Search Results (1,057)

In light of the increasing frequency and intensity of natural phenomena, whether climatic or telluric, the relevance of multi-risk assessment approaches has become an important issue for understanding and estimating the impacts of disasters on complex socioeconomic systems. Two aspects contribute to the worsening of this situation. First, climate change has heightened the incidence and, in conjunction, the seriousness of geohazards that often occur with each other. Second, the complexity of these impacts on societies is drastically exacerbated by the interconnections between urban areas, industrial sites, power or water networks, and vulnerable ecosystems. In front of the recent research on this problem, and the necessity to figure out the best scientific positioning to address it, we propose, through this review analysis, to revisit existing literature on multi-risk assessment methodologies. By this means, we emphasize the new recent research frameworks able to produce determinant advances. Our selection corpus identifies pertinent scientific publications from various sources, including personal bibliographic databases, but also OpenAlex outputs and Web of Science contents. We evaluated these works from different criteria and key findings, using indicators inspired by the PRISMA bibliometric method. Through this comprehensive analysis of recent advances in multi-risk assessment approaches, we highlight main issues that the scientific community should address in the coming years, we identify the different kinds of geohazards concerned, the way to integrate them in a multi-risk approach, and the characteristics of the presented case studies. The results underscore the urgency of developing robust, adaptable methodologies, effectively able to capture the complexities of multi-risk scenarios. This challenge should be at the basis of the keys and solutions contributing to more resilient socioeconomic systems. Full article

The transition towards a power system characterized by a reduced presence of synchronous generators (SGs) and an increased reliance on inverter-based resources (IBRs), including wind, solar photovoltaics (PV), and battery storage, presents new operational challenges, particularly when these sources exceed 50–60% of the system’s demand. While current grid-following (GFL) IBRs, which are equipped with fast and rigid control systems, continue to dominate the inverter landscape, there has been a notable surge in research focused on grid-forming (GFM) inverters in recent years. This study conducts a comparative analysis of the practicality and control methodologies of GFM inverters relative to traditional GFL inverters from a system planning perspective. A comprehensive framework aimed at assisting system developers and consulting engineers in the grid-integration of wide-scale renewable energy sources (RESs), incorporating strategies for the deployment of inverters, capacitor banks, and harmonic filters, is proposed in this paper. The discussion includes an examination of the reactive power capabilities of the plant’s inverters and the provision of additional reactive power to ensure compliance with grid interconnection standards. Furthermore, the paper outlines a practical approach to assess the necessity for enhanced filtering measures to mitigate potential resonant conditions and achieve harmonic compliance at the installation site. The objective of this work is to offer useful guidelines and insights for the effective addition of RES into contemporary power systems. Full article

The evolution of electrical power systems into smart grids has brought about significant advancements in electricity generation, transmission, and utilization. These cutting-edge grids have shown potential as an effective way to maximize energy efficiency, manage resources effectively, and enhance overall reliability and sustainability. However, with the integration of complex technologies and interconnected systems inherent to smart grids comes a new set of safety and security challenges that must be addressed. First, this paper provides an in-depth review of the key considerations surrounding safety and security in smart grid environments, identifying potential risks, vulnerabilities, and challenges associated with deploying smart grid infrastructure within the context of the Internet of Things (IoT). In response, we explore both cryptographic and non-cryptographic countermeasures, emphasizing the need for adaptive, lightweight, and proactive security mechanisms. As a key contribution, we introduce a layered classification framework that maps smart grid attacks to affected components and defense types, providing a clearer structure for analyzing the impact of threats and responses. In addition, we identify current gaps in the literature, particularly in real-time anomaly detection, interoperability, and post-quantum cryptographic protocols, thus offering forward-looking recommendations to guide future research. Finally, we present the Multi-Layer Threat-Defense Alignment Framework, a unique addition that provides a methodical and strategic approach to cybersecurity planning by aligning smart grid threats and defenses across architectural layers. Full article

With increasing electrification and the connection of more renewable resources at the transmission level, bulk interconnected electric grids need to plan network expansion with new transmission facilities. The transmission expansion planning (TEP) problem is particularly challenging because of the combinatorial, integer optimization nature of the problem and the complexity of engineering analysis for any one possible solution. Network synthesis methods, that is, heuristic-based techniques for building synthetic electric grid models based on complex network properties, have been developed in recent years and have the capability of balancing multiple aspects of power system design while efficiently considering large numbers of candidate lines to add. This paper presents a methodology toward scalability in addressing the large-scale TEP problem by applying network synthesis methods. The algorithm works using a novel heuristic method, inspired by simulated annealing, which alternates probabilistic removal and targeted addition, balancing the fixed cost of transmission investment with objectives of resilience via power flow contingency robustness. The methodology is demonstrated in a test case that expands a 2000-bus interconnected synthetic test case on the footprint of Texas with new transmission to support 2025-level load and generation. Full article

Visible light communication (VLC) is an emerging communication technology that integrates lighting and communication, offering significant advantages in terms of data transmission rates and broad application prospects. With advancements in semiconductor technology, micro-light-emitting diodes (micro-LEDs) have emerged as one of the most promising light sources for high-speed VLC systems, owing to their high brightness, low power consumption, and high modulation bandwidth. Recent developments have also seen substantial progress in high-bandwidth GaN-based visible light detectors, which complement the transmission capabilities of micro-LEDs. This paper reviews the latest advancements in micro-LEDs as high-speed transmitters for VLC, detailing their capabilities in terms of bandwidth, data rates, modulation techniques, and diverse applications, including structured lighting systems that combine positioning, communication, and illumination. Additionally, the advantages of using micro-LEDs in GaN-based photodetectors (PDs) are discussed, highlighting their potential in enhancing bandwidth and data rates and facilitating high-speed communications across multifunctional applications. Therefore, this review will benefit the further development of micro-LEDs and their application in 6G communication and global interconnect. Full article

In today’s increasingly interconnected digital world, cyber threats have grown in frequency and sophistication, making intrusion detection systems a critical component of modern cybersecurity frameworks. Traditional IDS methods, often based on static signatures and rule-based systems, are no longer sufficient to detect and respond to complex and evolving attacks. To address these challenges, Artificial Intelligence and machine learning have emerged as powerful tools for enhancing the accuracy, adaptability, and automation of IDS solutions. This study presents a novel, hybrid ensemble learning-based intrusion detection framework that integrates deep learning and traditional ML algorithms with explainable artificial intelligence for real-time cybersecurity applications. The proposed model combines an Artificial Neural Network and Support Vector Machine as base classifiers and employs a Random Forest as a meta-classifier to fuse predictions, improving detection performance. Recursive Feature Elimination is utilized for optimal feature selection, while SHapley Additive exPlanations (SHAP) provide both global and local interpretability of the model’s decisions. The framework is deployed using a Flask-based web interface in the Amazon Elastic Compute Cloud environment, capturing live network traffic and offering sub-second inference with visual alerts. Experimental evaluations using the NSL-KDD dataset demonstrate that the ensemble model outperforms individual classifiers, achieving a high accuracy of 99.40%, along with excellent precision, recall, and F1-score metrics. This research not only enhances detection capabilities but also bridges the trust gap in AI-powered security systems through transparency. The solution shows strong potential for application in critical domains such as finance, healthcare, industrial IoT, and government networks, where real-time and interpretable threat detection is vital. Full article

This study presents a novel spatio-temporal detection framework for identifying False Data Injection (FDI) attacks in DC microgrid systems from the perspective of cyber–physical symmetry. While modern DC microgrids benefit from increasingly sophisticated cyber–physical symmetry network integration, this interconnected architecture simultaneously introduces significant cybersecurity vulnerabilities. Notably, FDI attacks can effectively bypass conventional Chi-square detector-based protection mechanisms through malicious manipulation of communication layer data. To address this critical security challenge, we propose a hybrid deep learning framework that synergistically combines: Convolutional Neural Networks (CNN) for robust spatial feature extraction from power system measurements; Long Short-Term Memory (LSTM) networks for capturing complex temporal dependencies; and an attention mechanism that dynamically weights the most discriminative features. The framework operates through a hierarchical feature extraction process: First-level spatial analysis identifies local measurement patterns; second-level temporal analysis detects sequential anomalies; attention-based feature refinement focuses on the most attack-relevant signatures. Comprehensive simulation studies demonstrate the superior performance of our CNN-LSTM-Attention framework compared to conventional detection approaches (CNN-SVM and MLP), with significant improvements across all key metrics. Namely, the accuracy, precision, F1-score, and recall could be improved by at least 7.17%, 6.59%, 2.72% and 6.55%. Full article

The West Africa Power Pool (WAPP) Interconnected Transmission System (WAPPITS) has faced challenges with frequency control due to limited primary frequency control reserves (PFRs). Battery Energy Storage Systems (BESSs) have been identified as a possible solution to address frequency control challenges and to support growing levels of variable renewable energy in the WAPPITS. This paper uses a dynamic PSS/E grid simulation to evaluate the effectiveness of BESSs and conventional power plants for the maximum N-1 contingency scenario in WAPPITS—the loss of 400 MW of generation. BESSs outperform conventional power plants in fast frequency response; a BESS-only PFR mix produces the best technical performance for the metrics analyzed. However, this approach does not have the best marginal cost; a balanced mix of BESSs and conventional reserves achieves adequate performance on all metrics to meet grid requirements. This hybrid approach combines BESSs’ rapid power injection with the lower cost of conventional units, resulting in improved nadir frequencies (e.g., 49.70–49.76 Hz), faster settling times (1.00–2.20 s), and cost efficiency. The study indicates that an optimal approach to frequency control should include a combination of regulatory reforms and coordinated reserve procurement that includes BESS assets. Regulatory reforms should require or incentivize conventional plant to provide PFRs, possibly through creation of a (new to WAPPITS) market for ancillary services. While not a comprehensive analysis of all variables, these findings provide critical insights for policymakers and system operators. Full article

Driven by the environmental benefits associated with reduced greenhouse gas emissions, oil companies have intensified research efforts into reassessing the strategies used to meet the electrical demands of offshore production platforms. Among the various alternatives available, the deployment of onshore–offshore interconnections via High-Voltage Direct Current (HVDC) transmission systems has emerged as a promising solution, offering both economic and operational advantages. In addition to reliably meeting the electrical demand of offshore facilities, this approach enables enhanced operational flexibility due to the advanced control and regulation capabilities inherent to HVDC converter stations. Based on the use of interconnection through an HVDC link, aiming to evaluate the operation of the electrical system as a whole, this study focuses on evaluating dynamic events using the PSCAD software version 5.0.2 to analyze the direct online starting of a large induction motor and the sudden loss of a local synchronous generating unit. The simulation results are then analyzed to assess the effectiveness of both Grid-Following (GFL) and Grid-Forming (GFM) control strategies for the converters, while the synchronous generators are evaluated under both voltage regulation and constant power factor control operation, with a particular focus on system stability and restoration of normal operating conditions in the sequence of events. Full article

As many renewable energy sources have been waiting to be interconnected with distribution systems due to the lack of power system infrastructure in Korea, studies to solve the delayed problem for renewable energy sources required. In order to overcome these problems, this paper presents an introduction model and optimal capacity algorithm of a VPL (virtual power line) device, which is a virtual power line operation technology to manage the power system by operating an ESS installed at the coupling point of renewable energy source without additionally expanding the power system infrastructure in a conventional way; this paper also proposes an economic evaluation method to assess the feasibility of the VPL device. The optimal capacity of the VPL device is determined by solving the over-voltage problem for the customer, and the economic evaluation method for the VPL device is considered by cost and benefit elements to evaluate the feasibility of introduction model for VPL device. From the simulation result of the proposed optimal capacity algorithm and economic evaluation method based on the introduction model in the VPL device, and it was confirmed that the optimal kW capacity of VPL device was selected as the maximum value in power control values, and the optimal kWh capacity was also determined by accumulating the power control values over the time intervals; also, the proper capacity of the VPL can be more economical than the investment cost of power system infrastructure expansion in the conventional method. Full article

The combined application of Load Frequency Control (LFC) and Automatic Voltage Regulation (AVR), known as Automatic Generation Control (AGC), manages active and reactive power to ensure system stability. This study presents a novel hybrid controller with a (1+PDD²)-(1+TI) structure, optimized using the Mirage Search Optimization (MSO) algorithm. Designed for dual-area power systems, the controller enhances both LFC and AVR by coordinating voltage and frequency loops. MSO was chosen after outperforming five algorithms (ChOA, DOA, PSO, GTO, and GBO), achieving the lowest fitness value (ITSE = 0.028). The controller was tested under various challenging conditions: sudden load disturbances, stochastic variations, nonlinearities like Generation Rate Constraints (GRC) and Governor Dead Band (GDB), time-varying reference voltages, and ±20% to ±40% parameter deviations. Across all scenarios, the (1+PDD²)-(1+TI) controller consistently outperformed MSO-tuned TID, FOPID, FOPI-PIDD², (1+PD)-PID, and conventional PID controllers. It demonstrated superior performance in regulating frequency, tie-line power, and voltage, achieving approximately a 50% improvement in dynamic response. MATLAB/SIMULINK results confirm its effectiveness in enhancing overall system stability. Full article

Background: Chronic pain affects one in five youth globally and is frequently accompanied by mental health challenges that extend into adulthood. Caregivers play a vital role in supporting youth with chronic pain, yet their own mental and physical health needs are often overlooked. While caregiver well-being is linked to child outcomes, few interventions directly address caregivers’ health, especially among those facing systemic barriers. This study explored the lived experiences of caregivers to better understand their unmet needs and inform the co-design of a supportive digital health solution. Methods: We conducted a qualitative exploratory study involving 32 caregivers of youth with chronic pain across Canada and Australia. Semi-structured interviews were co-facilitated by caregiver partners. Thematic analysis was applied to interview data. Results: Two overarching themes were identified: (1) bearing the weight and sacrifice of caregiving and (2) deep interrelatedness and blurred boundaries. Caregivers reported profound emotional, physical, and financial burdens; strained relationships; and social isolation. Many struggled with self-neglect, prioritizing their child’s needs over their own. Fathers’ evolving caregiving roles challenged traditional gender norms, though mothers continued to bear a disproportionate load. Despite challenges, caregivers demonstrated resilience and recognized their well-being as interconnected with their child’s health. Conclusions: Findings underscore the need for systemic investment in caregiver well-being. Digital health solutions, including virtual peer networks, mental health resources, and tailored education, offer scalable, accessible pathways for support. These insights will inform the development of Power over Pain for Primary Caregivers, a digital solution and knowledge hub aimed at improving caregiver well-being and family outcomes, aligning with global efforts to enhance family-centred pediatric pain care. Full article

In the current configuration of Brazil’s hydro-thermal-wind power system, hydroelectric reservoirs have progressively lost their long-term regulatory role due to inadequate planning, inefficient energy use, and reduced inflows. In the context of the energy transition and the incorporation of low-emission technologies into the generation mix, this study proposes expanding nuclear baseload capacity as a “regulatory thermal buffer” to mitigate hydrological uncertainty and strengthen grid stability. Using the São Francisco River basin as a case study, an equivalence factor is developed to relate nuclear energy output to stored hydropower reservoir volume. Results show that nuclear generation can help restore the multi-annual regulatory capacity of Brazil’s hydropower system and enhance the resilience of the National Interconnected System by contributing substantial inertia to an increasingly variable, renewable-based grid. Full article

With the increasing load and renewable energy capacity in interconnected power grids, the system voltage stability faces significant challenges. Tie-line transmission power is a critical factor influencing the voltage stability margin. To address this, this paper proposes a fully data-driven global sensitivity calculation method for the tie-line power-voltage stability margin, aiming to quantify the impact of tie-line power on the voltage stability margin. The method first constructs an online estimation model of the voltage stability margin based on system measurement data under ambient excitation. To adapt to changes in system operating conditions, an online updating strategy for the parameters of the margin estimation model is further proposed, drawing on incremental learning principles. Subsequently, considering the source–load uncertainty of the system, a global sensitivity calculation method based on analysis of variance (ANOVA) is proposed, utilizing online acquired voltage stability margin and tie-line power data, to accurately quantify the impact of tie-lines on the voltage stability margin. The accuracy of the proposed method is verified through the Nordic test system and the China Electric Power Research Institute (CEPRI) standard test case; the results show that the error of the proposed method is less than 0.3%, and the computation time is within 1 s. Full article

This study analyzed the frequency control challenges within the West Africa Power Pool Interconnected Transmission System (WAPPITS) as it plans to incorporate variable renewable energy (VRE) resources, such as wind and solar energy. Concerns center on the ability of WAPPITS primary frequency control reserves to adapt to high VRE penetration given the synchronization and frequency control problems experienced by the three separate synchronous blocks of WAPPITS. Optimizing solutions requires a better understanding of WAPPITS’ current frequency control approach. This study used questionnaires to understand operators’ practical experience with frequency control and compared these observations to field tests at power plants and frequency response metrics during system events. Eight (8) of ten (10) Transmission System Operators (TSOs) indicated that primary frequency control service was implemented in the TSO, but nine (9) of ten TSOs indicated that the reserves provided were inadequate to meet system needs. Five (5) of ten (10) respondents answered “yes” to the provision of secondary frequency control service, while only one (1) indicated that secondary reserves were adequate. Three (3) TSOs indicated they have AGC (Automatic Generation Control) installed in the control room, but none have implemented it for secondary frequency control. The results indicate a significant deficiency in primary control reserves, resulting in a reliance on under-frequency load shedding for primary frequency control. Additionally, the absence of an AGC system for secondary frequency regulation required manual intervention to restore frequency after events. To ensure the effectiveness of battery energy storage systems (BESSs) and the reliable operation of the WAPPITS with a higher penetration of inverter-based VRE, this paper recommends (a) implementing and enforcing basic primary frequency control structures through regional regulation and (b) establishing an ancillary services market to mobilize secondary frequency control resources. Full article