Power Infrastructure Research Articles

The Assessment of the Influence of Low-Frequency Electromagnetic Fields Originated from the Power Infrastructure on Humans’ Health

The objective of this study is to assess the impact of low-frequency electromagnetic fields (LF EMFs) generated by power infrastructure on the nearby environment. Measurements of electric (E) and magnetic (H) field intensities were conducted around high-voltage power lines, transformer stations and facilities related to them. Numerical simulations were also performed to model the distribution of the field values around real buildings in close proximity to power delivery systems. Given the ongoing scientific debate regarding the effects of EMFs on living organisms, the current analysis was based on the existing standards—particularly ICNIRP 2010 guidelines, which set the maximum allowable E and magnetic induction (B) values at 5 kV/m and 200 μT, respectively. Stricter national regulations were also examined, such as Poland’s 1 kV/m E limit in residential areas and Belgium’s 10 μT limit for B. The results showed that while most cases complied with ICNIRP 2010 standards, certain stricter local regulations were exceeded. Specifically, 9 of 14 cases exceeded Poland’s E limits, and 8 failed to meet Belgium’s B requirements. Only in one place—a warehouse near 110 kV power lines (in a critical case)—the ICNIRP limit B was exceeded. These findings underscore the variability in regulatory standards and highlight the need for localized assessments of EMF exposure.

Building cybersecurity resilience: integrating defense and recovery investment strategies in an expected resilience framework

PurposeTo remain competitive in an unpredictable environment where the complexity and frequency of cybercrime are rapidly increasing, a cyber resiliency strategy is vital for business continuity. However, one of the barriers to improving cyber resilience is that security defense and accident recovery do not combine efficaciously, as embodied by emphasizing cyber security defense strategies, leaving firms ill-prepared to respond to attacks. The present study thus develops an expected resilience framework to assess cyber resilience, analyze cyber security defense and recovery investment strategies and balance security investment allocation strategies.Design/methodology/approachBased on the expected utility theory, this paper presents an expected resilience framework, including an expected investment resilience model and an expected profit resilience model that directly addresses the optimal joint investment decisions between defense and recovery. The effects of linear and nonlinear recovery functions, risk interdependence and cyber insurance on defense and recovery investment are also analyzed.FindingsAccording to the findings, increasing the defense investment coefficient reduces defense and recovery investment while increasing the expected resilience. The nonlinear recovery function requires a smaller defense investment and overall security investment than the linear one, reflecting the former’s advantages in lowering cybersecurity costs. Moreover, risk interdependence has positive externalities for boosting defense and recovery investment, meaning that the expected profit resilience model can reduce free-riding behavior in security investments. Insurance creates moral hazard for firms by lowering defensive investment, yet after purchasing insurance, expanded coverage and cost-effectiveness incentivize firms to increase defense and recovery spending, respectively.Originality/valueThe paper is innovative in its methodology as it offers an expected cyber resilience framework for integrating defense and recovery investment and their effects on security investment allocation, which is crucial for building cybersecurity resilience but receives little attention in cybersecurity economics. It also provides theoretical advances for cyber resilience assessment and optimum investment allocation in other fields, such as cyber-physical systems, power and water infrastructure – moving from a resilience triangle metric to an expected utility theory-based method.

Can the European nuclear power industry compete with the Chinese nuclear power industry?

European commissioner for the Internal Market, Thierry Breton, told Le Journal du Dimanche in January 2022, “Existing nuclear plants alone will need 50 billion euros of investment from now until 2030. And new generation ones will need 500 billion”. This paper considers whether these values are realistic. Further, it asks whether these investments would yield an internationally competitive European nuclear power infrastructure given that the nuclear power industries in the Organization for Economic Cooperation and Development member countries have lost global nuclear market share to Russian and Chinese firms since 1995.The paper investigates whether the European nuclear industry even with massive investment can compete with the Chinese nuclear industries. It concludes that the European (in particular, the French) nuclear power industry will be unlikely to be cost competitive with the Chinese nuclear power industry unless financing and new plant orders are immediately forthcoming. To achieve carbon neutrality, the issue becomes whether European Union countries can afford indigenous nuclear technologies or will need to import nuclear power plants from Asia.

Various Dimensions of Personal and Professional Work Life Balance of Employees in Power Industry in India

In today’s organized sector, work- life balance assumes a critical importance as this facilitates the development of a productive work culture and minimization of tensions between work and other aspects of people lives. There are three key components that are needed to achieve a healthy lifestyle, namely paid work, unpaid work and personal time. Bringing a balance between all these there is the optimum one can accomplish. Power is among the most critical components of infrastructure, crucial for the economic growth and welfare of nations. The existence and development of adequate power infrastructure is essential for sustained growth of the Indian economy. The fundamental principle of India power industry has been to provide universal access to affordable power in a sustainable way. The purpose of this study is to highlight the necessity of adopting work-life balance in a power sector. The paper examines different elements of work-life balance especially with reference to employees working in power sectors.

Ontology-Guided Generation of Mechanized Construction Plan for Power Grid Construction Project

Mechanized construction is being fully implemented in the electric power infrastructure domain to ensure construction safety, enhance project quality, and improve efficiency. Traditional methods of designing mechanized construction plans are often inefficient due to their labor-intensive processes and heavy reliance on human expertise. This study introduces and evaluates an ontology-guided system designed to automate mechanized construction planning for power grid projects. The developed ontology effectively models domain-specific knowledge, enabling the semantic integration of data from various sources. By leveraging SPARQL queries, the ontology-guided system incorporates knowledge reasoning capabilities that facilitate the automated selection of construction equipment and the generation of comprehensive construction plans. A prototype system incorporating an ontology-guided mechanism has been developed, showcasing marked enhancements in efficiency and accuracy over traditional manual methods, as evidenced by case studies and expert evaluations. The research results emphasize the potential of ontology-guided systems in innovating architectural planning, providing an extensible and standardized approach. Expert evaluation indicates that the system achieves 71.38% effectiveness in generating mechanized construction plans.

Exploring the Challenges of Online Learning in Nigerian Higher Education

This study examines the challenges faced by lecturers in Nigerian higher education institutions when adopting and using e-learning platforms. Through virtual interviews conducted with 12 university lecturers across six regions, the research identifies several key obstacles: unreliable internet connectivity, frequent power outages, and limited access to technological resources. Additionally, inadequate training and institutional support are noted as significant barriers. Thematic analysis was employed to analyze the qualitative data, revealing patterns and common themes related to these challenges. The study suggests that improving internet and power infrastructure, along with enhancing training and technical support, are crucial strategies for overcoming these issues. The findings emphasize the need for targeted interventions to create a more supportive environment for e-learning, aiming to improve the educational experience for both lecturers and students.

Design of retrofit flue gas (CO2) scrubber for dependable clean energy at the Duvha Coal Power Plant

The coal-fired power sector is facing unprecedented pressure due to the shift to low-carbon energy sources and the need to prevent climate change. It is imperative to incorporate advanced technologies into conventional coal-fired power plants to enhance their efficiency, flexibility, and environmental sustainability. One advantage of post-combustion CCS methods is that they may be retrofitted into power plants that are already in place. The goal of this work is to design a CO2 flue gas cleaning retrofit system that will meet the most stringent air quality regulations in an operational coal power station in Southern Africa. It will operate and expedite the removal of undesired gas (CO2) in order to attain ideal requirements for air quality in one of Southern Africa's current coal-fired power plants, the Duvha Coal Power Plant. This study is based on chemical absorption, and explores the mechanistic design of the scrubber, which was accomplished through simple computations and Ansys simulations. The approach for developing a wet CO2 scrubber and LSTG system is based on chemical absorption and is integrated with a pilot plant. The results of the parametric study provide a foundation for a comprehensive industrial system design for South Africa's coal-powered industry. The results show that the scrubber's cylinder height and diameter can be used for an LSTG system and are appropriate for CO2 gas flow and capture. The application of the suggested scrubber design and the LTSG's contributions will allow the coal power station to operate with minimal GHG emissions released into the atmosphere. Instead of shutting down coal power facilities, this cleaning system that completely absorbs CO2 emissions can be used to maintain a robust power infrastructure, rather than being phased out. This will boost the power plant's efficiency over its initial operating efficiency and benefit the nation's economy and the power industry.

Energy system models should consider evolving charging profiles

Abstract Globally, sales of battery electric vehicles (BEVs) are surpassing records every year, and their growing charging needs will ultimately reshape power infrastructure planning practices. While studies have analyzed the impact of light-duty BEVs on the electricity sector, they have overlooked the prospective evolution in charging profiles. We developed a framework for analyzing passenger vehicle electrification futures accounting for the evolution in charging infrastructure, BEVs technical features, and socio-demographics. We soft-link a BEV charging profiles generator with an energy system optimization model to analyze a light-duty vehicle (LDV) electrification scenario in the U.S. from 2020-2050. Compared to static charging profiles, common in prior work, evolving profiles lead to substantial differences in projected power plant installed capacity (up to ~300 GW more solar PV) and activity (up to ~460 TWh more solar PV generation). Hence, future studies should consider not only different charging profiles (e.g., day, night, uncontrolled) but also how these evolve over time.

Unravelling the efficiency of CoAl-LDH / g-C3N4 nanosheets: Type-II heterojunction for photocatalytic hydrogen production and dye degradation under solar light irradiation

The generation of hydrogen fuel, and wastewater treatment according to solar-driven catalysis possesses considerable prospective for establishing a carbon-neutral and ecologically sound power infrastructure. Driven by this problem, we suggest in this study, adopting a simple impregnation method, a customized association of CoAl-LDH and graphitic carbon nitride (CN), a visible light active narrow and wide band gap semiconductors. Several characterization approaches were implemented to understand the CoAl-LDH@g-C3N4 (CACN) composites' physiochemical and optical features. The CACN hetero structural forms exhibited significantly improved solar light-induced photocatalytic H2 generation and dye pollutants decomposition in contrast with pristine materials. The most effective catalyst 5 wt% CoAl-LDH@g-C3N4 (5-CACN) generated the highest hydrogen (∼430.7 μmolg−1h−1), which is 11.9-fold H2 production efficiency compared with CN and depicted significant Brilliant black dye removal efficacy via photocatalytic degradation (up to ∼79%). This was primarily ascribed to the development of the Type-II CACN heterojunctions, which promoted the separation of charges and expanded the abundance of surface-active sites while absorbing the visible spectrum of solar light.

A dynamic importance function for accidental scenarios generation by RESTART in the computational risk assessment of cyber-physical infrastructures

The Computational Risk Assessment (CRA) of Cyber-Physical Systems (CPSs) calls for the analysis of accidental scenarios emerging from the complexities and interdependencies typical of CPSs. Generating these scenarios via crude Monte Carlo Simulation (MCS) is impractical due to the high computational demand of simulation codes of CPSs, considering the combinatorial number of possible scenarios. In this paper, we tailor the use of Repetitive Simulation Trials After Reaching Thresholds (RESTART), a rare-event simulation method of literature, to efficiently generate relevant accidental scenarios. The tailored RESTART is guided by a dynamic Importance Function (IF) originally introduced here to dynamically characterize the relevance of the scenarios with reference to the current topology of the CPS and the susceptibility of its components. Two case studies of increasing complexity are considered: a single power grid and a CPS consisting of an Integrated Power and Telecommunication (IP&TLC) infrastructure. Results show that RESTART mines out more relevant scenarios than crude MCS for a number of different IFs based on vulnerability metrics of literature, and thus particularly efficiently when the novel IF is adopted.

Tower and power line segmentation method based on RandLA-Net

Abstract The scale of the power grid of China has gradually expanded, and the number of long-distance and high-level transmission lines has also increased. However, it is very hard to detect the power infrastructure transmission lines because of the complex laying environment and various ground features. Lines and towers in the power system are important components of power transmission, and their safety directly affects the operation of the entire power system. Reasonable management of lines and towers can reduce the occurrence of faults and system safety risks. At present, both manual inspection efficiency and visual inspection processing accuracy are low. An airborne LiDAR point cloud has become a key means for monitoring towers and power lines. In response to the above problems, we propose a tower and power line segmentation algorithm based on RandLA-Net. Experimental results demonstrate that the proposed method gets precise detection of power poles and lines, and enhances the efficiency in identifying hazardous areas along power lines. The highest Mean Intersection over Union (mloU) recorded is 95.34%, establishing a clear correlation between power towers and lines. Power line data holds significant importance for the power sector, facilitating the monitoring and management of transmission lines.

Data Analysis and Algorithm Innovation in Power System IntelligentMonitoring and Early Warning Technology

Data analysis and algorithm innovation play a pivotal role in enhancing power system intelligent monitoring and early warning technology. With the increasing complexity of modern power grids, the integration of advanced data analytics enables real-time monitoring, fault detection, and predictive maintenance. By leveraging machine learning algorithms, anomaly detection techniques, and big data analytics, power systems can efficiently identify potential risks and failures before they escalate into serious issues. These innovations not only improve grid reliability and resilience but also optimize resource utilization. Early warning mechanisms based on intelligent algorithms provide timely alerts, allowing for preventive measures that ensure the stability and safety of the power network. This approach fosters a smarter, more adaptive power infrastructure capable of meeting growing energy demands while minimizing downtime and disruptions.This paper presents a comprehensive investigation into the development and efficacy of an intelligent early warning system for power systems. Leveraging machine learning algorithms, IoT sensors, and cloud computing frameworks, the system aims to enhance real-time monitoring capabilities and facilitate proactive intervention and maintenance. Through a series of simulations and iterations, the study demonstrates significant improvements in performance metrics such as accuracy, precision, recall, and F1 score. The integration of data analytics and classification techniques enables the system to accurately predict and classify anomalies, thereby minimizing risks and ensuring the reliability and efficiency of power systems. Through a series of simulations and iterations, the study demonstrates significant improvements in performance metrics such as accuracy, precision, recall, and F1 score. Specifically, the system achieves an average accuracy of 95%, precision of 92%, recall of 94%, and F1 score of 92% across multiple iterations. The integration of data analytics and classification techniques enables the system to accurately predict and classify anomalies, thereby minimizing risks and ensuring the reliability and efficiency of power systems.

Enhancing safety in narrow-band transformerless PLC couplers with a passive symmetrical filter

As the demand for efficient data transmission over existing power infrastructure grows, power-line communication (PLC) systems have become increasingly vital. However, integrating communication signals with high-voltage power lines poses significant safety challenges, emphasizing the need for reliable, safe, and high-performance components. To address cost and safety concerns, this article introduces a symmetrical third-order band-pass filter design that employs a transformerless coupler, avoiding the expense and bulk of traditional transformers while enhancing both equipment and human safety in narrow-band PLC systems. The design, functionality, and safety considerations are discussed, with a focus on implementing a passive analog Butterworth filter, chosen for its flat frequency response in the passband. Additionally, we address the safety aspects of transformerless couplers in PLC applications, emphasizing their reliability and efficiency in maintaining signal integrity while minimizing the risks associated with high-voltage environments. Simulations validated the proposed design, confirming its effectiveness in achieving the desired frequency response. The design is cost-effective due to the elimination of the transformer and ensures safety through the strategic rearrangement of the coupler components, which isolates the power line from the communication side.

Review of peer-to-peer energy trading: Advances and challenges

The power system is confronting progress due to the high integration of distributed energy resources (DERs). These DERs are expected to cause challenges for power system operations. Therefore, innovative management approaches were proposed for integrating DERs in future power systems and maximizing DER owners’ benefits, such as peer-to-peer (P2P) energy trading. Direct energy trading between users is made possible by P2P energy trading, which supports bulk power infrastructure operations while supporting local power and energy balance. P2P energy trading is a promising approach to expanding the installation of renewable energy sources and achieving the system flexibility required for the shift to low-carbon energy. The grid is anticipated to gain from P2P energy trading by having lower reserve requirements, peak demand, and network losses. Many studies and pilot projects have shown how P2P energy trading benefits prosumers as well as the grid. However, the widespread use of such trading models remains limited in today's electrical markets. This paper reviews recent advances in the P2P energy system and a perceptive discussion of the challenges that are keeping P2P from becoming a viable energy management solution in the present electrical market. First, the energy network is covered in this paper's description of these new P2P markets; next, the types of P2P energy trading, moving on to the market structure. Then, the technologies and technical approaches behind P2P energy trading are covered. After that, P2P energy trading advances in different systems are discussed. Finally, we identify challenges before making some concluding remarks.

“The Devil You Know”: Barriers and Opportunities for Co-Designing Microclimate Sensors, A Case Study of Manoomi

Current environmental challenges have profound local consequences and often benefit from the collection of fine-grained microclimate data. Advances in wireless sensor networks and the Internet of Things have led to technologies nominally suited to support remote sensing; however, in practice long-running deployments of in-field environmental sensors are rare. Field conditions are often remote and culturally sensitive, with limited power, Internet, transportation, and human infrastructure; advances in device technology alone will not suffice. We ask how communities, Internet of Things researchers, government, and other interested parties can work together to co-design useful, low burden, sustainability-focused infrastructure. Toward this end, we conducted 11 semi-structured interviews with 13 experts who use or rely on environmental sensing technology. To complement our interview data, we engaged in three months of participant observation while immersed in organizations specifically working toward manoomin (wild rice) conservation. We make two primary contributions. First, we confirm and enrich a five-stage model, the microclimate sensor lifecycle, focusing on desired features and persistent challenges. Second, we outline a space for co-design of microclimate sensors with emphasis on the cost of experience, the generally unaddressed issue of technical usability in the messy field, and the opportunity for community engagement to improve technical design and outcomes. Furthermore, we discuss future design opportunities, recommendations, and challenges in the microclimate sensor design, deployment, and sustainability space.

Influence of Power Supply Reliability on Academic Performance and Project Completion Rates of Architectural Students at Caleb University, Lagos, Nigeria

This study investigates the influence of power supply reliability on academic performance and project completion rates among architecture students at Caleb University. The research adopts a quantitative approach, using a structured questionnaire to gather data from a representative sample of students across BSc, MSc, and PhD programs. Of the almost 700 population, 255 were sampled and the findings reveal that power interruptions are a frequent and significant issue, with 85% of students experiencing outages at least once a week and 60% reporting outages lasting between 1 to 3 hours. These disruptions have a pronounced negative impact on academic performance, with 78% of respondents indicating that power outages have adversely affected their grades. Furthermore, 82% of students reported delays in project completion due to power interruptions, with a substantial number having to redo portions of their work due to unsaved progress. The study highlights a strong correlation between the frequency of power outages and the decline in academic performance, as well as the delays in project completion. Additionally, the psychological impact of these outages, manifested in increased levels of stress and anxiety among 70% of respondents, further exacerbates the challenges faced by students. The research concludes that reliable power infrastructure is crucial for academic success, particularly in technology-intensive disciplines like architecture. Recommendations include improving power infrastructure, implementing energy management strategies, developing contingency plans, enhancing student support services, and fostering collaboration with power utility providers. By addressing these issues, educational institutions can create a more stable and conducive learning environment, thereby enhancing students' academic outcomes and overall well-being.

Advancing mineral-energy nexus for development (MEND) in Africa: A case study of Chinese lithium mining project in Zimbabwe

Providing sustainable energy solutions for critical mineral investments presents significant challenges, particularly in the context of resource-rich but energy-poor countries in sub-Saharan Africa. We developed an analytical framework to understand the role of the mineral-energy nexus in delivering developmental co-benefits (MEND). We identified four criteria of developmental co-benefits, namely (1) local electrification, (2) climate mitigation (via renewable energy technologies), (3) enhanced ‘last mile’ power infrastructures, and (4) re-distributive revenues for power sector reforms. By applying this framework to a case study of Chinese lithium mining investment in Zimbabwe, we illustrated the innovative potentials of the investors on the ground, the urgent need to nurture collaborative networks and risk-sharing mechanisms for local electrification, and the lack of regulatory and financial support for the investments on mineral-energy nexus.

Price trends in the global electricity market

The relevance of the research topic is determined by the need to adapt to rapid global changes in the electric power industry, which is associated with a change in the structure of the energy balance, the strengthening of geopo­litical factors, the impact of climate change, economic globalization, new regulatory require­ments, and the rapid development of energy storage technologies and smart networks. These changes lead, on the one hand, to challenges in ensuring energy security, and on the other hand, contribute to significant price volatility in the electricity market. As a result of the influence of global price trends and world energy develop­ment priorities on the domestic electricity sector, the study of these trends is of great importance for Ukraine. The aim of the research is to establish the price trends of the global electricity market with the determination of the key factors of price growth in the context of challenges for Ukraine regarding the stabilization of electricity prices. The research is based on the hypothesis that the factors that determine the trajectory of price changes on the international electricity market are also characteristic of the Ukrainian electricity market. The research was conducted using the methods of statistical analysis, syn­thesis, grouping, tabular and graphical display of results. A retrospective analysis of price dyna­mics on the global energy market was carried out, which showed a faster pace of price changes for energy products than for other products, with a faster increase in oil prices than for coal. The current trends in the development of changes in electricity prices were analyzed, the reasons for their rapid growth in 2021 were identified, and it was noted that in some countries, such as the USA and China, prices remained stable. Using the example of the EU countries, it has been analytically proven that electricity tariffs depend on the price structure. The factors that affect pricing in the field of electricity in the world are determined: energy prices, global crisis pheno­mena, the amount of available supply, weather conditions, supply chain problems, grid infra­struc­ture and distribution, the structure of the electricity market, the share occupied by taxes and fees in electricity prices and the purchasing power of the population. The current state of the electricity market of Ukraine is analyzed, which is characterized by a price imbalance, especially in the retail sector, a settlement crisis between the main market participants, a lack of real competition, limited transparency of the market and opportunities for manipulation on it, and the imperfection of the legislative framework. These factors are exacerbated by external negative influences in the form of a full-scale Russian invasion due to the destruction of electric power infrastructure and loss of capacity

Guideline for Developing Glamping Tourism in China: A Case Study of Gansu

Background and Aim: In China, glamping is experiencing rapid growth. With its unique advantages, Gansu Province has created opportunities for the development of glamping tourism. Despite challenges such as inadequate facilities and low service standards, glamping tourism in the province holds immense potential. This study aims to analyze tourism development in Gansu Province and propose recommendations for the advancement of glamping tourism. Materials and Methods: This study employed a quantitative research approach. A questionnaire survey was conducted among 400 glampers aged 18 and above who had visited Gansu Province and stayed at ten glamping sites over the past three years. The survey covered demographic information, travel habits, motivations, and tourist satisfaction. Descriptive statistical analysis, mean, and variance analysis were conducted using SPSS to quantify the relationships between different factors. Results: The research findings indicate that Gansu's unique natural beauty and rich cultural heritage contribute to high levels of tourist satisfaction with the abundance of nature and cultural landscapes. However, significant differences in satisfaction were observed in various aspects of glamping, including the glamping site environment, shower and toilet facilities, power and drainage infrastructure, emergency medical assistance, and security assurance, suggesting the need for further improvement. Additionally, external traffic and internal route planning were identified as significant factors influencing tourist satisfaction. Conclusion: The survey results indicate that glampers have high satisfaction with natural and cultural landscapes. However, there are significant differences in satisfaction regarding the campground environment, sanitation facilities, power and drainage infrastructure, transportation, emergency medical assistance, and safety measures. Analyzing the data, the following development guidelines are derived: enriching experiences, improving facilities, enhancing safety measures, reducing costs, promoting environmental conservation, integrating cultural heritage, fostering cooperation, and establishing feedback mechanisms. These measures aim to facilitate the sustainable development of glamping, attract more visitors, and promote economic prosperity.

A multiscale approach to optimize off-grid hybrid renewable energy systems for sustainable rural electrification: Economic evaluation and design

This article thoroughly investigates the design and optimization of an off-grid hybrid renewable energy system for a remote town in the province of Ankara, whose traditional power infrastructure is lacking. The goal is to provide an efficient and cost-effective energy system that can supply the village's power needs indefinitely. The optimization process entails selecting the best mix of renewable energy sources and sizing components to obtain the best economic and technical performance. To handle the complexity of the optimization problem, the Nelder-Mead simplex search method is used, taking into account the stochastic nature of renewable energy generation and the nonlinear features of RES-based power plants. The simulation results show that the suggested hybrid system outperforms traditional diesel power generators in terms of economic viability and environmental sustainability. The system assures consistent power supply by using reserve energy devices such as batteries, thereby minimizing the intermittent nature of renewable sources. With a competitive energy cost of €0.63/kWh, the optimized hybrid system ensures a dependable and continuous power supply, fulfilling the village's electrical requirement for an amazing 16 years.