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This paper presents a comprehensive bibliometric review and visualization of smart and sustainable energy consumption, delving into the challenges and opportunities of developing renewable and non-renewable energy sources. The study examines research trends and emerging themes about integrating smart solutions and sustainable energy resource consumption. The analytical methods used involve thoroughly analyzing empirical data, case studies, and review papers to map the research landscape. The results highlight dominant research topics, influential authors, and publication timelines in this field. The review identifies the key challenges in harnessing renewable and non-renewable energy sources, including the need for reliable energy sources, energy storage systems, and smart grid technologies. The paper concludes with insights into the most effective practices for promoting smart and energy-efficient methods while emphasizing the complexity of sustainable energy solutions. [ABSTRACT FROM AUTHOR]

Bitcoin is a complex phenomenon, whether in terms of the macro factors affecting its price or its role in the global energy infrastructure. However, extant literature pays too little attention to exploring the internal mechanisms of the protocol to be able to link them to how they affect the visible characteristics of Bitcoin. This paper uses secondary data from highly reputable Bitcoin-focused sources to systematically map the processes that enable Bitcoin to function as a peer-to-peer cash system. Novelty is achieved by applying the established and versatile "4I" organisational learning framework to provide a new lens through which to understand how the processes within Bitcoin enable and facilitate different types of changes to the protocol. Further insights are provided to organisational learning from Bitcoin, in relation to managing mission-critical changes to organisational systems. In addition, it presents an option for dealing with irreconcilable internal differences to "hard-fork" part of the organisation. While the scope of this paper is limited to secondary data, opportunities for further research, including primary data collection, are outlined to explore how Bitcoin knowledge disseminates within communities or companies. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive analysis of optimal energy community design, leveraging time-of-use pricing mechanisms and techno-economic parameters. Focusing on a case study of Valongo, Portugal, this study explores the intricate interplay between energy infrastructure planning, economic considerations, and pricing dynamics. Through a systematic approach, various factors, such as renewable energy integration, demand–response strategies, and investment costs, are evaluated to formulate an efficient and sustainable energy community model. Time-of-use pricing schemes are incorporated to reflect the dynamic nature of energy markets and consumer behavior. By integrating techno-economic analyses, this study aims to optimize energy resource allocation while ensuring cost-effectiveness and environmental sustainability. The influence of optimized sizes of photovoltaics (PV), battery storage, and electrical vehicles (EVs) on self-sufficiency rates, self-consumption rates and CO2 savings is analyzed. The findings offer valuable insights into the design and implementation of energy communities in urban settings, highlighting the importance of adaptive strategies in the transition towards a resilient and low-carbon energy future. The novelty of this paper lies in its comprehensive approach to energy community design, which integrates time-of-use pricing mechanisms with techno-economic parameters. By focusing on the specific case of Valongo, Portugal, it addresses the unique challenges and opportunities present in urban settings. Additionally, the analysis considers the interaction between renewable energy production, demand profiles and investment costs, providing valuable insights for optimizing resource allocation and achieving both cost-effectiveness and environmental sustainability. [ABSTRACT FROM AUTHOR]

This paper presents a time-dependent reliability analysis created for a critical energy infrastructure use case, which consists of an interconnected urban power grid and a communication network. By utilizing expert knowledge from the energy and communication sectors and integrating the renewal theory of multi-component systems, a representative reliability model of this interconnected energy infrastructure, based on real network located in the Czech Republic, is established. This model assumes reparable and non-reparable components and captures the topology of the interconnected infrastructure and reliability characteristics of both the power grid and the communication network. Moreover, a time-dependent reliability assessment of the interconnected system is provided. One of the significant outputs of this research is the identification of the critical components of the interconnected network and their interdependencies by the directed acyclic graph. Numerical results indicate that the original design has an unacceptable large unavailability. Thus, to improve the reliability of the interconnected system, a slightly modified design, in which only a limited number of components in the system are modified to keep the additional costs of the improved design limited, is proposed. Consequently, numerical results indicate reducing the unavailability of the improved interconnected system in comparison with the initial reliability design. The proposed unavailability exploration strategy is general and can bring a valuable reliability improvement in the power and communication sectors. [ABSTRACT FROM AUTHOR]

Much of the attention on bitcoin relates to its ability to store value over time or whether you will one day by able to buy a cup of coffee with it. Much less attention is given to bitcoin's potential role as a unit of account. This opinion piece proposes that bitcoin has potential to provide a consistent unit of account for organisations to adopt, but also to assist them in making and measuring meaningful business developments. The paper draws from the business improvement philosophy of Theory of Constraints to propose that unit of account, particularly within high inflation environments, is critical to consider. An illustrative case of a well-known publicly traded company, Microstrategy, provides an example and logic for a company choosing to integrate bitcoin into a business. The paper also gives attention to how the adoption of bitcoin can promote the development of renewable energy infrastructure and provide staff with opportunities for personal development to support their well-being. Opportunities for further research are identified to explore the integration of bitcoin within a business as well as with Theory of Constraints. [ABSTRACT FROM AUTHOR]

Pre-disaster protection strategies are essential for enhancing the resilience of electric power systems against natural disasters. Considering the budgets for protection strategies, the dependency of other infrastructure systems on electricity, and the uncertainty of disaster scenarios, this paper develops risk-neutral and risk management models of strategies for pre-disaster protection. The risk-neutral model is a stochastic model designed to maximize the expected value of resilience (EVR) of the integrated system. The risk management model is a multi-objective model prioritizing the minimization of risk metrics as a secondary goal alongside maximizing the EVR. A case study conducted on the energy infrastructure systems in the Greater Toronto Area (GTA) validates the effectiveness of the models. The findings reveal the following: (i) increasing the budget enhances the EVR of the integrated system; however, beyond a certain budget threshold, the incremental benefits to the EVR significantly diminish; (ii) reducing the value of the downside risk often results in an increase in the EVR, with the variation in Pareto-optimal solutions between the two objectives being non-linear; and (iii) whether for the risk-neutral or risk management protection strategies, there are reasonable budgets when considering disaster intensity and the cost of protection measures. The models can help decision-makers to select effective protection measures for natural disasters. [ABSTRACT FROM AUTHOR]

Energy security is a crucial issue for political, environmental, and economic reasons. This article presents a modern approach to securing critical infrastructure in energy transmission networks, which are managed by advanced IT systems. This paper focuses on the integration of cryptographic mechanisms with biometric data, providing an additional layer of protection against cyber threats. The discussed solutions enable the protection of management systems in energy transmission networks, enhancing their resilience to cyberattacks. The use of the command-line interface (CLI) in combination with biometrics allows for precise execution of security tasks such as network monitoring, firewall management, and automation of security tasks. This makes these systems more reliable and secure, which is essential for the stability of energy systems. [ABSTRACT FROM AUTHOR]

This paper presents a thorough review of our state-of-the-art technique for enhancing dynamic grid partitioning and scheduling in multi-energy source systems. We use a hybrid approach to T-spherical fuzzy sets, combining the alternative ranking order method accounting for the two-step normalization (AROMAN) method for alternating ranking order to enable two-step normalisation with the method based on removal effects of criteria (MEREC) for eliminating criteria effects. This enables us to obtain the highest level of accuracy from our findings. To ascertain the relative importance of these criteria, we use MEREC to perform a rigorous examination of the influence that each evaluation criterion has on the outcomes of the decision-making process. In addition, we use AROMAN to provide a strong foundation for assessing potential solutions by accounting for spherical fuzzy sets to account for any ambiguity. We illustrate how our approach successfully considers several factors, such as social acceptability, technical feasibility, environmental sustainability, and economic feasibility, through the analysis of an extensive case study. Our approach provides decision-makers (DMs) with a rigorous and rational framework for assessing and choosing the best grid division and scheduling options. This is done in an effort to support the administration and design of resilient and sustainable multi-energy systems. This research contributes to the growing body of knowledge in this area by offering insights that help to direct policy, planning, and investment decisions in the shift towards more sustainable energy infrastructures. Moreover, it adds to the growing body of information on multi-criteria decision-making (MCDM) in energy system optimization. [ABSTRACT FROM AUTHOR]

Topics of interest for publication included, but were not limited to, advanced simulation and modeling methods for complex energy problems, soft computing and artificial intelligence in energy systems, machine learning, multi-energy systems, co-simulation, distributed energy resources, and energy demand prediction. The second paper, "A statistical assessment of blending hydrogen into gas networks" [[6]], provides a tool for the statistical assessment of deploying hydrogen in existing gas networks. The need for a "smarter" energy grid infrastructure, with the large-scale integration of renewables and a better demand-response mechanism, is leading to an ever-increasing complexity of next-generation energy networks [[1]]. [Extracted from the article]

Although the severity of the COVID-19 pandemic has appears to have subsided in most parts of the world, nevertheless, in addition to six million deaths, it has yielded unprecedented challenges in the economy, energy, education, urban services, and healthcare sectors. Meanwhile, based on some reports, smart solutions and technologies have had significant success in achieving pandemic-resilient cities. This paper reviews smart city initiatives and contributions to the prevention and treatment of coronavirus disease, as well as reducing its destructive impact, leading towards pandemic-resilient economic and health systems. Furthermore, the situational awareness contributions are reviewed in pandemic-resilient governance. The main contribution of this study is to describe the construction of social capital in smart cities as a facilitator in creating a pandemic-resilient society in crisis through two analyses. Moreover, this research describes smart cities' energy as interconnection of energy hubs (EHs) that leads to a high level of resiliency in dealing with the main challenges of the electricity industry during the pandemic. Energy-hub-based smart cities can contribute to designing pandemic-resilient energy infrastructure, which can significantly affect resilience in economic and health infrastructure. In brief, this paper describes a smart city as a pandemic-resilient city in the economic, energy, and health infrastructural, social, and governmental areas. [ABSTRACT FROM AUTHOR]

The development of offshore wind farms requires robust bonding solutions that can withstand harsh marine conditions for the easy integration of secondary structures. This paper investigates the durability performance of two adhesives: Sikadur 30 epoxy resin and Loctite UK 1351 B25 urethane-based adhesive for use in offshore wind environments. Tensile tests on adhesive samples and accelerated aging tests were carried out under a variety of temperatures and environmental conditions, including both dry and wet conditions. The long-term effects of aging on adhesive integrity are investigated by simulating the operational life of offshore installations. The evolution of mechanical properties, studied under accelerated aging conditions, provides an important indication of the longevity of structures under normal conditions. The results show significant differences in performance between the two adhesives, highlighting their suitability for specific operating parameters. It should also be noted that for both adhesives, their exposure to different environments (seawater, distilled water, humid climate) over a prolonged period showed that (i) Loctite adhesive has a slightly faster initial uptake than Sikadur adhesive, but the latter reaches an asymptotic plateau with a lower maximum absorption rate than Loctite adhesive; and (ii) a progressive deterioration in the tensile properties occurred following an exponential function. Therefore, aging behavior results showed a clear correlation with the Arrhenius law, providing a predictive tool for the aging process and the aging process of the two adhesives followed Arrhenius kinetics. Ultimately, the knowledge gained from this study is intended to inform best practice in the use of adhesives, thereby improving the reliability and sustainability of the offshore renewable energy infrastructure. [ABSTRACT FROM AUTHOR]

Energy storage systems are essential in modern energy infrastructure, addressing efficiency, power quality, and reliability challenges in DC/AC power systems. Recognized for their indispensable role in ensuring grid stability and seamless integration with renewable energy sources. These storage systems prove crucial for aircraft, shipboard systems, and electric vehicles, addressing peak load demands economically while enhancing overall system reliability and efficiency. Recent advancements and research have focused on high-power storage technologies, including supercapacitors, superconducting magnetic energy storage, and flywheels, characterized by high-power density and rapid response, ideally suited for applications requiring rapid charging and discharging. Hybrid energy storage systems and multiple energy storage devices represent enhanced flexibility and resilience, making them increasingly attractive for diverse applications, including critical loads. This paper provides a comprehensive overview of recent technological advancements in high-power storage devices, including lithium-ion batteries, recognized for their high energy density. In addition, a summary of hybrid energy storage system applications in microgrids and scenarios involving critical and pulse loads is provided. The research further discusses power, energy, cost, life, and performance technologies. [ABSTRACT FROM AUTHOR]

Over the years, a rapid evolution of smart grids has been witnessed across the world due to their intelligent operations and control, smart characteristics, and benefits, which can overcome several difficulties of traditional electric grids. However, due to multifaceted technological advancements, the development of smart grids is evolving day by day. Thus, smart grid researchers need to understand and adapt to new concepts and research trends. Understanding these new trends in smart grids is essential for several reasons, as the energy sector undergoes a major transformation towards becoming energy efficient and resilient. Moreover, it is imperative to realize the complete potential of modernizing the energy infrastructure. In this regard, this paper presents a comprehensive bibliometric analysis of smart grid concepts and research trends. In the initial search, the bibliometric data extracted from the Scopus and Web of Science databases totaled 11,600 and 2846 records, respectively. After thorough scrutiny, 2529 unique records were considered for the bibliometric analysis. Bibliometric analysis is a systematic method used to analyze and evaluate the scholarly literature on a particular topic and provides valuable insights to researchers. The proposed analysis provides key information on emerging research areas, high-impact sources, authors and their collaboration, affiliations, annual production of various countries and their collaboration in smart grids, and topic-wise title count. The information extracted from this bibliometric analysis will help researchers and other stakeholders to thoroughly understand the above-mentioned aspects related to smart grids. This analysis was carried out on smart grid literature by using the bibliometric package in R. [ABSTRACT FROM AUTHOR]

Poland is actively exploring the application of nuclear power as a substitute for its present reliance on fossil fuels for the generation of heat and electricity. This change reflects a calculated attempt to reduce carbon emissions, diversify the nation's energy sources, and enhance the sustainability of its energy infrastructure. However, the implementation of nuclear technology faces many challenges, such as radiation exposure, the production of radioactive waste, the off-site effects of nuclear accidents, and high capital costs. Addressing such nuclear-safety-related issues is crucial for nuclear technology's successful deployment. An extended analysis of the "coal-to-nuclear" process in terms of its safety has to be performed. Therefore, this review paper covers multidisciplinary studies related to the rollout of nuclear energy in Poland. The first stage of this study was the identification of the key areas of analysis, which included (i) formal requirements and recommendations imposed by international and national organizations on the process of designing and operating nuclear power systems; (ii) potential nuclear hazards for the personnel working at a nuclear reactor unit and the local population; (iii) the applied solutions of the security systems of a reactor itself, the steam turbine cycle, and the auxiliary infrastructure; and (iv) the management of spent nuclear fuel and radioactive waste. This methodology, developed based on a review of the literature and international standards, was tested for the selected country—Poland. [ABSTRACT FROM AUTHOR]

Energy communities are key actors in the energy transition since they optimally interconnect renewable energy capacities with the consumers. Despite versatile objectives, they usually aim at improving the self-consumption of renewable electricity within low-voltage grids to maximize revenues. In addition, energy communities are an excellent opportunity to supply renewable electricity to regional and national energy systems. However, effective price signals have to be designed to coordinate the needs of the energy infrastructure with the interests of these local stakeholders. The aim of this paper is to demonstrate the integration of energy communities at the national level with a bottom–up approach. District energy systems with a building scale resolution are modeled in a mixed-integer linear programming problem. The Dantzig–Wolfe decomposition is applied to reduce the computational time. The methodology lies within the framework of a renewable energy hub, characterized by a high share of photovoltaic capacities. Both investments into equipment and its operation are considered. The model is applied on a set of five typical districts and weather locations representative of the Swiss building stock. The extrapolation to the national scale reveals a heterogeneous photovoltaic potential throughout the country. Present electricity tariffs promote a maximal investment into photovoltaic panels in every region, reaching an installed capacity of 67.2 GW and generating 80 TWh per year. Placed in perspective with the optimal PV capacity forecast at 15.4 GW   p e a k at the national level, coordinated investment between local and national actors is needed to prevent dispensable expenses. An uncoordinated design is expected to increase the total costs for residential energy systems from 12% to 83% and curtails 48% of local renewable electricity. [ABSTRACT FROM AUTHOR]

Offshore wind energy is becoming an increasingly important element in the decarbonisation of energy systems. This study aims to estimate the technical potential for offshore wind energy in the Polish exclusive economic zone (EZZ) of the Baltic Sea. Such estimates are necessary to plan the expansion of energy infrastructure. This paper proposes a multi-criteria analysis for the estimation of offshore wind potential and site selection using QGIS software (QGIS Desktop 3.28.6). The criteria include wind velocity, water depth, distance from nature conservation areas, distance from submarine cables and gas pipelines, distance from shipping routes, distance from fishing areas, distance from shipwrecks, and distance from the coastline. The best sites are identified through the Analytic Hierarchy Process (AHP). The results show that the total suitable marine area of 16,218.67 square kilometres can be divided into three parts, in which the highly suitable area for offshore wind farms accounts for 17.55%, the moderately suitable area accounts for 48.56%, and the marginally suitable area accounts for 10.26%. Two different wind turbine placement configurations are being considered, in which wind turbines with a nominal capacity of 15 MW are laid out: 2.5 km and 2 km apart from each other. The corresponding overall electrical capacities only in highly suitable areas equal ca. 9 GW and 15 GW, respectively. If this area is extended to also include the moderately suitable parts, these values increase to ca. 31 GW and 50 GW. The results indicate that the technical potential of offshore wind in the Polish EEZ is significant and should be taken into account when designing the future electricity generation mix. [ABSTRACT FROM AUTHOR]

We have designed a real-world smart building energy fault detection (SBFD) system on a cloud-based Databricks workspace, a high-performance computing (HPC) environment for big-data-intensive applications powered by Apache Spark. By avoiding a Smart Building Diagnostics as a Service approach and keeping a tightly centralized design, the rapid development and deployment of the cloud-based SBFD system was achieved within one calendar year. Thanks to Databricks' built-in scheduling interface, a continuous pipeline of real-time ingestion, integration, cleaning, and analytics workflows capable of energy consumption prediction and anomaly detection was implemented and deployed in the cloud. The system currently provides fault detection in the form of predictions and anomaly detection for 96 buildings on an active military installation. The system's various jobs all converge within 14 min on average. It facilitates the seamless interaction between our workspace and a cloud data lake storage provided for secure and automated initial ingestion of raw data provided by a third party via the Secure File Transfer Protocol (SFTP) and BLOB (Binary Large Objects) file system secure protocol drivers. With a powerful Python binding to the Apache Spark distributed computing framework, PySpark, these actions were coded into collaborative notebooks and chained into the aforementioned pipeline. The pipeline was successfully managed and configured throughout the lifetime of the project and is continuing to meet our needs in deployment. In this paper, we outline the general architecture and how it differs from previous smart building diagnostics initiatives, present details surrounding the underlying technology stack of our data pipeline, and enumerate some of the necessary configuration steps required to maintain and develop this big data analytics application in the cloud. [ABSTRACT FROM AUTHOR]

E-mobility represents an important part of the EU's green transition and one of the key drivers for reducing CO2 pollution in urban areas. To accelerate the e-mobility sector's development it is necessary to invest in energy infrastructure and to assure favorable conditions in terms of competitive electricity prices to make the technology even more attractive. Large peak consumption of parking lots which use different variants of uncoordinated charging strategies increases grid problems and increases electricity supply costs. On the other hand, as observed lately in energy markets, different, mostly uncontrollable, factors can drive electricity prices to extreme levels, making the use of electric vehicles very expensive. In order to reduce exposure to these extreme conditions, it is essential to identify the optimal way to supply parking lots in the long term and to apply an adequate charging strategy that can help to reduce costs for end consumers and bring higher profit for parking lot owners. The significant decline in photovoltaic (PV) and battery storage technology costs makes them an ideal complement for the future supply of parking lots if they are used in an optimal manner in coordination with an adequate charging strategy. This paper addresses the optimal power supply investment problem related to parking lot electricity supply coupled with the application of an optimal EV charging strategy. The proposed optimization model determines optimal investment decisions related to grid supply and contracted peak power, PV plant capacity, battery storage capacity, and operation while optimizing EV charging. The model uses realistic data of EV charging patterns (arrival, departure, energy requirements, etc.) which are derived from commercial platforms. The model is applied using the data and prices from the Croatian market. [ABSTRACT FROM AUTHOR]

Energy infrastructure connectivity is a key implementation area for the success of the Belt and Road Initiative. In the current complex international environment, China's energy infrastructure investment in the countries along the Belt and Road is often restricted due to varying degrees of heated disputes with the host countries, thus facing the political risk of investment loss or even failure. This paper used the Heckman two-stage selection model to overcome the sample selection problem in traditional literature and systematically studied the political risks to China's energy infrastructure investment in countries along the Belt and Road within a unified framework. The results showed that Chinese energy infrastructure investments exhibited market-seeking and energy resource-seeking features; while political risks had a significant impact on choosing the locations of energy infrastructure investments, socio-environmental factors were not given sufficient attention. At the national level, the implementation of the Belt and Road Initiative was beneficial to China's foreign energy infrastructure investments under certain regulatory levels and environmental policy performance. [ABSTRACT FROM AUTHOR]

This study focuses on the specific topic of assessing the negative visual impacts associated with renewable energy infrastructure that may prevent their wider deployment in energy mix. The main objective of the paper is to quantify the perception of the visual impact of renewable energy infrastructure and to estimate potential changes in the visitation of a location after the construction of power plants. The research was conducted using a questionnaire survey in which 449 respondents evaluated edited photographic materials of seven locations with a fictitious power plant. The collected data served as input for the statistical testing of eight defined hypotheses using the U-Mann–Whitney test. The results confirmed trends regarding the influence of age, educational level, and power plant proximity on the overall acceptance of renewable energy infrastructure. Landscape-forming factors affecting the acceptance rate of power plants were also defined at the local level. [ABSTRACT FROM AUTHOR]

Modern power and transportation systems are subject to high requirements for reliability and performance in performing their specified functions. At the same time, these requirements are constantly increasing with the increasing complexity of technology and the introduction of electronics and computer technology into its structure. This is fully applicable to energy and transportation infrastructure, including electric vehicles. The complexity of the systems and increasing requirements for them have led to the fact that the problem of increasing their operational reliability has acquired great importance. The article presents a review of methods and justification of ensuring a high level of reliability and serviceability of technical systems as one of the most important tasks in the creation and operation of complex systems, such as modern energy and transportation systems. It is shown that a significant reserve in solving the problem of increasing the reliability and performance of technical systems is the information on failures and malfunctions of these systems obtained from the field of operation. The methodology of collection and processing of statistical information on failures of vehicles described by different distribution laws is outlined. [ABSTRACT FROM AUTHOR]

Planning the best path for the energy system decarbonization is currently one of the issues of high global interest. At the European level, the recent policies dealing with the transportation sector have decided to ban the registration of light-duty vehicles powered by internal combustion engines fed by fossil fuels, from 2035. Regardless of the official positions, the major players (industries, politicians, economic and statistical institutions, etc.) manifest several opinions on this decision. In this paper, a mathematical model of a nation's energy system is used to evaluate the economic impact of this decision. The model considers a superstructure that incorporates all energy conversion and storage units, including the entire transportation sector. A series of succeeding simulations was run and each of them was constrained to the achievement of the decarbonization level fixed, year by year, by the European community road-map. For each simulation, an optimization algorithm searches for a less costly global energy system, by including/excluding from the energy system the energy conversion units, storage devices, using a Mixed Integer Linear approach. Three optimization scenarios were considered: (1) a "free" scenario in which the only constraint applied to the model is the achievement of the scheduled decarbonization targets; (2) an "e-fuels" scenario, in which all new non-battery-electric light-duty vehicles allowed after 2035 must be fed with e-fuels; (3) a "pure electric" scenario, in which all new light-duty vehicles allowed after 2035 are battery-electric vehicles. The comparison of the optimum solutions for the three scenarios demonstrates that the less costly transition to a fully renewable energy system decarbonizes the transportation sector only when the share of renewable energy sources exceeds 90%. E-fueled light-duty vehicles always turn out to be a less expensive alternative than the electric vehicles, mainly because of the very high cost of the energy supply infrastructure needed to charge the batteries. Most of all, the costs imposed to society by the "e-fuels" and "pure electric" light-duty-vehicle decarbonizing scenarios exceed by 20% and 60%, respectively, the "free" transition scenario. [ABSTRACT FROM AUTHOR]

Drones are becoming a greater threat to modern electrical grids with the capability to cause expensive and time-consuming damage repairs to substations and transmission lines. Consumer drones have the potential to cause harm at a low cost, and finding methods to counter these threats is becoming more crucial to keep grids secure. In 2021, there was an attempted attack on a substation with a consumer drone which highlighted the need for research in this area. Previously, there has been a large focus on counter drones around places such as airports; however, more focus is warranted to analyze drone impact on the grid infrastructure. Methods to counter drones' harmful impacts vary from physical methods to using electromagnetic waves. This article looks to identify and propose potential applications for existing technologies, as well as developing anti-drone technologies. These methods have not been adopted yet; thus, there is a great opportunity to utilize these existing technologies to defend the grid. The methods investigated were surveillance cameras, patrolling drones, nets, signal jammers, and energy weapons. The existing technology is currently lacking in the area of drone defense and can be improved with existing studies. However, there is a need to identify those methods and find ways to apply them to the power grid. Different defending technologies vary concerning their potential implementation. This paper also identifies and categorizes different results these methods produce to counter drones and their associated costs. [ABSTRACT FROM AUTHOR]

Large-scale clean-heating renovations are being carried out in northern China as part of important measures to optimize energy infrastructure, improve the atmospheric environment, and minimize peak CO2 emissions. Because rural areas in the urban–rural fringe are close to the city center, they have several advantages in centralized heating reforms, but there are no effective means to measure whether a transformation is economical or has good environmental effects. In this paper, based on an actual reconstruction project, 100 typical households were selected for a related test. These typical households evinced convergence and possessed certain regional characteristics; therefore, the applicability of the models had certain limitations. To make sure that the relevant factors were fully considered in establishing the model, a prediction model group was established regarding heat consumption in winter (four models in total) that could predict the actual effect well. Lastly, the authors used the model group to calculate economic effects and CO2 emission reduction in rural heating transformations in Beijing under different heating methods. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) are gaining more and more traction as a viable option in the automotive sector. This mode of transportation is currently on track, according to current trends, to totally replace internal combustion engine (ICE) cars in the not-too-distant future. The economic system, the energy infrastructure, and the environment are just a few of the areas where electric vehicles could have a major impact. The transportation industry produces the second-most carbon dioxide gas from the combustion of fossil fuels, making it the second-highest contributor to global warming. A lot of people are looking to EVs, or electric vehicles, as a possible game-changing answer to this problem. Since an electric motor drives the electric vehicle's propeller instead of an internal combustion engine, electric vehicles can reduce their carbon dioxide (CO2) emissions compared to traditional automobiles. If coupled with renewable energy sources, EVs might theoretically become emission-free automobiles. In this paper, we will examine the various EV drive circuit types, including their construction and the benefits and drawbacks of employing each. This article discusses the current state of battery technology with an emphasis on EV batteries. This article discusses the best electric motor for EVs in terms of efficiency, power density, fault tolerance, dependability, cost, and more. Next, we conduct in-depth research into the difficulties and potential rewards of EV adoption in the future. While improvements in areas like charging times and battery performance are encouraging, government regulation of EVs remains a big non-technical barrier. [ABSTRACT FROM AUTHOR]

The global economy faces increasing environmental challenges and economic instability, prompting the adoption of innovative energy technologies as a crucial strategy. This study addresses the urgent quest for sustainable development in South Africa, specifically by evaluating renewable energy solutions. This study utilizes a comprehensive literature analysis to examine the current state of renewable energy infrastructure, policy frameworks, technological advancements, and economic viability within the South African context. Synthesizing insights from the existing literature on the interplay between energy, economy, and technology, this study aims to provide a refined understanding of renewable energy solutions' feasibility and integration potential. The exploration of these solutions in South Africa identifies key opportunities, challenges, and implications for sustainable development. These findings offer valuable guidance for policymakers, researchers, and stakeholders in advancing a country's transition towards a sustainable energy future. [ABSTRACT FROM AUTHOR]

Compressed natural gas (CNG) main stations are critical components of the urban energy infrastructure for CNG distribution. Due to its high electrification and significant power consumption, researching the economic operation of the CNG main station in demand response (DR)-based electricity pricing environments is crucial. In this paper, the dehydration process is considered in the CNG main station energy consumption model to enhance its participation in DR. A bilevel economic dispatch model for the CNG main station is proposed, considering critical peak pricing. The upper-level and lower-level models represent the energy cost minimization problems of the pre-system and rear-system, respectively, with safety operation constraints. The bilevel programming model is solved using a genetic algorithm combined with a bilevel programming method, which has better efficiency and convergence. The proposed optimization scheme has better control performance and stability, reduces the daily electricity cost by approximately 21.04%, and decreases the compressor switching frequency by 50.00% without changing the CNG filling demand, thus significantly extending the compressor's service life. Moreover, the average comprehensive power cost of processing one unit of CNG reduces 20.62%. [ABSTRACT FROM AUTHOR]

The ambitious goal of the European Union (EU) countries is to achieve carbon neutrality by providing inclusive economic growth, which requires the development of relevant incentives and initiatives. Furthermore, such incentives and initiatives should guarantee the achievement of the declared goals. Energy sectors are the core determinant of inclusive economic growth. Traditional energy resources (coal oriented) have a higher negative impact on nature and people's well-being than on economic and social benefits. However, the transition to renewable energy raises new issues in achieving goals of inclusive economic growth: affordable and clean energy, responsible energy consumption, and energy infrastructure. The analysis of the theoretical framework found that the digitalization of government could be a core instrument for handling the abovementioned issues. The paper aims to justify the role of green energy in achieving inclusive economic growth empirically. The study applies the following methods: fully modified Ordinary Least Square (OLS) and canonical cointegrating regression. The findings allow concluding that institutional quality passively affects inclusive economic growth and that the digitalization of government has a U-shaped impact on inclusive economic growth. In this case, countries should boost the digital transformation of public services and continuously increase the quality of institutions. [ABSTRACT FROM AUTHOR]

In the current era, the skyrocketing demand for energy necessitates a powerful mechanism to mitigate the supply–demand gap in intelligent energy infrastructure, i.e., the smart grid. To handle this issue, an intelligent and secure energy management system (EMS) could benefit end-consumers participating in the Demand–Response (DR) program. Therefore, in this paper, we proposed a real-time and secure incentive-based EMS for smart grid, i.e., RI-EMS approach using Reinforcement Learning (RL) and blockchain technology. In the RI-EMS approach, we proposed a novel reward mechanism for better convergence of the RL-based model using a Q-learning approach based on the greedy policy that guides the RL-agent for faster convergence. Then, the proposed RI-EMS approach designed a real-time incentive mechanism to minimize energy consumption in peak hours and reduce end-consumers' energy bills to provide incentives to the end-consumers. Experimental results show that the proposed RI-EMS approach induces end-consumer participation and increases customer profitabilities compared to existing approaches considering the different performance evaluation metrics such as energy consumption for end-consumers, energy consumption reduction, and total cost comparison to end-consumers. Furthermore, blockchain-based results are simulated and analyzed with the help of deployed smart contracts in a Remix Integrated Development Environment (IDE) with the parameters such as transaction efficiency and data storage cost. [ABSTRACT FROM AUTHOR]

Recent motivation to cut greenhouse gas emissions to combat climate change has led to increasing transportation electrification. However, electric vehicle proliferation comes with a number of challenges such as battery capacities and the range anxiety of electric vehicles. In this paper, a review of the main components that affect electric vehicle adoption, which are charging infrastructure and energy resources, is presented. We discuss the categories of electric vehicle charging infrastructure, based on the location-of-charge and the charging technology. In addition, a review of the energy resources required for electric vehicles is also presented. The key features of these batteries are also discussed. [ABSTRACT FROM AUTHOR]

Thorium was a part of energy infrastructure in the 19th century due to the refractory and electronic properties of its dioxide. It will be a part of future energy infrastructure as the most abundant energy reserve based on nuclear fission. This paper discusses the solid-state chemistry of the monoxides and related rocksalt phases of thorium and the rare earths, both at atmospheric and at high pressure. The existence of solid thorium monoxide was first suggested more than 100 years ago; however, it was never obtained in bulk and has been studied mostly theoretically. Monoxides of lanthanides from Eu to Ho are ferromagnetic semiconductors sought for spintronics and were studied in thin films. La to Sm metallic monoxides were synthesized in bulk at pressures below 5 GPa. Recently, ThO formation in thin films has been reported and the stability of bulk ThO at high pressure was theoretically predicted based on first principles computations at 0 K. New ab initio computations were performed accounting for temperature effects up to 1000 K using lattice dynamics in the quasi-harmonic approximation. New computational results confirm the stabilization of pure ThO above 30 GPa and suggest the possibility of high-pressure synthesis of (Th,Nd)O at 1000 K and 5 GPa. [ABSTRACT FROM AUTHOR]

As the demand for electricity continues to grow in Saudi Arabia, finding ways to increase power generation becomes increasingly important. However, conventional power generation methods such as burning fossil fuels contribute significantly to environmental pollution and harm human health through the emissions of greenhouse gases. One potential solution to this problem is the use of solar energy, which has the advantage of being abundant in Saudi Arabia due to its location in the sun belt. When compared to conventional power generation methods, solar energy is a viable alternative, particularly when the indirect costs of fossil fuels, such as harm to the environment and human health, are considered. Using photovoltaic cells to convert sunlight into electrical energy is a key method for producing clean energy. Despite the initial cost of investing in solar energy infrastructure, it is ultimately less expensive than electricity derived from fossil fuels. In recognition of the potential of solar energy, the Saudi government has outlined an ambitious plan to install 41 GW of solar capacity and invest USD 108.9 billion by 2032. Additionally, financing and significant tax benefits have been provided to promote the development of the solar industry. This research article reviews the techno-economic analysis of PV power plants and examines previous policy papers and the existing research on the topic. [ABSTRACT FROM AUTHOR]

Climate change primarily caused by the greenhouse gases emitted as a result of the consumption of carbon-based fossil fuels is considered one of the biggest challenges that humanity has ever faced. Moreover, the Ukrainian crisis in 2022 has complicated the global energy and food status quo more than ever. The permanency of this multifaceted fragility implies the need for increased efforts to have energy independence and requires long-term solutions without fossil fuels through the use of clean, zero-carbon renewables energies. Hydrogen technologies have a strong potential to emerge as an energy eco-system in its production-storage-distribution-utilization stages, with its synergistic integration with solar-wind-hydraulic-nuclear and other zero-carbon, clean renewable energy resources, and with the existing energy infrastructure. In this paper, we provide a global review of hydrogen energy need, related policies, practices, and state of the art for hydrogen production, transportation, storage, and utilization. [ABSTRACT FROM AUTHOR]

The aim of the article is to identify problems related to the siting of wind farms, both those that have arisen as a result of recent legislative revisions and those arising from social developments in Poland. In 2022 a map defining 'exclusion zones' around wind turbines, i.e., areas where residential development was prohibited, was released in Poland. It was only then that many territorial governments realised the scale of the problems generated by the entry into force of the 2016 Wind Farm Act. It turned out that this group of municipalities included towns that might suffer some consequences despite the fact that there are no or few wind farms in their area. The aim of this paper is to identify towns and cities where more than one quarter of the area is land within the H10 zones, where the construction of wind farms is banned, if their distance from the nearest building or from the boundary of a national park is less than ten times the height of the turbine mast. The example of the town and rural municipality of Darłowo shows that in the early phase of their construction in Poland, wind turbines were perceived positively and did not give rise to conflicts. It was only after some time, as existing wind farms started to be expanded and new ones built, that protests emerged. The arguments of the parties to the conflict focused mainly on economic considerations: profits for the municipality versus losses for the residents neighbouring the wind turbines, such as barriers to the development of agritourism. The conflicts were fuelled and prolonged by irregularities in the municipality's planning documents and a poor flow of information about planned investments. In 2022, The Council of Ministers adopted a draft amendment to the Wind Farm Investment Act. This legislation represents a compromise between the opportunities for wind energy development and the needs of local communities. [ABSTRACT FROM AUTHOR]

Rapid urbanization across the world has led to an exponential increase in demand for utilities, electricity, gas and water. The building infrastructure sector is one of the largest global consumers of electricity and thereby one of the largest emitters of greenhouse gas emissions. Reducing building energy consumption directly contributes to achieving energy sustainability, emissions reduction, and addressing the challenges of a warming planet, while also supporting the rapid urbanization of human society. Energy Conservation Measures (ECM) that are digitalized using advanced sensor technologies are a formal approach that is widely adopted to reduce the energy consumption of building infrastructure. Measurement and Verification (M&V) protocols are a repeatable and transparent methodology to evaluate and formally report on energy savings. As savings cannot be directly measured, they are determined by comparing pre-retrofit and post-retrofit usage of an ECM initiative. Given the computational nature of M&V, artificial intelligence (AI) algorithms can be leveraged to improve the accuracy, efficiency, and consistency of M&V protocols. However, AI has been limited to a singular performance metric based on default parameters in recent M&V research. In this paper, we address this gap by proposing a comprehensive AI approach for M&V protocols in energy-efficient infrastructure. The novelty of the framework lies in its use of all relevant data (pre and post-ECM) to build robust and explainable predictive AI models for energy savings estimation. The framework was implemented and evaluated in a multi-campus tertiary education institution setting, comprising 200 buildings of diverse sensor technologies and operational functions. The results of this empirical evaluation confirm the validity and contribution of the proposed framework for robust and explainable M&V for energy-efficient building infrastructure and net zero carbon emissions. [ABSTRACT FROM AUTHOR]

Institutions of higher learning in South Africa are grappling with occasional power outages in lecture halls, leading to disruptions in academic activities and occasional loss of lecture hours. Therefore, this study presents a comprehensive evaluation of a grid-connected solar PV/Li-ion battery microgrid (μG) system aimed at maintaining a constant power supply to selected lecture halls at a university in the Western Cape, South Africa. The microgrid design, modelling, and simulations, conducted in the MATLAB/Simulink environment, include the solar PV, Li-ion battery, energy consumption of the lecture halls (load profile), boost converter, bidirectional converter, and grid. Using the detailed design, modelling, and simulation, the study evaluates the economic and environmental impacts of integrating μGs, focusing on enhancing energy reliability, reducing operational costs, and mitigating CO2 emissions. The results indicate that integrating the microgrid resulted in a significant 51% reduction in energy cost and a decrease in greenhouse gas emissions by 530 kgCO2e per hour. In Cases 2 and 4, where the battery supplied power, the annual battery degradation costs are 6.08% and 14.9% of the initial cost, respectively. The μG ensures an uninterrupted power supply and improves the overall reliability of the university's energy infrastructure. It promotes environmental sustainability goals of zero emissions and maintains continuous academic activities during grid outages. Furthermore, it fosters a conducive learning environment, supports innovation and creativity in sustainable energy technologies, and sets a standard for other higher education institutions to integrate renewable energy-powered μGs. [ABSTRACT FROM AUTHOR]

Isolated water and energy microgrids (IWEMGs) serve as vital solutions for enhancing the well-being of remote and rural communities, particularly in areas where water and energy resources are scarce. This has spurred research into the interdependence between the water and energy sectors (water–energy nexus), a field that has grown in response to technological advancements. Through a systematic optimization framework, this review critically evaluates the integration of various technologies within IWEMGs, encompassing infrastructure, management, and strategic planning, while considering economic and social impacts. IWEMGs incorporate diverse technologies for the infrastructure, management, and strategic planning of water and energy resources, integrating economic and social considerations to inform decisions that affect both immediate and long-term sustainability and reliability. This article presents an exhaustive review of the literature on IWEMG management, employing an approach that synthesizes existing studies to enhance the understanding of strategic IWEMG management and planning. It introduces a structured taxonomy for organizing research trends and tackling unresolved challenges within the field. Notably, the review identifies critical gaps, such as the lack of comprehensive data on water demand in isolated locations, and underscores the emerging role of game theory and machine learning in enriching IWEMG management frameworks. Ultimately, this review outlines essential indicators for forthcoming research, focusing on the optimization, management, and strategic planning of IWEMG resources and infrastructure, thereby setting a direction for future technological and methodological advancements in the field. [ABSTRACT FROM AUTHOR]

The energy carrier infrastructure, including both electricity and natural gas sources, has evolved and begun functioning independently over recent years. Nevertheless, recent studies are pivoting toward the exploration of a unified architecture for energy systems that combines Multiple-Energy Carriers into a single network, hence moving away from treating these carriers separately. As an outcome, a new methodology has emerged, integrating electrical, chemical, and heating carriers and centered around the concept of Energy Hubs (EHs). EHs are complex systems that handle the input and output of different energy types, including their conversion and storage. Furthermore, EHs include Combined Heat and Power (CHP) units, which offer greater efficiency and are more environmentally benign than traditional thermal units. Additionally, CHP units provide greater flexibility in the use of natural gas and electricity, thereby offering significant advantages over traditional methods of energy supply. This article introduces a new approach for exploring the steady-state model of EHs and addresses all related optimization issues. These issues encompass the optimal dispatch across multiple carriers, the optimal hub interconnection, and the ideal hub configuration within an energy system. Consequently, this article targets the reduction in the overall system energy costs, while maintaining compliance with all the necessary system constraints. The method is applied in an existing Smart Microgrid (SM) of a typical Greek 17-bus low-voltage distribution network into which EHs are introduced along with Renewable Energy Sources (RESs) and Electric Vehicles (EVs). The SM experiments focus on the optimization of the operational cost using different operational scenarios with distributed generation (DG) and CHP units as well as EVs. A sensitivity analysis is also performed under variations in electricity costs to identify the optimal scenario for handling increased demand. [ABSTRACT FROM AUTHOR]

This study examines the effect of international financial flows, including investments and development assistance, on the expansion of renewable energy technologies. It also seeks to investigate the impact of the sectoral economy on the proportion of renewable energy consumption in Ethiopia. This study used an explanatory research design and a quantitative research approach. An autoregressive distributed lag model was applied to explore the long and short-term relationship among variables. A time series of data aggregated and disaggregated ranging from 2000 to 2022 was used. According to this study, sustainable finance programs are essential for advancing and aiding renewable energy projects in the long and short term. Ethiopia's use of renewable energy will increase as sustainable finance rises. The main economic sectors determining Ethiopia's consumption of renewable energy in the long and short term include the manufacturing, mining and service industries. This study's findings imply that policies focusing on providing continuous financial support and fostering international cooperation to promote the development of the manufacturing sector are needed. This could include incentives for adopting renewable energy technologies and investing in renewable energy infrastructure. On the other hand, since the service and mining industries negatively impact renewable energy use, there is a need to diversify renewable energy sources beyond these sectors. This could involve promoting renewable energy projects in other sectors, such as manufacturing, agriculture, construction and trade. Based on the findings of this study, it is suggested that policymakers carefully consider the consequences within each economic sector when formulating decisions related to renewable energy. This study is novel in presenting empirical evidence linking renewable energy use to long- and short-term economic growth. [ABSTRACT FROM AUTHOR]

We consider the restrictions on photovoltaic (PV) capacity that are caused by limitations on where panels can be sited and find quantitative evidence for the need for high efficiencies. We define 15% of the UK's energy consumption as a "significant" contribution and, with London as an exemplar, we perform an idealised calculation that makes the most optimistic possible assumptions about the capabilities of future PV technologies and use published surveys on energy usage, dwelling type and insolation. We find that covering every UK domestic roof with the highest power conversion efficiency (PCE) solar panels currently commercially available could produce up to 9% of the UK's energy. A 15% contribution would require PV technologies with >37% PCE, more than the theoretical Shockley–Queisser limit. Replacing the idealising assumptions with more realistic estimates increases this by 2–3 times. Alternatively, a solar farm using the currently available PCEs would require a politically challenging ~1200 km2 of new land, roughly the area of Greater London, for this 15% contribution. We conclude that PCEs must be driven higher than even the Shockley–Queisser limit for PV to play a significant part in carbon mitigation. [ABSTRACT FROM AUTHOR]

Micro-hydropower plants have now become a way to decarbonise the power generation system. Older micro-hydropower plants generally operate at a fixed speed. When there is a lack of rainfall, these plants operate outside their design flow causing various problems (such as the occurrence of the phenomenon of cavitation, decreased turbine performance, and decreased operating hours), especially in micro-hydropower plants installed in irrigation infrastructure, where the priority for water use is crops. This study aims to carry out a comparative evaluation of several indicators (cavitation, investment costs, electricity production and economic benefit) of two types of control system on an asynchronous electric generator (a fixed speed control system (scenario 1) and a variable-speed control system (scenario 2)) at the same micro-hydropower plant. The Rebolluelo micro-hydropower plant (Spain) is used for this purpose as a case study. This micro-hydropower plant uses a semi-Kaplan turbine coupled to an asynchronous electric generator through a gearbox. The results show the advantages of using a variable-speed control system. The use of variable-speed technology: (i) eliminates the possibility of cavitation, (ii) increases the power output ratio (from 35.87 % to 93.03 % ), and (iii) increases the economic benefit (from 29.31 % to 108.72 % ). There are also, of course, disadvantages, such as an 11.96 % increase in cost. This work demonstrated the superiority of variable speed technology at micro-hydropower plants for three of the four indicators evaluated. This work could be of assistance when making decisions regarding future micro-hydropower plant installations. [ABSTRACT FROM AUTHOR]

The hierarchical structure and microscale dimensions of carbon nanotube yarns (CNTYs) make them great candidates for the development of integrated sensing applications. The change in the electrical resistance of CNTYs due to mechanical strain, known as piezoresistivity, is the principal mechanism in strain sensing using CNTYs. While the axial tensile properties of CNTYs have been studied widely, studies on the axial piezoresistive response of CNTYS under compression have been limited due to the complexities associated with the nature of the experiments involving subjecting a slender fiber to compression loading in its axial direction. In this study, the piezoresistive response of a single CNTY embedded into a polymeric resin (CNTY monofilament composite) was investigated under axial compression. The results suggest that the CNTY exhibits a strong piezoresistive response in the axial direction with sensitivity or gauge factor values in the order of 0.4–0.5 for CNTY monofilament composites. The piezoresistive response of the CNTY monofilament composites under compression was compared to that under tension and it was observed that the sensitivity appears to be slightly lower under compression. The potential change in sensitivity between the freestanding CNTY and the CNTY monofilament composite under compression is still unknown. Knowing the axial piezoresistive response of the CNTYs under both tension and compression will enable their use in sensing applications where the yarn undergoes compression including those in aerospace and marine structures, and civil or energy infrastructure. [ABSTRACT FROM AUTHOR]

The real estate sector is undergoing a significant transformation. The global energy transition has greatly impacted the entire energy infrastructure, forcing the energy-consuming property sector to increase its operational efficiency. Today, the European Union (EU) enhances building smartness in real estate through regulation. However, the attitudes towards smartness in the financially significant housing market remain unclear. This study observed the attitudes and readiness of Finnish housing market operators toward smartness at the end of 2022. In total, 13 semi-structured interviews were held with housing market professionals. The analysis was further supported by categorizing the interviewees into novice practitioners and smart building experts. The research results implied that the attitudes towards smartness among novice practitioners, including real estate investors and owners, are still rather reserved compared to the control group (consisting of smart building experts). However, enhancing the attitude of real estate investors and owners is crucial to ensure a successful smart transition towards carbon neutrality in the built environment. The results of this study highlight the need for a standardized metric for building smartness. However, engaging market practitioners in developing such metrics is essential to ensure that the future standard for smartness answers the market's needs. [ABSTRACT FROM AUTHOR]

Implementing high-performance computing (HPC) to solve problems in energy infrastructure resilience research in a heterogeneous environment based on an in-memory data grid (IMDG) presents a challenge to workflow management systems. Large-scale energy infrastructure research needs multi-variant planning and tools to allocate and dispatch distributed computing resources that pool together to let applications share data, taking into account the subject domain specificity, resource characteristics, and quotas for resource use. To that end, we propose an approach to implement HPC-based resilience analysis using our Orlando Tools (OT) framework. To dynamically scale computing resources, we provide their integration with the relevant software, identifying key application parameters that can have a significant impact on the amount of data processed and the amount of resources required. We automate the startup of the IMDG cluster to execute workflows. To demonstrate the advantage of our solution, we apply it to evaluate the resilience of the existing energy infrastructure model. Compared to similar approaches, our solution allows us to investigate large infrastructures by modeling multiple simultaneous failures of different types of elements down to the number of network elements. In terms of task and resource utilization efficiency, we achieve almost linear speedup as the number of nodes of each resource increases. [ABSTRACT FROM AUTHOR]

This study examines the impact of energy poverty on internal immigration based on the current situation in which reducing energy poverty is a necessary condition for ensuring sustainable development. The threshold effects model is applied to verify the significance of energy poverty in the prediction of internal immigration. The main results suggest that energy poverty significantly and negatively affects internal immigration. A heterogeneity analysis between coastal and non-coastal regions shows that the effects are more pronounced in non-coastal regions than in coastal regions. Further analysis reveals that there exists a kink in the threshold effects. The results remain robust using the specification of the kink threshold effects model. The policy implication is that a balanced development of energy infrastructure in different regions is required to achieve better social welfare for migrants. [ABSTRACT FROM AUTHOR]

The significance of renewable energy in achieving necessary reductions in emissions to limit global warming to 1.5 degrees Celsius is widely acknowledged. However, there is growing concern over the allocation of land for constructing the required new infrastructure. Nowhere is this conflict more apparent than in India, where renewable energy targets are ambitious and land use conflicts are already significant. India intends to increase renewable energy to 500 GW by 2030. This would require an additional 42 GW of renewable energy to be installed every year. Although renewable energy can provide the solution to both India's growing need for cheap energy and climate change mitigation, the sustainable future of renewable energy deployment is far from simple due to its associated land use impacts and socio-ecological risk. While others have highlighted challenges to India's renewable energy targets, here we focus on the land use change issues that will need to be addressed for India to meet its targets. We introduce a series of recommendations and highlight how these could contribute to mainstreaming land values and facilitate the implementation of India's 2030 renewable energy targets. These recommendations include suggested planning approaches that would guide the development of standard siting guidelines, identification of preferential "go-to" areas for renewable energy, and the development of tools that allow access to data and information to site renewable right. Policy recommendations highlight utilizing converted lands and existing built infrastructure for renewable energy development, and adapting existing policies so they address land use impacts. [ABSTRACT FROM AUTHOR]

Small (<1 km2) saline wetlands scattered across the landscape often go unnoticed or are threatened by urbanization or other interventions, despite their role as biodiversity shelters. This study is needed to show methods for monitoring this specific kind of wetland, and to guide the selection of analytical techniques. We provide data and comparisons for salient soil traits of two quasi-pristine gypsiferous and saline wetlands named Farrachuela (FA) and Agustín (AG). The soil characteristics presented in this article are a more sensitive indicator of their ecological status than some of the most used indicators, such as birds and plants. We found significant differences between the two saladas in percent water saturation, equivalent calcium carbonate, gypsum content, and soil salinity expressed as electrical conductivity both of 1:5 soil-to-water ratio and of saturation extracts. The differences were also significant in the concentrations of Mg2+, Na+, and Cl−, while they were non-significant for Ca2+, HCO32−, and SO42−. The mean contents of the six ions were lower in FA than in AG. Both pH and sodium adsorption ratios were significantly different between the two wetlands. The data are mainly examined and plotted by displaying their non-parametric statistics, a synoptic approach that will allow us to monitor the evolution of the wetlands against both traditional agricultural pressures and emerging green energy infrastructures. Last but not least, we discuss the shortcomings of some standard laboratory methods when applied to gypsum-rich soils. [ABSTRACT FROM AUTHOR]

To lessen the environmental impact of the maritime industry, ports must decarbonize in conformity with various standards such as the European Green Deal and the Sustainable Development Goals (SDGs). In this regard, they must demonstrate integrated low-emission energy production, distribution, and supply, as well as sustainable alternative infrastructure for refueling ships, cargo handling equipment, and other vehicles inside port boundaries. To address this issue, ports must progress toward smartening their operations. This requires intelligent infrastructure and components, with smart energy infrastructure being one of the most crucial ones. It is a part of port energy management systems (EMSs) and works based on modern technology to balance energy demand, distributions, and supply while transitioning to renewable energies. This study investigates the "scoping review" of "smart energy infrastructure" deployment and its efficiency in seaport EMSs to reduce the port's carbon footprint (C.F). The "Introduction" section discusses the subject's significance. The "Materials and Methods" section explains the process of selecting and revising references and relevant material. The "Findings" section then examines the several aspects and sections of a smart port and smart energy infrastructure, as well as how they function. The "Discussion" section explains the interpretation based on the present situation. Finally, the "Conclusion" part gives scientific thoughts and comments on the work-study debate and ideas for future research in the same field to help port authorities achieve sustainability. [ABSTRACT FROM AUTHOR]

The electric vehicle (EV) market is expanding rapidly to achieve the future goal of eco-friendly transportation. The scientific planning of energy supplement infrastructures (ESIs), with appropriate locations and capacity, is imperative to develop the EV industry. In this research, a mixed integer linear programming (MILP) model is proposed to optimize the location and capacity of ESIs, including vehicle charging stations (VCSs), battery swapping stations (BSSs), and battery charging stations (BCSs), in highway networks. The objective of this model is to minimize the total cost with the average waiting time for EVs being constrained. In this model, battery swapping and transportation behaviors are optimized such that the EV average waiting time can be reduced, and the average queue and service process waiting time is estimated by the M/M/1 model. Real-world data, i.e., from the London M25 highway network system, are used as a case study to test the effectiveness of the proposed method. The results show that considering battery transportation behaviors is more cost efficient, and the results are sensitive to the EV average waiting time tolerance, battery cost, and charging demand. [ABSTRACT FROM AUTHOR]

Innovation in the economy is closely tied to energy development, encompassing the exploration of new energy sources, increased energy production efficiency, and the integration of diverse energy sources for safe and effective supply to industries and households. Outdated energy infrastructure disrupts electricity continuity and hampers economic innovation. Power interruptions lead to higher SAIDI and SAIFI reliability indices. Quality and reliability requirements have sparked interest in enclosed energy devices. Vacuum technology has been pivotal in electrical switchgear insulation and arc-quenching for over four decades. However, the lack of real-time pressure monitoring systems for vacuum equipment, especially enclosed disconnectors, limits their use as isolation connectors. Potential insulation failure poses risks to power line maintenance teams and can lead to unplanned shutdowns, further compromising energy supply quality. This article explores an innovative pressure monitoring system for vacuum interrupters, utilizing fiber optic Bragg grids as a measuring sensor, enabling pressure measurement within the vacuum chamber ranging from 2 × 101 Pa to 5 × 105 Pa. [ABSTRACT FROM AUTHOR]