA) is suggested in order to evaluate the commercial viability of smart grid solutions. The paper concludes that while the BRIDGE guidelines have proven to be fit for purpose, further developments are needed to facilitate their practical application in real-world projects.

Smart grid solutions for sustainable photovoltaic-electric vehicle integration in Bangladesh

Smart grid solutions for sustainable photovoltaic-electric vehicle integration in Bangladesh

Navigating the Present and Future Dynamics of Electric Vehicle Fast Charging and its Impact on Grid

As electric vehicle (EV) adoption surges worldwide, the need for fast charging infrastructure becomes paramount. Fast charging technology alleviates range anxiety and bolsters EV practicality. This comprehensive analysis delves into current challenges and future prospects surrounding EV fast charging and its grid impact. Examining the state of fast charging technology, it scrutinizes charging standards, connector types, and power levels across global regions. Emphasis is placed on key market players and the imperative for interoperability and standardization to seamlessly integrate EVs into the power grid. Voltage fluctuations, harmonics, and power factor issues stemming from rapid, high-power charging pose technical hurdles. Solutions like advanced power electronics, grid management tactics, and enhanced communication between EVs and the grid are explored to uphold stability and power quality. Consideration is given to energy sources fueling fast chargers, including renewable integration and environmental repercussions. Economic facets, encompassing infrastructure deployment costs and grid upgrade analyses, are examined amidst escalating electricity demand and potential grid expansion needs. A forward-looking perspective addresses future challenges and opportunities. This includes advancements in battery tech, smart grid solutions, and bidirectional power flow potential between EVs and the grid. Index Terms: Battery electric vehicles (BEVs), Grid, Fast Charging, plug-in hybrid electric vehicles (PHEVs).

A Comprehensive Review of Developments in Electric Vehicles Fast Charging Technology

Electric vehicle (EV) fast charging systems are rapidly evolving to meet the demands of a growing electric mobility landscape. This paper provides a comprehensive overview of various fast charging techniques, advanced infrastructure, control strategies, and emerging challenges and future trends in EV fast charging. It discusses various fast charging techniques, including inductive charging, ultra-fast charging (UFC), DC fast charging (DCFC), Tesla Superchargers, bidirectional charging integration, and battery swapping, analysing their advantages and limitations. Advanced infrastructure for DC fast charging is explored, covering charging standards, connector types, communication protocols, power levels, and charging modes control strategies. Electric vehicle battery chargers are categorized into on-board and off-board systems, with detailed functionalities provided. The status of DC fast charging station DC-DC converters classification is presented, emphasizing their role in optimizing charging efficiency. Control strategies for EV systems are analysed, focusing on effective charging management while ensuring safety and performance. Challenges and future trends in EV fast charging are thoroughly explored, highlighting infrastructure limitations, standardization efforts, battery technology advancements, and energy optimization through smart grid solutions and bidirectional chargers. The paper advocates for global collaboration to establish universal standards and interoperability among charging systems to facilitate widespread EV adoption. Future research areas include faster charging, infrastructure improvements, standardization, and energy optimization. Encouragement is given for advancements in battery technology, wireless charging, battery swapping, and user experience enhancement to further advance the EV fast charging ecosystem. In summary, this paper offers valuable insights into the current state, challenges, and future directions of EV fast charging, providing a comprehensive examination of technological advancements and emerging trends in the field.

Saudi Arabia’s Journey toward a Renewable Future

Recent statistics indicate that as of 2023, the global renewable energy capacity has reached new heights, with Saudi Arabia significantly contributing to this growth through its strategic initiatives. The kingdom is particularly focusing on harnessing solar power, given its abundant sunlight, and is also exploring wind energy, leveraging its vast desert landscapes. These efforts are part of Saudi Arabia’s broader strategy to become a global leader in renewable energy. This paper provides a detailed exploration of Saudi Arabia’s ambitious journey from a fossil-fuel-dominated energy sector to a more sustainable, renewable-energy-driven future. Anchored in the broader context of global energy trends, the study emphasizes the critical shift toward renewable resources, with a particular focus on Saudi Arabia’s unique position in this global movement. Key to this transition is Saudi Arabia’s Vision 2030, a strategic framework that guides the country’s renewable energy policies and initiatives. A comprehensive review of these policies, including other governmental and international collaborations that support renewable energy development, is offered. The current state of renewable energy in Saudi Arabia is assessed, including an overview of existing projects and production statistics. The paper also explores emerging technologies such as energy storage systems and smart grid solutions, emphasizing their role in Saudi Arabia’s energy transition. An impact assessment is conducted to understand the environmental, economic, and social effects of this energy shift. The paper also includes a comparative analysis of other countries’ renewable energy transitions, extracting lessons and best practices applicable to the Saudi context. Strategic recommendations and reflections on Saudi Arabia’s future role in the global energy landscape are provided for stakeholders in energy policy, environmental planning, and sustainable development.

Measuring the digitalisation of electricity distribution systems in Europe: Towards the smart grid

This paper proposes a set of digitalisation indicators focused on measuring the different digital capabilities and infrastructure of electricity distribution systems, as opposed to previous indicators which have mainly focused on performance and quality of service aspects.The indicators are classified according to the pillars of digitalisation: sensor and actuator, connectivity, data processing, and digital culture. They are use-case-agnostic and do not require a huge amount of information. In addition to this, three possible new applications of these indicators for distribution system operators and regulatory authorities are identified and discussed.The extensive use of these indicators in Europe could allow the development of fruitful collaborations between distribution system operators, allow the identification of cause–effect relations between grid performance and digital infrastructure, and improve the replicability of innovative smart grid solutions. However, this will only be possible if regulators promote the adoption of the proposed indicators and the dissemination of their results.

Leveraging 5G Network Capabilities for Smart Grid Communication

This paper presents a comprehensive investigation into the architecture and components of 5G networks, focusing on their suitability for smart grid applications. With the increasing complexity and demands of modern energy infrastructure, there is a growing need for reliable and low-latency communication systems to support critical smart grid operations. This paper explores key features of 5G networks, including network slicing, massive MIMO (Multiple Input Multiple Output), and low-latency communication protocols like URLLC (Ultra-Reliable Low Latency Communication), and examines how these features can be harnessed to address the unique requirements of smart grid environments. Through a detailed analysis of each component, this paper sheds light on the design considerations, deployment strategies, and performance implications of leveraging 5G technology for smart grid communication. Furthermore, practical insights, challenges, and future research areas are discussed to guide the development of next-generation smart grid solutions.

Smart Grid Solutions for Loss Minimization and Voltage Profile Enhancement using Genetic Algorithm-Optimized Capacitor and Solar PV Integration in Radial Feeder

This research addresses the critical challenge of power loss in distribution systems caused by increasing electricity demand. It focuses on reducing power losses and enhancing voltage profiles in a radial distribution system through the optimal placement of capacitors and solar PV. The project employs comprehensive analysis and optimization techniques, including forward and backward sweep algorithms for load flow analysis and Genetic Algorithm (GA) in MATLAB. The performance of the distribution system is evaluated by considering parameters such as power loss and voltage characteristics. Simulation results on an IEEE 33-bus radial distribution network validate significant improvements after various configurations, including the base case, capacitor case, DG case, and combined DG and capacitor case. In each scenario, active power losses are reduced, reactive power loss diminishes, and voltage profile enhancements are observed. The study further validates these results using ETAP software, ensuring consistency and reliability. Notable improvements are also observed in the Thimi Sallaghari 11KV feeder, showcasing potential practical implementations in real feeders in the future. Different case scenarios are explored for the number of capacitors and DGs, providing insights into the optimal combination for enhanced distribution system performance.

Decoding design characteristics of local flexibility markets for congestion management with a multi-layered taxonomy

Local flexibility markets are becoming increasingly popular smart grid solutions. They connect customers who require flexible electricity supply and demand with local flexibility providers. However, the growing number of diverse solutions has led to a proliferation of concepts, projects, and companies in this market, with this diversity making understanding and comparison difficult. To tackle this challenge, we propose a multi-layered taxonomy of local flexibility market solutions. This focuses on congestion management on the distribution side of this activity; a crucial service for distribution system operators. Our taxonomy utilizes the Smart Grid Architecture Model to describe these markets comprehensively. We employ an iterative taxonomy-building method, refining and evaluating it through insights from ongoing implementations and twenty-eight expert interviews. Moreover, we present a complete instantiation of our taxonomy and offer a discussion with practical recommendations for practitioners in the local flexibility market landscape.

Advanced hardware-in-the-loop testing chain for investigating interactions between smart grid components during transients

Aiming to investigate the possible interactions between smart grid components during transient events, an advanced hardware-in-the-loop testing chain for the validation of novel smart grid solutions is proposed in this paper. The testing chain is directed towards both academic and industrial hardware-in-the-loop users, e.g., relay manufacturers, power electronics manufacturers and DSOs/TSOs. All different hardware-in-the-loop simulation setups, ranging from simple local simulations up to more elaborate, power hardware-in-the-loop simulations, are discussed, forming a solid testing chain. The interactions during transients, which can be investigated at each step, are analytically derived to emphasize the insights that each step can offer to the performed component validation. To highlight the applicability of the proposed hardware-in-the-loop testing chain, when validating smart grid components, a case study concerning the testing of a microgrid transition algorithm, between the interconnected and islanded modes of operation, is considered for a real microgrid. Particularly, the interactions between an advanced grid-forming inverter and the already existing grid-following inverters of the microgrid are investigated during normal and abnormal grid conditions, while following the appropriate steps of the proposed testing chain.

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.

Cybersecurity and Confidentiality in Smart Grid for Enhancing Sustainability and Reliability

Ensuring cybersecurity and confidentiality in smart grids is crucial for enhancing sustainability and reliability in today's technology-driven world. With the increasing reliance on smart grid technologies, it is imperative to address the potential cybersecurity risks and protect the confidentiality of sensitive data. This research focuses on exploring the challenges and strategies associated with cybersecurity and confidentiality in smart grids. It examines the importance of safeguarding smart grid infrastructure from cyber threats to maintain sustainable and reliable energy delivery systems. The study investigates various techniques and technologies, including encryption, authentication, intrusion detection, and secure communication protocols, that can be employed to enhance the cybersecurity and confidentiality of smart grids. By highlighting the significance of a robust cybersecurity framework and the integration of privacy-preserving measures, this research aims to contribute to the development of secure and resilient smart grid systems. The findings and recommendations presented in this work provide valuable insights for policymakers, industry professionals, and researchers involved in the design and implementation of secure smart grid solutions, ultimately leading to the advancement of sustainable and reliable energy infrastructures.

Smart Grid Study As Solution To The Challenges Of Electricity Transmission And Distribution In North Sulawesi

Electricity delivery in North Sulawesi faces many problems, such as inadequate supply, unreliable infrastructure, ineffective power transfer, and inadequate integration of renewable sources. This research is a literature study that provides a logical description in accordance with the study objectives. The results of this study show that Smart Grid Technology is considered a feasible solution to overcome the problem. Smart Grid can revolutionize the power grid in this region by monitoring and controlling superior power transmission by combining contemporary information and communication technology with conventional energy infrastructure. As this research shows, Smart Grid solutions can improve the efficiency and reliability of electric power transmission and distribution in North Sulawesi.

Investigating the Impact of Electric Vehicle Charging on the Electrical Grid and Understanding Smart Grid Solutions that Can Manage the Variability and Uncertainty of Electric Vehicle Charging Demand

Investigating the Impact of Electric Vehicle Charging on the Electrical Grid and Understanding Smart Grid Solutions that Can Manage the Variability and Uncertainty of Electric Vehicle Charging Demand

Power flow control: Solutions for a modern smart grid [Book review

Power flow control: Solutions for a modern smart grid [Book review

Phase Identification in Smart Grids – Case Study

. A widespread problem of the electricity distribution system is determining to which phase a consumer is connected. Generally, utility companies did not record the distribution of the phases over time, which is essential to address the problem of unbalanced voltage distribution networks. In addition, manual phase identification is not feasible due to its high cost. The massive deployment of smart meters allowed periodic readings of energy consumption, voltage, current, etc. Out of this large amount of data, several techniques based on machine learning have emerged, addressing the problem of phase identification automatically while maintaining the existing infrastructure. Hence, phase identification is essential for developing smart-grid solutions. In the present work, we applied an unsupervised machine-learning technique that allows the classification of the time-voltage series recorded by the smart meters of a low-voltage three-phase radial distribution network located in the Balearic Islands (Spain). The results show that there is a correlation between the time series of the feeder voltage and the consumer meters. The proposed method reached a 100% success rate in the case study. In addition, the results obtained open the way to deploy a new grid configuration to minimize the load imbalance.

Retracted] Smart Grid Security Based on Blockchain with Industrial Fault Detection Using Wireless Sensor Network and Deep Learning Techniques

Low‐cost monitoring and automation solutions for smart grids have been made viable by recent advancements in embedded systems and wireless sensor networks (W.S.N.s). A well‐designed smart network of subsystems and metasystems known as a “smart grid” is aimed at enhancing the conventional power grid’s efficiency and guaranteeing dependable energy delivery. A smart grid (S.G.) requires two‐way communication between utility providers and end users in order to accomplish its aims. This research proposes a novel technique in enhancing the smart grid security and industry fault detection using a wireless sensor network with deep learning architectures. The smart grid network security has been enhanced using a blockchain‐based smart grid node routing protocol with IoT module. The industrial analysis has been carried out based on monitoring for fault detection in a network using Q‐learning‐based transfer convolutional network. The experimental analysis has been carried out in terms of bit error rate, end‐end delay, throughput rate, spectral efficiency, accuracy, M.A.P., and RMSE. The proposed technique attained bit error rate of 65%, end‐end delay of 57%, throughput rate of 97%, spectral efficiency of 93%, accuracy of 95%, M.A.P. of 55%, and RMSE of 75%. This proposed paradigm is advantageous for the operation of smart grids for increased security and industrial fault detection across the network because security is the biggest barrier in smart grid implementation.

Power grid surveillance: Topology change detection system using power line communications

This paper proposes an efficient channel impulse response (CIR)-based technique to detect topology changes in the power grid. The features of the proposed approach include the following aspects: (i) it is a software-only solution, not requiring any intervention on the current smart grid architecture; (ii) topology changes can be detected via a simple distributed algorithm that requires only local communications; and, (iii) both memory and computational footprints of the proposed solution are minimal. The above-mentioned features make this contribution notably appealing for the resource-constrained smart grid domain. Furthermore, the paper provides a detailed discussion of the introduced technique, accompanied by an implementation reflecting a realistic use case, and presents an extensive simulation campaign to show the quality and viability of the proposed approach. A unique feature of our solution is that it performs well even when the communication channel is affected by a high noise level. For instance, with noise levels below 100 dBμV (the typical PLC noise power range), the proposed solution showed a ≈100% detection rate.To the best of our knowledge, our solution is the first one proposing a fully CIR-based, distributed, deterministic algorithm for intrusion detection and localization. We believe that the performance and advantages of the proposed technique pave the way for further smart grid applications and solutions.

High-Frequency Ripple Injection Signals for the Effective Utilization of Residential EV Storage in Future Power Grids With Rooftop PV System

The electrification of the transport industry is expected to have a major impact on the operation of future distribution grids which includes overloading of components, voltage unbalance, and power quality issues. This article proposes a novel approach to utilize the ripple injection load control signals for the control of EV charging load, considering a large integration of PV systems in the grid. Currently, ripple injection signals are widely used by distribution network service providers around the world for control of loads such as streetlights and hot water systems. Ripple injection signals or audio frequency injection control (AFIC) signals are the applications of a high-frequency signal superimposed on the 50/60 Hz supply. The proposed control will make use of the existing infrastructure and offers a viable solution where a smart grid solution is not available. AFIC signals can be encoded in binary to carry different information, which can be used to set the maximum allowable charging rate of future charging stations or activate the vehicle-to-grid mode when necessary. This provides a method to control the EV load depending on the stochastic nature of a future grid. A multimode energy management algorithm has been proposed depending on the load consumption of a particular substation. A power flow simulation study has been used to demonstrate the efficacy of the proposed method.

Special Section on Power Electronics-Enabled Smart Power Distribution Grid

Economic and environmental constraints, as well as technological advancements, are reshaping the traditional view of power distribution systems. In a future distribution grid, as the number of inverter- and converter-based devices increases to more than hundreds of thousands, it is rather intuitive that the current state-of-the-art technical solutions and industry practices will no longer be effective. While tremendous progress has been made in advancing smart grid solutions, not much attention has been paid to bridging the gap between two traditionally disjointed research areas—power systems (especially distribution systems) and power electronics—that will ultimately facilitate the vision of 100% penetration of power-electronics-based distributed energy resources coming to fruition. There is a growing interest in the concepts of power electronics-enabled power systems around the world. This Special Section invites a broad spectrum of contributors (e.g., academics, researchers, engineers, consultants, market regulators and system operators, key policymakers) to define and develop the interdisciplinary technical approaches collectively. Although there are many technical challenges associated with making this vision a reality, policy, economic, and workforce issues also play a significant role. This Special Section hence concentrates on discussing various relevant topics associated with how to accommodate extremely high levels of power-electronics-based distributed energy resources to promote economic efficiency; improve social welfare; reduce energy cost; support plug-and-play of distributed renewable energy; and improve the capability, adaptability, scalability, resiliency, safety, security, and usability that our electric power distribution infrastructure can provide. The articles are authored by a diverse group of experts from academics, industry, and national laboratories around the world ( <xref ref-type="fig" rid="fig1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Fig. 1</xref> ). The guest editorial board received 120+ abstract submissions and invited 65 of them for full-paper submissions. After two-round rigorous reviews, 23 papers have been accepted for final publication. It is worth noting that this Special Section places an emphasis on addressing the mutual research interests of academics and industry. Hence, interdisciplinary research and real-world-problem-driven research topics are of particular relevance to this Special Section. The guest editorial board and IEEE PES leadership made tremendous efforts to attract authors from the industry. All the papers have gone through the same review criteria. Approximately 35% of the accepted papers are led or co-led by industry experts.