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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]

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]

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]

The growing integration of renewable energy sources into grid-connected microgrids has created new challenges in power generation forecasting and energy management. This paper explores the use of advanced machine learning algorithms, specifically Support Vector Regression (SVR), to enhance the efficiency and reliability of these systems. The proposed SVR algorithm leverages comprehensive historical energy production data, detailed weather patterns, and dynamic grid conditions to accurately forecast power generation. Our model demonstrated significantly lower error metrics compared to traditional linear regression models, achieving a Mean Squared Error of 2.002 for solar PV and 3.059 for wind power forecasting. The Mean Absolute Error was reduced to 0.547 for solar PV and 0.825 for wind scenarios, and the Root Mean Squared Error (RMSE) was 1.415 for solar PV and 1.749 for wind power, showcasing the model's superior accuracy. Enhanced predictive accuracy directly contributes to optimized resource allocation, enabling more precise control of energy generation schedules and reducing the reliance on external power sources. The application of our SVR model resulted in an 8.4% reduction in overall operating costs, highlighting its effectiveness in improving energy management efficiency. Furthermore, the system's ability to predict fluctuations in energy output allowed for adaptive real-time energy management, reducing grid stress and enhancing system stability. This approach led to a 10% improvement in the balance between supply and demand, a 15% reduction in peak load demand, and a 12% increase in the utilization of renewable energy sources. Our approach enhances grid stability by better balancing supply and demand, mitigating the variability and intermittency of renewable energy sources. These advancements promote a more sustainable integration of renewable energy into the microgrid, contributing to a cleaner, more resilient, and efficient energy infrastructure. The findings of this research provide valuable insights into the development of intelligent energy systems capable of adapting to changing conditions, paving the way for future innovations in energy management. Additionally, this work underscores the potential of machine learning to revolutionize energy management practices by providing more accurate, reliable, and cost-effective solutions for integrating renewable energy into existing grid infrastructures. [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]

The global energy sector is currently undergoing a transformative shift mainly driven by the ongoing and increasing demand for clean, sustainable, and reliable energy solutions. However, integrating renewable energy sources (RES), such as wind, solar, and hydropower, introduces major challenges due to the intermittent and variable nature of RES, affecting grid stability and reliability. Hybrid energy storage systems (HESS), which combine multiple energy storage devices (ESDs), present a promising solution by leveraging the complementary strengths of each technology involved. This comprehensive review examines recent advancements in grid-connected HESS, focusing on their components, design considerations, control strategies, and applications. It provides a detailed analysis of technological progress in various ESDs and the critical role of power conversion, control, energy management, and cooling systems in optimizing HESS performance. Highlighting case studies of some notable and successful HESS implementations across the globe, we illustrate practical applications and identify the benefits and challenges encountered. By addressing these challenges, HESS can significantly enhance the efficiency and reliability of RES, supporting the shift towards a sustainable and resilient energy infrastructure. The paper concludes by identifying future research directions, highlighting the development of intelligent control systems, sustainable materials, and efficient recycling processes to ensure the widespread adoption and long-term viability of HESS. [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]

Water security in arid and semi-arid Middle Eastern climates has been severely impacted by effects of climate change such as reduced precipitation, diminished storage, increased evapotranspiration, and prolonged heat waves. These climate effects are compounded in Iraq, where populations, agriculture, industry, and energy rely heavily on varying transboundary water flows to meet water demands. Iraq's most profitable sector, energy, is especially threatened by insufficient water supply, which complicates government decision making in energy infrastructure development. The goal of this paper is to develop a scenario-based multi-criteria analysis framework to prioritize infrastructure investments in the context of climate change and scarcity of natural resources. Infrastructure facilities are evaluated against social, economic, climate, and hydrologic criteria across a set of disruptive climatological, economic, and social scenarios to identify robust initiatives and the most and least disruptive scenarios to the system. A particular innovation of this paper is the evaluation of hydrology data derived from satellites in determining water scarcity impact on individual energy facilities. The methods are demonstrated for a critical sector of Iraq's economy: oil and natural gas. The demonstration includes 13 system-order criteria, 44 oil and gas initiatives within Iraq, and seven risk scenarios. The results include an accounting of the most and least disruptive scenarios to energy sector priorities and scenario-based system orderings to guide stakeholders in investment prioritization. [ABSTRACT FROM AUTHOR]

Commitments to rapidly reduce greenhouse gas (GHG) emissions from aviation are growing stronger, stimulating efforts to meet net zero targets. As critical infrastructure for air travel, airports obviously have an important role to play in making the transition away from fossil fuels. This requires major organisational change, operational innovation and future planning for low carbon and zero emission travel. New Zealand's Christchurch International Airport has taken a pioneering lead, developing a transformational agenda, achieving global recognition for its emissions reductions and mobilising to build renewable energy infrastructure. This paper reports on research commissioned to assess the airport's journey toward a green transition. It discusses how the airport made sustainability integral to its business purpose and organisational culture, how it developed a Green Transition Plan, and how it has raised sustainability on the agenda, locally, nationally and internationally. It also reports the airport's development of a renewable energy precinct and its partnerships for the future implementation of low emission travel powered by renewable electricity and green hydrogen. [ABSTRACT FROM AUTHOR]

After Russia's massive Cyber-attacks on Ukraine's government and bank sectors in January–February 2022, many analysts alleged that Cyber-power would be a crucial component of Russia's military victory in Ukraine. Contrary to these expectations, however, Russian Cyber-intrusions yielded meagre strategic benefits, with Moscow seemingly prioritising conventional warfare and destruction of energy and civilian infrastructure instead. Using a theory of asymmetric conflict, this paper argues, somewhat counterintuitively, that the reason behind inhibited efficacy of Russian Cyber-operations post-2022 are Moscow's prior Cyber-attacks against Ukraine since 2013. While having helped the Kremlin weaken Ukraine's Cyber-networks and collect local intelligence, these antecedent Cyber-operations have provided a two-pronged learning loop: for Ukraine to cultivate habits of mitigating Russian Cyber-threats, and for Russia to acquire habits of relying on information operations more than on destructive Cyber-attacks. This "pedagogical" mechanism ultimately enabled Ukraine to redress its Cyber-asymmetry with Russia and deny Moscow success in its Cyber-intrusions post-2022. [ABSTRACT FROM AUTHOR]

Purpose: Renewable energy infrastructure is an important asset class in the context of reducing global carbon emissions going forward. This includes solar power, wind farms, hydro, battery storage and hydrogen. This paper examines the risk-adjusted performance and diversification benefits of listed renewable energy infrastructure globally over Q1:2009–Q4:2022 to examine the role of renewable energy infrastructure in a global infrastructure portfolio and in a global mixed-asset portfolio. The performance of renewable energy infrastructure is compared with the other major infrastructure sectors and other major asset classes. The strategic investment implications for institutional investors and renewable energy infrastructure in their portfolios going forward are also highlighted. This includes identifying effective pathways for renewable energy infrastructure exposure by institutional investors. Design/methodology/approach: Using quarterly total returns, the risk-adjusted performance and portfolio diversification benefits of global listed renewable energy infrastructure over Q1:2009–Q4:2022 is assessed. Asset allocation diagrams are used to assess the role of renewable energy infrastructure in a global infrastructure portfolio and in a global mixed-asset portfolio. Findings: Listed renewable energy infrastructure was seen to underperform the other infrastructure sectors and other major asset classes over 2009–2022. While delivering portfolio diversification benefits, no renewable energy infrastructure was seen in the optimal infrastructure portfolio or mixed-asset portfolio. More impressive performance characteristics were seen by nonlisted infrastructure funds over this period. Practical reasons for these results are provided as well as effective pathways going forward are identified for the fuller inclusion of renewable energy infrastructure in institutional investor portfolios. Practical implications: Institutional investors have an important role in supporting reduced global carbon emissions via their investment mandates and asset allocations. Renewable energy infrastructure will be a key asset to assist in the delivery of this important agenda for a greener economy and addressing global warming. Based on this performance analysis, effective pathways are identified for institutional investors of different size assets under management (AUM) to access renewable energy infrastructure. This will see institutional investors embracing critical investment issues as well as environmental and social issues in their investment strategies going forward. Originality/value: This paper is the first published empirical research analysis on the performance of renewable energy infrastructure at a global level. This research enables empirically validated, more informed and practical decision-making by institutional investors in the renewable energy infrastructure space. The ultimate aim of this paper is to articulate the potential strategic role of renewable energy infrastructure as an important infrastructure sector in the institutional real asset investment space and to identify effective pathways to achieve this renewable energy infrastructure exposure, as institutional investors focus on the strategic issues in reducing global carbon emissions in the context of increased global warming. [ABSTRACT FROM AUTHOR]

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The lack of access to clean energy remains one of the major challenges in the global energy sector. Access to clean, sustainable and affordable energy, outlined in the seventh Sustainable Development Goals (SDG 7) of the United Nations, plays a crucial role in advancing health (SDG 3), as unclean cooking energy may endanger people's health by causing air pollution. However, due to endogeneity problems such as reverse causality, the health consequences of environmental pollution caused by unclean fuel usage are difficult to be scientifically and accurately evaluated. This paper aims to systematically assess the health cost of unclean fuel usage based on tackling endogeneity, using the data from Chinese General Social Survey. The ordinary least squares model, ordered regression methods, instrumental variable approach, penalized machine learning methods, placebo test, and mediation models are applied in this research. Analytical results demonstrate that households' unclean fuel use significantly damages people's health. Specifically, the use of dirty fuel leads to an average of about a one-standard-deviation decline in self-rated health, demonstrating its notable negative effect. The findings are robust to a series of robustness and endogeneity tests. The impact mechanism is that unclean fuel usage reduces people's self-rated health through increasing indoor pollution. Meanwhile, the negative effect of dirty fuel use on health has significant heterogeneity among different subgroups. The consequences are more prominent for the vulnerable groups who are female, younger, living in rural areas and older buildings, with lower socio-economic status and uncovered by social security. Therefore, necessary measures should be taken to improve energy infrastructure to make clean cooking energy more affordable and accessible as well as to enhance people's health. Besides, more attention should be paid to the energy needs of the above specific vulnerable groups faced with energy poverty. [ABSTRACT FROM AUTHOR]

Electric power systems face heightened risks from climate change, on top of existing challenges like aging infrastructure, regulatory shifts, and cybersecurity threats. This paper explores how advanced technologies, including smart grids, artificial intelligence (AI), and machine learning, (ML), enhance the resilience of power systems against climate-driven extreme weather events. Drawing insights from resilience theory, the paper presents a state-of-the-art review of the literature on power system resilience, highlighting the escalating vulnerabilities of energy systems to weather-related disruptions. Although utilities currently use technologies like automated meter reading and advanced metering infrastructure to collect vital grid performance data, the lack of strategic collaboration often impedes effective data governance and sharing, thus undermining efficient responses to climate threats. The paper underscores the significance of distributed energy resources, long-duration energy storage, microgrids, and demand-side management. It further illustrates how AI and ML optimize smart grids to support these strategies. Proactive integration of smart grids with advanced technologies could significantly reduce climate-related costs compared to non-adaptive methods. Such proactive grid resilience strategies not only climate-proof energy infrastructure against climatic changes but also herald a modern, placed-based industrial transformation. Climate change exacerbates challenges in our energy systems, from aging infrastructure and a constantly shifting regulatory environment to cybersecurity risks and diversifying energy portfolios. Addressing these issues requires strategic investment in modern infrastructure, particularly smart grids enhanced by advanced technologies like artificial intelligence (AI) and machine learning (ML). These technologies are vital for enhancing power system resilience against climate impacts. Automated systems such as automated meter infrastructure (AMI) and supervisory control and data acquisition (SCADA) provide real-time data crucial for managing extreme weather events. AI and ML contribute to predictive maintenance, preventing failures and blackouts. They also forecast grid loads during severe weather, facilitating proactive power distribution management to prevent blackouts. This comprehensive improvement in situational awareness promotes economic growth in the energy sector and supports sustainable, climate-resilient transformation. AI and ML not only improve energy distribution and efficiency but also promote conservation efforts and ensure reliable energy amidst a changing climate. Collaboration among utility managers, regulators, and governments is key, focusing on data access, verification, and adaptability. Strategies should be tailored to each utility's unique challenges. Moreover, establishing technical standards is critical for enhancing power grid resilience against climate-induced extreme weather events. [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]

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]

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]

The incorporation of net-zero technology into preexisting energy networks is crucial for facilitating the shift toward an ecologically conscious and sustainable energy infrastructure. The primary objective of this integration is to effectively decrease carbon footprints and to provide a comprehensive understanding of the current approaches and trends related to the design and management frameworks of integrated energy networks. The initial section of this study establishes the foundation for a comprehensive examination of the particular challenges associated with decarbonization in the strategic and operational aspects of integrated energy networks. The subsequent analysis proceeds to elucidate the fundamental framework and technological architecture upon which these energy networks are constructed. This provides significant insights into the operational complexity and efficacy of the system. In addition, the paper provides a concise examination of prominent frameworks and alternative approaches that tackle the issue of low-carbon design and administration. The degree of accuracy facilitates individuals when selecting systems that align with the specific requirements of unique circumstances. Furthermore, this study provides explicit suggestions for future research based on an examination of the distinct attributes and framework of integrated energy networks. The anticipated outcome of implementing these recommendations is to enable the advancement of sustainable development and expedite the shift toward energy infrastructure with reduced carbon emissions. This will make a significant contribution to the collaborative endeavor of mitigating climate change and fostering a sustainable energy future. This study further elucidates the significant contribution of integrated energy networks in addressing climate change and enhancing energy efficiency. It achieves this by synthesizing a complete range of concepts sourced from many academic papers, industry reports, and case studies. This statement offers an examination of the multifaceted technological, legislative, and planning factors that contribute to the attainment of net-zero objectives. [ABSTRACT FROM AUTHOR]

The global electricity network and natural gas have been developed worldwide. So far, various investigations in relation to energy infrastructures have been performed; however, the combination of these systems has not been examined much. For this reason, electric and thermal loads have been interconnected by CHP units, and the combined study of power and heat has helped the operator to propose a more optimal structure for energy management. Therefore, integrating different energy carriers and using the benefits of each one can increase the efficiency and reliability along with optimizing system performance. Such a capability in structure and operation requires a comprehensive framework to describe the effects of combining different energy carriers on the economic and environmental indicators of energy systems. In this paper, the microgrid has been modeled as an energy hub in order to combine different energy carriers and perform conversions in them to provide the optimal electric and thermal load required by the consumer. This structure has been created by managing the incoming carriers of gas, electricity and renewable energy and managing their conversion and storage in order to minimize the cost of energy supply and environmental pollutants. In addition to managing generation units, in order to improve the performance of the microgrid and help the operator of the microgrid, a responsive load management strategy and charging and discharging of electric vehicles have been proposed. Epsilon constraints and fuzzy decision-making methods have been used to solve this issue. The results of the study indicated that in the optimal state with the application of responsive loads, the total cost of operation has been reduced by more than 6% and the cost of environmental pollutants has been mitigated by about 13%. [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]

The reliable prediction of solar energy production and surplus is crucial for the stability of the electricity grid and effective energy distribution, particularly during peak consumption periods. Encouraging solar adoption by customers is also important despite fluctuations in solar energy generation. This paper addresses the need for an intelligent surplus solar energy prediction model, referred to as the Green Model, which aims to accurately predict surplus electrical energy that can be returned to the distribution grid. The Green Model utilizes a combination of a developed long short-term memory (LSTM) neural network and a novel optimization technique called deterministic selection network by gain sharing knowledge (DSN-GSK). The DSN-GSK optimizes the structure of LSTM by determining the optimal number of hidden layers, nodes in each layer, biases, weights, and activation functions based on the most important features that represent the relationship between generated solar energy and weather factors. The Green Model was evaluated and analysed, demonstrating high accuracy in the short-term prediction of surplus electrical energy with a minimal percentage of error. The model shows promising prospects for the development of returned electrical energy prediction. The main novelty of this paper lies in the development of the Green Model, which combines LSTM and DSN-GSK to enhance the accuracy of surplus solar energy prediction. The benefits of the Green Model include improved stability and efficiency of the electricity grid, effective utilization of renewable energy sources, and the reduction of negative environmental impacts. The contributions of this paper include advancing the field of intelligent energy prediction, optimizing the structure of LSTM, and providing valuable insights for the integration of renewable energy into the existing energy infrastructure. [ABSTRACT FROM AUTHOR]

Woody biomass has gained increased attention as a source of renewable energy. However, its categorization as a sustainable source of energy remains controversial, as its carbon neutrality depends on its end use, moisture content, bulk density, and the distance between the source of biomass and its end use. Due to these mediating factors, policies largely shape its sustainability and ability to mitigate emissions. This paper organizes and evaluates the current state of research through a systematic review of global literature from 2011 to 2021 (n = 345) on the governance of the production, transportation, sale, and use of woody biomass for energy. Peer-reviewed literature emphasizes the role of woody biomass as a decentralized energy source for individual households and communities, focusing on its harvest, transport, and localized energy conversion. Policies primarily address land management and energy infrastructure rather than direct emissions reduction. Research gaps in policy within the Global South underscore the need to examine biomass regulation in regions with limited energy diversity. The key factors that drive the sustainable uptake of woody biomass include strict sustainability criteria, fiscal incentives, technological development, and wood utilization from across its value chain. Effective policy implementation increases rural employment, boosts rural economies, provides energy security to remote areas, improves overall environmental sustainability, reduces emissions, and improves land management practices. Our systematic review reveals that future research should focus on improving conversion efficiencies in small-scale systems, reducing emissions in the international trade of woody biomass, and using the wood value chain to increase the profitability of bioenergy products. [ABSTRACT FROM AUTHOR]

This paper examines the financing of green energy initiatives as a critical element in strengthening Ukraine's energy security, especially in the context of post-war reconstruction and the need for sustainable and resilient energy infrastructure. The study aims to assess the potential and challenges of investing in green energy in Ukraine, considering the destruction caused by Russian military actions in the winter of 2022- 2023, and the need for recovery based on sustainable models. In this regard, the obtained results emphasize the importance of creating a reliable and decarbonized energy sector, driven by both domestic needs and international cooperation with the EU and other partners. The analysis shows that despite strong support for the green energy transition, the development of the sector is hindered by the high capital intensity required for green technologies, which are often not competitive without government subsidies. This requires a careful balance between innovation and commercial viability of green energy projects, highlighting the need for public and private investments in technologies that can compete with traditional sources of energy in the long term and developing new financing tools for Ukraine. The conclusions indicate that a multifaceted approach is needed to ensure Ukraine's energy future and minimize risks. Such an approach should include policy reforms, strategic investments in proven green technologies, and fostering partnerships to bridge the commercialization gap. Policymakers face the dual challenge of accelerating the energy transition while managing financial constraints exacerbated by military spending, highlighting the trade-off between rapid development and the risks associated with financing innovation. Overall, this study contributes to the understanding of how green energy financing mechanisms can enhance Ukraine's energy security, suggesting broader implications for policy, investment, and technological innovation in the context of Ukraine's post-war recovery and future resilience. [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]

As energy systems transition from fossil fuels to renewable sources, energy infrastructure will become a predominant land use, especially in rural areas. This poses a challenge for municipalities who need to adapt land use planning frameworks to more renewable energy. Using plan quality evaluation, this paper assesses how 57 rural official plans in Manitoba (Canada) are attempting to integrate energy planning. Consideration of energy within plans is poor, especially for implementation mechanisms and fact base. While rural communities are the forefront of the energy transition, existing land use planning frameworks are maladapted to enable it. [ABSTRACT FROM AUTHOR]

With advent of Internet of Things (IoT) an exponential growth has been observed in recent times towards the use of fifth generation (5G) network to share data among anything and even everything around connected in billions. The exchange of large amount of data by these devices or objects accumulates network overhead in the IoT infrastructure in terms of energy, routing, battery charge, data rate, packet delivery/loss rate, availability, interoperability, congestion, scalability, cost and security. Hence it is highly essential to project optimal solutions to uphold thereby the quality of service (QoS) in available network. This study provides a thorough literature survey of diverse optimization techniques in IoT aided wireless networks like Mobile Ad-hoc NETwork (MANET) driven Internet of Mobile Things (IoMobT), Vehicular Ad-hoc NETwork (VANET) driven Internet of Vehicles (IoV), Flying Ad-hoc NETwork (FANET) driven Internet of Flying Things (IoF), Robot Ad-hoc NETwork (RANET) enabled Internet of Robots (IoR), Ship Ad-hoc NETwork (SANET) driven Internet of Ships (IoS) and Underwater or Underground Ad-hoc NETwork (UANET) in Internet of Underwater or Underground Things (IoU). It categorizes papers based on the issues resolved by the examined works and optimization strategies employed and then it contrasts and condenses the salient characteristics of each kind of publication. It also even sketches a preview of IoT along with its evolving trends and cutting-edge-solutions for improving QoS. Our survey attempts to give readers a better grasp of the principles behind various computing models and to examine QoS network optimization strategies across a range of IoT models. [ABSTRACT FROM AUTHOR]

Renewable energy infrastructures, such as wind and solar farms, require land on which they can be deployed. While politics and conflicts over accessing land for renewables are well documented, the role, conditions and potential agency of landownership have been often overlooked or oversimplified as a powerful terrain in the field of renewables development. In this paper, we explore the relationship between landed property and community renewable energy projects. In particular, we focus on how landed property variously influences the development modes of renewables by acting as a mediator, barrier and enabler for different types of wind energy projects. We show how this takes place through appropriation of rents in processes of assetisation and value grabbing by landowners. In this way, value grabbing acts as a vital intermediary process to understand green grabbing and wider processes of capital accumulation through renewables. We draw on insights from the Netherlands and Scotland to illuminate different mechanisms, social and historical conditions, and policies through which landed property constrains or enables community wind energy projects. The paper finishes by sketching out some alternative ways of allocating land for the deployment of renewable energy projects, which could help shift the balance of power in favour of community energy developments. [ABSTRACT FROM AUTHOR]

Helicopters provide aerial services such as firefighting, medical transport, agriculture, and construction for critical industries that form the backbone of modern society. These "aerial work" applications comprise the majority of the current market for civilian helicopters and include a diverse set of mission types and flight profiles; in many cases, aerial work applications are meeting growing needs driven by the climate crisis and energy transition. Through a series of more than 180 interviews with operators, pilots, and users across helicopter aerial work, this paper--the largest contemporary study of its kind -- surveys the challenges that the industry sees for itself. Part I analyzes and summarizes our original primary source data to provide both qualitative and quantitative assessments of the needs of this community. Part II presents a case study for aerial firefighting, where a growing demand driven by record-breaking climatic changes is straining the existing air crews, aircraft fleet, and firefighting technology. Many issues identified in firefighting are endemic problems that beset other neighboring applications within aerial work such as public services, energy infrastructure, construction, and agriculture; technologies that have the potential to have a significant impact on firefighting are discussed. Part III is an analysis of technology and how it might better meet the needs of helicopter aerial work. We identify characteristics such as compatibility, reliability, and application specialization that are valued by helicopter aerial work customers and operators. In the backdrop of unprecedented venture capital investment and technology development in new types of vertical takeoff and landing aircraft for AAM, this paper's core finding is that the needs of helicopter aerial work are not being met: a venture capital culture prioritizes innovation that can create new markets over solving challenges in existing ones. Innovation for commercial air transport missions that operate under different market, environmental, and operational conditions does not "trickle down" to aerial work. We identify a need for increased collaboration between technologists and the aerial work community and for a more thoughtful approach towards investment and development to meet the growing challenges of the industry. [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]

Copyright of Przeglad Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

Purpose: This paper analyzes the European Bank for Reconstruction and Development's (EBRD) strategic financing roles in Kosovo from 2013 to 2020, focusing on economic impacts and developmental progress. Methodology: Employing a quantitative and comparative approach, this study utilizes secondary data analysis, supported by statistical tools in Microsoft Excel, to evaluate the effectiveness of EBRD investments in various sectors within Kosovo. Results: The findings reveal significant EBRD investments, primarily in SMEs and infrastructure, contributing to competitive gains and sustainable development. The study details the volume of investments and their distribution across different sectors, highlighting substantial impacts on employment and green energy initiatives. Theoretical Contribution: This research enriches the literature on international financial institutions' roles in post-conflict economic development, providing a nuanced understanding of the EBRD's strategic priorities and operational outcomes in transitional economies. Practical Implications: The study offers policymakers and development agencies insights into practical strategies for leveraging international finance for economic growth and sustainability. Recommendations are provided to enhance the focus on renewable energy and infrastructure, aligning with global sustainable development goals. [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]

The rapid growth of service-oriented and cloud computing has created large-scale data centres worldwide.Modern data centres’ operating costs mostly come from back-end cloud infrastructure and energy consumption. In cloud computing, extensive communication resources are required.Moreover, cloud applications requiremore bandwidth to transfer large amounts of data to satisfy end-user requirements. It is also essential that no communication source can cause congestion or bag loss owing to unnecessary switching buffers. This paper proposes a novel Energy and Communication (EC) aware scheduling (EC-scheduler) algorithm for green cloud computing, which optimizes data centre energy consumption and traffic load. The primary goal of the proposed EC-scheduler is to assign user applications to cloud data centre resources with minimal utilization of data centres. We first introduce a Multi-Objective Leader Salp Swarm (MLSS) algorithm for task sorting, which ensures traffic load balancing, and then an Emotional Artificial Neural Network (EANN) for efficient resource allocation. EC-scheduler schedules cloud user requirements to the cloud server by optimizing both energy and communication delay, which supports the lower emission of carbon dioxide by the cloud server system, enabling a green, unalloyed environment. We tested the proposed plan and existing cloud scheduling methods using the GreenCloud simulator to analyze the efficiency of optimizing data centre energy and other schedulermetrics. The EC-scheduler parameters PowerUsage Effectiveness (PUE), Data Centre Energy Productivity (DCEP), Throughput, Average Execution Time (AET), Energy Consumption, and Makespan showed up to 26.738%, 37.59%, 50%, 4.34%, 34.2%, and 33.54% higher efficiency, respectively, than existing state of the art schedulers concerning number of user applications and number of user requests. [ABSTRACT FROM AUTHOR]

Urban and regional development is indispensable from energy systems that function in a sustainable and resilient manner. The generation of renewable energy has seen significant upturn in the last decade. Renewables can be exploited to meet the global energy needs and climate change mitigation goals. Therefore, development of urban and regional energy systems must take into account the possibilities and challenges posed by the increasing penetration of the renewable. The achievement of goals of the energy system in the context of transition to low-carbon energy society rises numerous complex decisions over development of infrastructure and technologies. Although renewable energy devices generate clean energy, they also change landscape. The term of energy-scape encourages discussion about interactions between the energy system and the environment, and other ecosystem services at local level. The paper reviews previous studies analysing energy-scape elements and provides the insights towards the transition to low-carbon energy and low-carbon society in general. The systematic literature review allows clearly outlining the problem and gives reliable background for further studies. The main contribution of the article to the existing literature is the creation of framework for the analysis and assessment of new renewable energy technologies installation and infrastructure. The presented framework can be applied for all renewable energy technologies and infrastructure in both urban and rural areas and allows to attain a decision acceptable to the local community. [ABSTRACT FROM AUTHOR]

Copyright of Oltenia, Studii si Comunicari Seria Stiintele Naturii is the property of Museum of Oltenia Craiova and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

The object of research is the energy supply company and the processes of generation and supply of electric energy. The paper examines the problems of building mathematical models for forecasting the operation of a critical infrastructure object in the conditions of a changing security environment, characterized by unpredictability, the presence of uncertainties of various types, the appearance of new threats, their combinations, changes in the form, duration, nature of their influence. In the work, the main attention is paid to the study of the functioning of critical infrastructure in the field of energy supply. Based on the study of the functioning of the energy company system, methods of dealing with uncertainties at the stage of data preparation for analysis and during the preliminary construction of models are presented, in particular, statistical and probabilistic approaches, modeling of the studied processes, alternative methods of estimating model parameters, etc. The complexity of preparing the input data set is related to the fact that it is necessary to ensure the representativeness and variability of the data sets, given that a significant number of factors must be included in the model according to the requirements of regulatory documents, which can lead to multicollinearity of the input variables. The paper proposes an analytical toolkit based on the use of mathematical models and their combinations, intended for use in specialized decision support systems. In the course of the research, a number of numerical experiments were conducted, in which the proposed methodology was worked out on the materials of the enterprise – the object of the critical infrastructure of the energy sector. SAS Energy Forecasting software was used to build the models. The best forecasting results are obtained using generalized linear models (GLM), in particular the GLM model in the form of ARIMAX (a moving average autoregressive model that includes an integrated trend component and external regressors). The proposals presented in the work will allow to increase the efficiency of the functioning of the energy sector, including the determination of the goals, tasks and benchmarks of its operation in regular mode for certain periods of time, as well as in the field of development of universal and special mechanisms for ensuring stability in the mode of response to threats and critical situations. [ABSTRACT FROM AUTHOR]

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]

High performance steels, such as stainless steels, have many desirable characteristics that warrant their use in various sectors, including infrastructure and energy applications. This paper is concerned with two of such applications: (i) the use of stainless steel for large‐scale liquid hydrogen storage tanks, which is a requirement for the future hydrogen energy network, and (ii) the use of stainless steel in steel‐framed buildings to enhance their robustness under extreme loading conditions. The paper begins with a discussion of the technical challenges associated with the material behaviour of stainless steel storage tanks under extreme temperature and pressure conditions. It presents and discusses the results of a pilot experimental programme that investigates the mechanical behaviour of stainless steel 304 L material under cryogenic 20 k hydrogen environment. Next, to demonstrate the benefits of the strategic use of stainless steel in the key connection parts of steel‐framed structures, the paper presents the setup for a new test programme that investigates the behaviour of stainless steel beam‐to‐column connections, using A4‐70 bolts and EN1.4301 plates, under a column removal scenario. The numerical modelling prediction results of the specimens are presented, and comparisons with carbon steel counterparts are made and discussed. [ABSTRACT FROM AUTHOR]

South Africa's has been battling with energy crisis for many years, and with the ongoing power cuts, the nation has been plunged into darkness experienced almost every day in major cities such as Johannesburg. This paper conceptualises and positions the role of electrical and mechanical energy in food processing and preparation within South Africa's low-income households. The study aims to understand how households' choices and decisions made around food access, preparation and storage are affected by energy infrastructure. Urban studies on informality show that energy is a key input in food processing, preparation, and storage. This study focused on the intersection of infrastructure systems and sought to understand the energy needs and livelihoods strategies of South Africa's low-income households. A secondary focus of this study was on indigent energy policies that supports the provision and access of energy services to indigent households in South Africa. The study adopted a case study approach, low-income households' energy needs in Alexandra township, Johannesburg. This study utilised in-depth interviews and policy document reviews. Data was analysed using correlation and cross-tabulation methods. Findings reveal that measures adopted by the city authorities in the provisioning and access to infrastructure are largely fragmented and uncoordinated. [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]

The evolution of the smart grid has enabled residential users to manage the ever-growing energy demand in an efficient manner. The smart grid plays an important role in managing this huge energy demand of residential households. A home energy management system enhances the efficiency of the energy infrastructure of smart homes and provides an opportunity for residential users to optimize their energy consumption. Smart homes contribute significantly to reducing electricity consumption costs by scheduling domestic appliances effectively. This residential appliance scheduling problem is the motivation to find an optimal appliance schedule for users that could balance the load profile of the home and helps in minimizing electricity cost (EC) and peak-to-average ratio (PAR). In this paper, we have focused on appliance scheduling on the consumer side. Two novel home energy management models are proposed using multiple scheduling options. The residential appliance scheduling problem is formulated using the multiple knapsack technique. Serial and parallel scheduling algorithms of home appliances namely MKSI (Multiple knapsacks with serial implementation) and MKPI (Multiple knapsacks with parallel implementation) are proposed to reduce electricity cost and PAR. Price-based demand response techniques are incorporated to shift appliances from peak hours to off-peak hours to optimize energy consumption. The proposed algorithms are tested on real-time datasets and evaluated based on time of use pricing tariff and critical peak pricing. The performance of both the algorithms is compared with the unscheduled scenario and existing algorithm. Simulations show that both proposed algorithms are efficient methods for home energy management to minimize PAR and electricity bills of consumers. The proposed MKSI algorithm achieves cost reduction of 20.26% and 42.53% for TOU and CPP, respectively as compared to the unscheduled scenario while PAR is reduced by 45.07% and 39.51% for TOU and CPP, respectively. The proposed MKPI algorithm achieves 22.33% and 46.36% cost reduction compared to the unscheduled case for TOU and CPP while the PAR ratio is reduced by 46.47% and 41.16% for TOU and CPP respectively. [ABSTRACT FROM AUTHOR]

In developing countries, electricity and water supply are strategic challenges arising from growing demand due to increasing populations and modernization of households. This review paper focuses on Iran as a dryland country that has strived to maintain water resources, generate electricity for domestic purposes and even export electricity. It addresses a scientific gap in the existing literature that has paid limited attention to the intertwined geographical, geopolitical, infrastructure and workforce elements in Iran's development of electricity generation. This review also seeks to link domestic energy production to politically focused regional considerations. It highlights the factors and policies enabling Iran to export its generated electricity. Water conservation and energy generation/electricity can be viewed as complementary when considered within the scenario of hydropower which depends on the presence of large dams. Iran's emphasis on economic advancement in earlier years involved the development of water and energy infrastructure which, decades later, provided opportunities for exporting electricity to neighboring countries. The earlier sole focus on economic development has gradually shifted toward a greater concern for sustainable economic development. Both environmental and political issues are relevant if Iran wants to continue maintaining its water resources, generating hydropower, and exporting its electricity in the region [ABSTRACT FROM AUTHOR]

The failure of a 144‐m‐high lava‐dam waterfall on the Río Coca, Ecuador, in February 2020 initiated a catastrophic watershed reset—regressive erosion upstream and a massive sediment pulse downstream—as the river evolves towards a new equilibrium grade. The evolution of this river corridor after a sudden base‐level fall embodies the "complex response" concepts long understood through laboratory experiments, numerical modelling and smaller‐scale field studies, but that have not been observed in the field before on this scale. This paper presents geomorphic and geotechnical data to characterize the evolution of the Río Coca since 2020. In the three years after the lava‐dam failure, the erosion front migrated almost 13 km upstream along the mainstem river and triggered secondary headcuts that began migrating up tributaries. Erosion of the mainstem and tributary valleys generated a sediment pulse estimated to be 277 million m3 and ~500 million tonnes (Mt) over three years, depositing sediment tens of meters thick over tens of kilometres downstream from the former waterfall. This sediment pulse is one of the largest in modern times, comparable to the annual sediment load of a major continent‐draining river but with orders‐of‐magnitude greater sediment yield. Geomorphic adjustment of the Río Coca represents a highly unusual natural disaster threatening life, property, water quality, the regional economy, major infrastructure and energy security. However, this event also provides a rare opportunity to learn how a large autogenic watershed disturbance and recovery evolve, with important lessons for interpreting the sedimentary record of volcanic landscapes. [ABSTRACT FROM AUTHOR]

This paper discusses the future challenges of strategic spatial planning in Europe in the coming decades. The paper argues that one of the core challenges for strategic spatial planning is to regain its political legitimacy. Strategic spatial planning has increasingly lost its political support after the global financial crisis in 2007–2008 and a decade of austerity policies. Strategic spatial planning must make itself relevant again by addressing the most prominent challenges for contemporary urban areas, such as the current energy crisis. The energy crisis has demonstrated the need for an even faster transition to renewable energy sources, which requires large areas for energy infrastructures on land. The paper argues that strategic spatial planning could play an important future role in supporting the sustainable energy transition by identifying appropriate spaces of production and building support for such production facilities among local communities. [ABSTRACT FROM AUTHOR]