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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]

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]

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]

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]

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]

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]

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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]

This paper presents a detailed techno-economic review and assessment of a hydrogen refueling station (HRS) powered by a grid-connected photovoltaic (PV) system to address the issues of carbon emissions and energy sustainability in transportation. In the study, the HRS system with 1, 3 and 5 MW PV installed capacity for Ankara, the capital city of Türkiye, is considered for different system lifetimes. In the proposed HRS, on-site hydrogen production is achieved through anion exchange membrane water electrolysis (AEMWE) using a grid-connected PV system, and the produced hydrogen is stored in a cascaded storage system and is utilized at the HRS station. In order to evaluate the cost competitiveness and economic viability of the designed HRS system, the levelized cost of hydrogen (LCOH) is determined by considering the initial investment costs, operating expenses and potential revenue streams. The results show that the HRS capacity, PV installed capacity and system lifetime significantly impact the LCOH. The technoeconomic analysis results show that the best system configuration was determined as 8.54 €/kg H 2 in the 20-year long term refueling scenario for a 5 MW installed PV capacity with a daily refueling capacity of 170 kg H 2. This study contributes to the development of sustainable energy infrastructure by providing a comprehensive framework for the design, calculation and economic evaluation of PV-integrated hydrogen refueling stations. The results provide valuable information for policymakers, industry stakeholders, and researchers to help achieve a carbon-neutral transportation sector and promote energy sustainability. • PV integrated onsite hydrogen refueling station is proposed. • Techno-economic evaluation of the HRS was conducted. • The lowest levelized cost of hydrogen (LCOH) was obtained as 8.54 €/kg H 2. • HRS infrastructure required to support hydrogen vehicles through the carbon zero transition. [ABSTRACT FROM AUTHOR]

The competitiveness of hydrogen as a sustainable energy carrier depends greatly on its transportation and storage costs. Liquefying hydrogen offers advantages such as enhanced purity, versatility, and higher density, yet current industrial liquefaction processes face efficiency and cost challenges. Although various large-scale and efficient liquefaction concepts exist in the literature, they often overlook the economic and technical viability of such plants. Here, we addresses this issue by establishing a framework for modeling a large-scale hydrogen liquefaction concept and conducting both technical and economic assessments, with a specific focus on 125 tonnes per day (TPD) high-pressure hydrogen Claude-cycle concept. The technical analysis involves preliminary designs of key process components, while the economic assessment utilizes Aspen Process Economic Analyzer. Our findings indicate that at an electricity price of €0.1/kWh, the Claude-cycle liquefier concept yields a specific liquefaction cost (SLC) of €1.55/kg LH 2 . A sensitivity analysis was performed, which shows that electricity price has a significant influence on the economics. Further investigation on the compressors design shows that incorporating high-speed centrifugal compressors could reduce the SLC by 5.42% and potentially more. Scaling up to 250 and 500 TPD reveals further cost improvements, while cost projections indicate substantial declines as the technology matures. Ultimately, this paper presents novel cost-scaling and experience curves of hydrogen liquefaction technology, demonstrating the compelling economic viability of integrating large-scale hydrogen liquefaction into sustainable energy infrastructure. [Display omitted] • A process model of a large-scale Claude-cycle hydrogen liquefaction plant has been developed for both technical assessment and economic analysis. • The technical evaluation primarily centers on the preliminary design of key process equipment, such as compressors, turbo-expanders, and heat exchangers. • The techno-economic assessment is performed based on the process simulation and equipment preliminary design. • Capital cost estimation is carried out using the Aspen Process Economics Analyzer. • These cost estimations serve as the basis for predicting cost and experience curves of hydrogen liquefaction technology. [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]

The paper looks into natural gas as a factor influencing the dynamics of the energy market in Eastern Europe. The energy market as such is in fact the correlation between various interrelated markets which have different effects on the final consumers' prices and on the inflation. The Eastern European energy market is currently one of the fastest-growing energy markets. It consists of resource-rich and transit countries (Belarus, Bulgaria, Czech Republic, Hungary, Poland, Moldova, Romania, Russia, Slovakia and Ukraine) with a population of roughly 291 million people, that contributes significantly to the world's energy consumption and security. The dynamics of this market depend on the new infrastructure for transiting and storing natural gas as well as the big undergoing investments in renewable energy infrastructure. [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]

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]

As the global market develops for green hydrogen and ammonia derived from renewable electricity, the bulk transmission of hydrogen and ammonia from production areas to demand-intensive consumption areas will increase. Repurposing existing infrastructure may be economically and technically feasible, but increases in supply and demand will necessitate new developments. Bulk transmission of hydrogen and ammonia may be effected by dedicated pipelines or liquefied fuel tankers. Transmission of electricity using HVDC lines to directly power electrolysers producing hydrogen near the demand markets is another option. This paper presents and validates detailed cost models for newly-built dedicated offshore transmission methods for green hydrogen and ammonia and carries out a techno-economic comparison over a range of transmission distances and production volumes. New pipelines are economical for short distances, while new HVDC interconnectors are suited to medium-large transmission capacities over a wide range of distances, and liquefied gas tankers are best for long distances. [Display omitted] • Future hydrogen and ammonia markets will require new-build long-distance transmission. • Energy may be transmitted in dedicated pipelines, liquid tankers or by HVDC lines. • Levelised cost of transmission depends on the transferred quantity and the distance. • Pipelines are the best option over short distances for hydrogen and ammonia. • HVDC has lowest cost for medium distances, tankers are suitable for long distances. [ABSTRACT FROM AUTHOR]

At present, two subsidy policies, which are based on electric vehicle (EV) consumers and EV charging station firms, have been widely implemented in different areas in China to promote EV adoption. However, the effectiveness of subsidy policies is significantly influenced by the indirect network and herd effects, depicting the positive impacts of the numbers of energy infrastructure firms and the sales of vehicles on consumers' utilities, respectively. Taking the aforementioned effects into consideration, this study examines the optimal subsidy policies by developing a Stackelberg game model. The game model analyzes the interaction and decisions of multiple stakeholders (i.e., consumers, energy infrastructure firms, EV and gasoline vehicle manufacturers, and the government). Interestingly, we find that a stronger herd effect will promote EV sales when the unit production cost of EVs is low; however, it will hinder EV sales when the unit production cost is high. Besides, we compare the effectiveness of the two subsidy policies for promoting EV adoption, reducing environmental impacts, and increasing the social welfare. Findings show that the effectiveness of subsidy policies highly depends on the extent of the indirect network and herd effects. Specifically, compared with EV consumers-based subsidy policy, EV charging station firms-based subsidy policy will be more effective in only two conditions: a weak indirect network effect and a strong herd effect. Otherwise, the EV consumers-based subsidy policy will be more effective. The findings of the paper are helpful in enhancing the effectiveness of subsidy policy in China. • Government subsidy cannot always promote electric vehicle adoption. • The indirect network and herd effects affect the effectiveness of subsidy policy. • A stronger herd effect will not always promote electric vehicle sales. • Either consumers or charging station investors can be the best subsidy object. [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]

Energy security and environmental concerns are driving a lot of research projects to improve energy efficiency, make the energy infrastructure less stressed, and cut carbon dioxide (CO2) emissions. One research goal is to increase the effectiveness of building heating applications using cutting-edge technologies like solar collectors and heat pumps. Another study technique uses phase change materials (PCMs), which have high energy storage densities. There still needs to be a thorough analysis of how these two research methods, namely how PCM is used to heat buildings, fit together. A thorough explanation of PCM application in buildings, specifically in walls, floors, ceilings, and glazed sections, and the critical PCM properties have been included in this article. This paper gave a summary of the research done for different applications, including the types of PCM, the forms of PCM encapsulation, and the types of PCM units used in different applications. This was done so that PCM can be used effectively in building applications. By summarizing and talking about the research methods used in different applications, we can learn more about the study's possibilities and limits. From the study, authors conclude that the selection of appropriate PCM for a particular application requires careful consideration. The appropriate thermal conductivity, melting temperature ranges, coherence with building materials, and durability over time are a few factors that must be taken into account. Compatibility issues may arise when PCMs come into contact with other components or construction materials, which may lead to leakage or inadequate performance. Scholars can use the important conclusions and suggestions for future research on these applications to help them with their work. A list of recommendations for future work that can increase the use of PCMs in building applications include the improvement in low thermal conductivity and boost system efficiency, PCMs' heat transfer properties can be improved, or heat transfer enhancement methods such as fins or heat pipes can be used. The next generation of studies aims to develop PCMs with enhanced robustness, durability over time, and little degradation following repetitive temperature cycling. Making PCM-based solutions commercially viable for various building projects requires robustness as well as inexpensive manufacturing procedures. [ABSTRACT FROM AUTHOR]

The transition to a low-carbon energy system can be depicted as a "great reconfiguration" from a socio-technical perspective that carries the risk of impact shifts. Electrification with the objective of achieving rapidly deep decarbonisation must be accompanied by effective efficiency and flexibility measures. Hydrogen can be a preferred option in the decarbonisation process where electrification of end-uses is difficult or impractical as well as for long-term storage in energy infrastructure characterised by a large penetration of renewable energy sources. Notwithstanding the current uncertainties regarding costs, environmental impact and the inherent difficulties of increasing rapidly supply capacity, hydrogen can represent a solution to be used in multi-energy systems with combined heat and power (CHP), in particular in urban energy districts. In fact, while achieving carbon savings with natural gas fuelled CHP is not possible when low grid carbon intensity factors are present, it may still be possible to use it to provide flexibility services and to reduce emissions further with switch from natural gas to hydrogen. In this paper, a commercially established urban district energy scheme located in Southampton (United Kingdom) is analysed with the goal of exploring potential variations in its energy demand. The study proposes the use of scalable data-driven methods and probabilistic simulation to generate seasonal energy demand patterns representing the potential short-term and long-term evolution of the energy district. • Hydrogen role in the transition to low carbon energy systems for urban energy district. • Data-driven urban energy modelling using regression-based approaches. • Probabilistic modelling of energy demand in terms of electricity and fuels. • Climate change impact and energy efficiency measures accounting. • Seasonal variations of energy demand patterns from short-term to long-term scenarios. [ABSTRACT FROM AUTHOR]

In recent years, sustainable development has become a challenge for many societies due to natural or other disruptive events, which have disrupted economic, environmental, and energy infrastructure growth. Developing hydrogen energy infrastructure is crucial for sustainable development because of its numerous benefits over conventional energy sources. However, the complexity of hydrogen energy infrastructure, including production, utilization, and storage stages, requires accounting for potential vulnerabilities. Therefore, resilience needs to be considered along with sustainable development. This paper proposes a decision-making framework to evaluate the resilience of hydrogen energy infrastructure by integrating resilience indicators and sustainability contributing factors. A holistic taxonomy of resilience performance is first developed, followed by a qualitative resilience assessment framework using a novel Intuitionistic fuzzy Weighted Influence Nonlinear Gauge System (IFWINGS). The results highlighted that Regulation and legislation, Government preparation, and Crisis response budget are the most critical resilience indicators in the understudy hydrogen energy infrastructure. A comparative case study demonstrates the practicality, capability, and effectiveness of the proposed approach. The results suggest that the proposed model can be used for resilience assessment in other areas. • A Holistic taxonomy of resilience is proposed for hydrogen infrastructure. • A Novel IFWINGS is proposed for advanced qualitative resilience assessment. • Importance of regulation, government preparation, and crisis response budget are discussed. • A Practical and effective application on a real hybrid wind-hydrogen power plant is presented. • Framework provides a tool for promoting sustainable development. [ABSTRACT FROM AUTHOR]

[Display omitted] • A comprehensive framework for analysing embodied carbon in TBM tunnelling. • Evaluate module-based carbon outputs with functional units via BIM-driven platform. • Baseline surveys for segmental lining designs and carbon reduction strategies. • Establish correlations between geotechnical parameters and TBM carbon emissions. • Identify limitations of current assessment methods suggesting a holistic framework. Alongside the transition towards sustainable and renewable infrastructure and energy production, tunnelling projects that adopt tunnel boring machines (TBM) continue to increase in size and complexity. Life Cycle Assessment (LCA) methodologies have a significant impact on the Architecture, Engineering and Construction (AEC) industry, with a shift in focus to cost and carbon management across the infrastructure lifecycle through the use of digitalisation techniques and sustainability rating systems. This paper aims to develop a systematic framework to enhance the sustainability of underground infrastructure in the early design and construction stages, aiming for "build clever and efficiently". This framework integrates digitalisation, carbon assessment standards, numerical modelling, and optimisation techniques to assess carbon emissions and establish benchmarks for construction products and processes. The approach uses parametric models to define tunnelling-related entities such as geological formations, TBM, and segments, designed with dimensional constraints that allow for adaptive modelling and interactions. Enabled by building information modelling (BIM) through parametric models enriched with domain properties, module-based carbon accounting is adopted to evaluate the footprint of material- and asset-level key emitters with functional units. Leveraging established databases, baselines for segmental lining designs and carbon reduction strategies are established. Through project-driven case studies, the correlations among geotechnical conditions, tunnel dimensions, and TBM operating parameters are developed to quantify TBM carbon emissions. A prototype programme demonstrates the framework's application on typical metro and road tunnels at different levels of details (LoD). This paper serves as a guideline for conducting embodied carbon assessments specifically tailored to TBM tunnelling, acknowledging the substantial contribution of the TBM construction process, which is controlled by geotechnical conditions. [ABSTRACT FROM AUTHOR]

The evaluation of communities' vulnerability to prolonged power outages offers valuable insights for prioritizing improvements in infrastructure resilience, thereby alleviating societal consequences. This study proposes a data-driven approach aiming at developing a Social Vulnerability Index (SoVI) to prolonged power outages leveraging three county-level datasets in California including (1) demographic features, (2) power outage factors, and (3) backup power factors. Furthermore, the study conducts a sensitivity analysis on three distinct datasets under two scenarios (Scenario 1: the current SoVI in 2022, Scenario 2: the prediction of SoVI in the year 2030). The results of Scenario 1 indicate that the counties with more affected customers, the number of power outages, and less education attainment tend to be more vulnerable to power outages in 2022. Scenario 1 reveals that the number of affected customers and power outages are the primary features influencing around 29% and 18% of counties, while educational attainment, public Electric Vehicles (EVs) chargers, and homes with rooftop photovoltaic (PV) substantially impact approximately 32%, 11%, and 8% of counties, respectively. However, in Scenario 2, crucial factors affecting the anticipated SoVI in 2030 include public EV chargers, houses with rooftop PV, power outages, and adults living alone. In contrast to Scenario 1, the prevalence of adults living alone has emerged as a notable factor impacting SoVI in 2030, while both scenarios underscore the pivotal role of EV chargers in influencing SoVI concerning power outages. The proposed SoVI facilitates informed policy decisions and infrastructure improvements in energy resilience, resource allocation, and disaster preparedness, contributing valuable insights for targeted interventions in these domains. • A data-driven approach was proposed to quantify the social vulnerability index (SoVI) to power outages. • This paper applies Principal Component Analysis (PCA) to identify the most correlated features from county-level datasets. • The paper conducts a sensitivity analysis to predict SoVI in2030 and evaluate how counties' dynamics change over time. • This paper provides insights into how policymakers can reduce the social vulnerability to power outages in California. [ABSTRACT FROM AUTHOR]

Pathways to decarbonisation are commonly explored by government and industry through the use of energy system models. However, such models rarely consider where new energy infrastructure might be located. This is problematic as the spatial context of new renewable energy infrastructure will determine, in part, the environmental, social, and technical impacts of the energy transition. This paper presents the ADVENT-NEV model which brings together innovations in energy and natural capital modelling to identify the optimal locations of multiple renewable energy technologies at a national scale and high spatial resolution. Using Great Britain as a case study, the results show how the spatial distribution of renewable energy technologies changes when a natural capital approach is taken. In particular, the least-cost locations for onshore wind farms and bioenergy crops are highly influenced by the value of carbon sequestration, or emissions associated with their land use change. Siting using a natural capital approach produced appreciable ecosystem service benefits, such that the overall welfare gain to society was estimated at nearly £25 B. Overall, this paper demonstrates that understanding the geospatial context of the energy transition is essential to identifying which renewable energy pathways are consistent with decarbonisation and environmental objectives. [Display omitted] [ABSTRACT FROM AUTHOR]